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Yang Chen

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astro-ph.HE astro-ph.GA Computer Vision math-ph math.MP astro-ph.SR eess.SP math.CA astro-ph.CO eess.IV Machine Learning Information Theory math.IT physics.optics math.ST quant-ph Statistics Theory Computation and Language nlin.SI Artificial Intelligence astro-ph Cryptography and Security hep-th math.PR physics.chem-ph physics.ins-det physics.med-ph hep-ex math.RA physics.plasm-ph Software Engineering Applications astro-ph.IM cond-mat.mes-hall cond-mat.mtrl-sci Distributed, Parallel, and Cluster Computing eess.AS Methodology physics.app-ph astro-ph.EP Computation Computational Complexity Computational Engineering, Finance, and Science Computer Science and Game Theory cond-mat cond-mat.dis-nn cond-mat.other cond-mat.stat-mech cond-mat.str-el cond-mat.supr-con eess.SY hep-ph Human-Computer Interaction math.FA math.SP Multiagent Systems Networking and Internet Architecture Neurons and Cognition Numerical Analysis physics.comp-ph physics.data-an physics.space-ph Programming Languages q-fin.GN Social and Information Networks Sound Systems and Control

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preprint2026arXiv

A neural network for modeling human concept formation, understanding and communication

A remarkable capability of the human brain is to form more abstract conceptual representations from sensorimotor experiences and flexibly apply them independent of direct sensory inputs. However, the computational mechanism underlying this ability remains poorly understood. Here, we present a dual-module neural network framework, the CATS Net, to bridge this gap. Our model consists of a concept-abstraction module that extracts low-dimensional conceptual representations, and a task-solving module that performs visual judgement tasks under the hierarchical gating control of the formed concepts. The system develops transferable semantic structure based on concept representations that enable cross-network knowledge transfer through conceptual communication. Model-brain fitting analyses reveal that these emergent concept spaces align with both neurocognitive semantic model and brain response structures in the human ventral occipitotemporal cortex, while the gating mechanisms mirror that in the semantic control brain network. This work establishes a unified computational framework that can offer mechanistic insights for understanding human conceptual cognition and engineering artificial systems with human-like conceptual intelligence.

preprint2026arXiv

DB-MSMUNet:Dual Branch Multi-scale Mamba UNet for Pancreatic CT Scans Segmentation

Accurate segmentation of the pancreas and its lesions in CT scans is crucial for the precise diagnosis and treatment of pancreatic cancer. However, it remains a highly challenging task due to several factors such as low tissue contrast with surrounding organs, blurry anatomical boundaries, irregular organ shapes, and the small size of lesions. To tackle these issues, we propose DB-MSMUNet (Dual-Branch Multi-scale Mamba UNet), a novel encoder-decoder architecture designed specifically for robust pancreatic segmentation. The encoder is constructed using a Multi-scale Mamba Module (MSMM), which combines deformable convolutions and multi-scale state space modeling to enhance both global context modeling and local deformation adaptation. The network employs a dual-decoder design: the edge decoder introduces an Edge Enhancement Path (EEP) to explicitly capture boundary cues and refine fuzzy contours, while the area decoder incorporates a Multi-layer Decoder (MLD) to preserve fine-grained details and accurately reconstruct small lesions by leveraging multi-scale deep semantic features. Furthermore, Auxiliary Deep Supervision (ADS) heads are added at multiple scales to both decoders, providing more accurate gradient feedback and further enhancing the discriminative capability of multi-scale features. We conduct extensive experiments on three datasets: the NIH Pancreas dataset, the MSD dataset, and a clinical pancreatic tumor dataset provided by collaborating hospitals. DB-MSMUNet achieves Dice Similarity Coefficients of 89.47%, 87.59%, and 89.02%, respectively, outperforming most existing state-of-the-art methods in terms of segmentation accuracy, edge preservation, and robustness across different datasets. These results demonstrate the effectiveness and generalizability of the proposed method for real-world pancreatic CT segmentation tasks.

preprint2026arXiv

HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer

The evolution of visual generative models has long been constrained by fragmented architectures relying on disjoint text encoders and external VAEs. In this report, we present HiDream-O1-Image, a natively unified generative foundation model via pixel-space Diffusion Transformer, that pioneers a paradigm shift from modular architectures to an end-to-end in-context visual generation engine. By mapping raw image pixels, text tokens, and task-specific conditions into a single shared token space, HiDream-O1-Image achieves a structural unification of multimodal inputs within an Unified Transformer (UiT) architecture. This native encoding paradigm eliminates the need for separate VAEs or disjoint pre-trained text encoders, allowing the model to treat diverse generation and editing tasks as a consistent in-context reasoning process. Extensive experiments show that HiDream-O1-Image excels across various generation tasks, including text-to-image generation, instruction-based editing, and subject-driven personalization. Notably, with only 8B parameters, HiDream-O1-Image (8B) achieves performance parity with or even surpasses established state-of-the-art models with significantly larger parameters (e.g., 27B Qwen-Image). Crucially, to validate the immense scalability of this paradigm, we successfully scale the architecture up to over 200B parameters. Experimental results demonstrate that this massive-scale version HiDream-O1-Image-Pro (200B+) unlocks unprecedented generative capabilities and superior performance, establishing new state-of-the-art benchmarks. Ultimately, HiDream-O1-Image highlights the immense potential of natively unified architectures and charts a highly scalable path toward next-generation multimodal AI.

preprint2026arXiv

LLMRouterBench: A Massive Benchmark and Unified Framework for LLM Routing

Large language model (LLM) routing assigns each query to the most suitable model from an ensemble. We introduce LLMRouterBench, a large-scale benchmark and unified framework for LLM routing. It comprises over 400K instances from 21 datasets and 33 models. Moreover, it provides comprehensive metrics for both performance-oriented routing and performance-cost trade-off routing, and integrates 10 representative routing baselines. Using LLMRouterBench, we systematically re-evaluate the field. While confirming strong model complementarity-the central premise of LLM routing-we find that many routing methods exhibit similar performance under unified evaluation, and several recent approaches, including commercial routers, fail to reliably outperform a simple baseline. Meanwhile, a substantial gap remains to the Oracle, driven primarily by persistent model-recall failures. We further show that backbone embedding models have limited impact, that larger ensembles exhibit diminishing returns compared to careful model curation, and that the benchmark also enables latency-aware analysis. All code and data are available at https://github.com/ynulihao/LLMRouterBench.

preprint2026arXiv

Mitigating Prompt-Induced Hallucinations in Large Language Models via Structured Reasoning

To address hallucination issues in large language models (LLMs), this paper proposes a method for mitigating prompt-induced hallucinations. Building on a knowledge distillation chain-style model, we introduce a code module to guide knowledge-graph exploration and incorporate code as part of the chain-of-thought prompt, forming an external knowledge input that provides more accurate and structured information to the model. Based on this design, we develop an improved knowledge distillation chain-style model and leverage it to analyze and constrain the reasoning process of LLMs, thereby improving inference accuracy. We empirically evaluate the proposed approach using GPT-4 and LLaMA-3.3 on multiple public datasets. Experimental results demonstrate that incorporating code modules significantly enhances the model's ability to capture contextual information and effectively mitigates prompt-induced hallucinations. Specifically, HIT@1, HIT@3, and HIT@5 improve by 15.64%, 13.38%, and 13.28%, respectively. Moreover, the proposed method achieves HIT@1, HIT@3, and HIT@5 scores exceeding 95% across several evaluation settings. These results indicate that the proposed approach substantially reduces hallucination behavior while improving the accuracy and verifiability of large language models.

preprint2026arXiv

Residual Gaussian Splatting for Ultra Sparse-View CBCT Reconstruction

While 3D Gaussian splatting (3DGS) offers explicit and efficient scene representations for cone-beam computed tomography reconstruction, conventional photometric optimization inherently suffers from spectral bias under ultra sparse-view conditions, leading to over-smoothing and a loss of high-frequency anatomical details. Since wavelet transforms provide rich high-frequency information and have been widely utilized to enhance sparse reconstruction, this work integrates wavelet multi-resolution analysis with 3DGS. To circumvent the mathematical mismatch between the strict non-negativity of physical X-ray attenuation and the bipolar nature of high-frequency wavelet coefficients, we propose Residual Gaussian Splatting (RGS). Methodologically, we introduce a spectrally-decoupled Gaussian representation that stratifies the volumetric field into a geometric base component and a residual detail component. This decomposition systematically transforms explicit high-frequency fitting into a physically consistent, implicit residual compensation task. Furthermore, we devise a spectral-spatial collaborative optimization strategy to coordinate the interplay between geometric anchoring and texture refinement, effectively preventing spectral crosstalk. Extensive experiments on clinical datasets demonstrate that RGS enables the reconstructed images to capture highly refined geometric textures. It successfully resolves the trade-off between artifact suppression and detail preservation, yielding superior visual fidelity in complex trabecular and vascular structures compared to existing neural rendering baselines.

preprint2026arXiv

Towards Understanding and Characterizing Vulnerabilities in Intelligent Connected Vehicles through Real-World Exploits

Intelligent Connected Vehicles (ICVs) are a core component of modern transportation systems, and their security is crucial as it directly relates to user safety. Despite prior research, most existing studies focus only on specific sub-components of ICVs due to their inherent complexity. As a result, there is a lack of systematic understanding of ICV vulnerabilities. Moreover, much of the current literature relies on human subjective analysis, such as surveys and interviews, which tends to be high-level and unvalidated, leaving a significant gap between theoretical findings and real-world attacks. To address this issue, we conducted the first large-scale empirical study on ICV vulnerabilities. We began by analyzing existing ICV security literature and summarizing the prevailing taxonomies in terms of vulnerability locations and types. To evaluate their real-world relevance, we collected a total of 649 exploitable vulnerabilities, including 592 from eight ICV vulnerability discovery competitions, Anonymous Cup, between January 2023 and April 2024, covering 48 different vehicles. The remaining 57 vulnerabilities were submitted daily by researchers. Based on this dataset, we assessed the coverage of existing taxonomies and identified several gaps, discovering one new vulnerability location and 13 new vulnerability types. We further categorized these vulnerabilities into 6 threat types (e.g., privacy data breach) and 4 risk levels (ranging from low to critical) and analyzed participants' skills and the types of ICVs involved in the competitions. This study provides a comprehensive and data-driven analysis of ICV vulnerabilities, offering actionable insights for researchers, industry practitioners, and policymakers. To support future research, we have made our vulnerability dataset publicly available.

preprint2025arXiv

Ultrahigh-Energy Gamma-ray Emission Associated with Black Hole-Jet Systems

Black holes (BH), one of the most intriguing objects in the universe, can manifest themselves through electromagnetic radiation initiated by the accretion flow. Some stellar-mass BHs drive relativistic jets when accreting matter from their companion stars, forming microquasars. Non-thermal emission from the radio to tera-electronvolt (TeV) gamma-ray band has been observed from microquasars, indicating the acceleration of relativistic particles. Here we report detection of four microquasars (SS 433, V4641 Sgr, GRS 1915+105, MAXI J1820+070) of spectrum extending to the ultrahigh-energy (UHE; photon energy $E>100$ TeV) band and one microquasar (Cygnus X-1) of spectrum approaching 100 TeV, using the Large High Altitude Air Shower Observatory (LHAASO). Notably, the total emission associated with SS 433 cannot be interpreted with a single leptonic component. In the UHE band, its emission is in spatial coincidence with a giant atomic cloud, which is consistent with a hadronic origin. An elongated source is discovered from V4641 Sgr with the spectrum continuing up to 800 TeV. The detection of UHE gamma rays demonstrates that accreting BHs and their environments can operate as extremely efficient accelerators of particles out of 1 peta-electronvolt (PeV), suggesting microquasars to be important contributors to Galactic cosmic rays especially around the `knee' region.

preprint2024arXiv

tf.data service: A Case for Disaggregating ML Input Data Processing

Machine learning (ML) computations commonly execute on expensive specialized hardware, such as GPUs and TPUs, which provide high FLOPs and performance-per-watt. For cost efficiency, it is essential to keep these accelerators highly utilized. This requires preprocessing input data at the rate at which the accelerators can ingest and perform ML computations on the data. To avoid data stalls, the host CPU and RAM required for input data processing per accelerator core used for ML computations varies across jobs. Hence, the traditional approach of processing input data on ML accelerator hosts with a fixed hardware ratio leads to either under-utilizing the accelerators or the host CPU and RAM. In this paper, we address these concerns by building a disaggregated ML data processing system. We present tf.data service, an open-source disaggregated input data processing service built on top of tf.data in TensorFlow. We show that disaggregating data preprocessing has three key advantages for large-scale ML training jobs. First, the service can horizontally scale-out to right-size CPU/RAM host resources for data processing in each job, saving 32x training time and 26x cost, on average. Second, the service can share ephemeral preprocessed data results across jobs, to optimize CPU usage and reduce redundant computations. Finally, the service supports coordinated reads, a technique that avoids stragglers due to different input sizes in distributed training, reducing training time by 2.2x, on average. Our design is inspired by lessons learned from deploying tf.data service in production, including relaxing data visitation guarantees without impacting model accuracy.

preprint2023arXiv

Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning

The performance of existing underwater object detection methods degrades seriously when facing domain shift caused by complicated underwater environments. Due to the limitation of the number of domains in the dataset, deep detectors easily memorize a few seen domains, which leads to low generalization ability. There are two common ideas to improve the domain generalization performance. First, it can be inferred that the detector trained on as many domains as possible is domain-invariant. Second, for the images with the same semantic content in different domains, their hidden features should be equivalent. This paper further excavates these two ideas and proposes a domain generalization framework (named DMC) that learns how to generalize across domains from Domain Mixup and Contrastive Learning. First, based on the formation of underwater images, an image in an underwater environment is the linear transformation of another underwater environment. Thus, a style transfer model, which outputs a linear transformation matrix instead of the whole image, is proposed to transform images from one source domain to another, enriching the domain diversity of the training data. Second, mixup operation interpolates different domains on the feature level, sampling new domains on the domain manifold. Third, contrastive loss is selectively applied to features from different domains to force the model to learn domain invariant features but retain the discriminative capacity. With our method, detectors will be robust to domain shift. Also, a domain generalization benchmark S-UODAC2020 for detection is set up to measure the performance of our method. Comprehensive experiments on S-UODAC2020 and two object recognition benchmarks (PACS and VLCS) demonstrate that the proposed method is able to learn domain-invariant representations, and outperforms other domain generalization methods.

preprint2023arXiv

Analytical Approximations for Generalized Landau-Zener Transitions in Multi-level Non-Hermitian Systems

We study the dynamics of non-adiabatic transitions in non-Hermitian multi-level parabolic models where the separations of the diabatic energies are quadratic function of time. The model Hamiltonian has been used to describe the non-Hermitian dynamics of two pairs of coupled cavities. In the absence of the coupling between any two pairs of cavities, the wave amplitudes within each subsystem are described by the tri-confluent Heun functions. When all the couplings between the cavities are present, we reduce the dynamics into a set of two coupled tri-confluent Heun equations, from which we derive analytical approximations for the wave amplitudes at different physical limits.

preprint2023arXiv

The Bending of C$_3$: Experimentally Probing the $l$-type Doubling and Resonance

C$_3$, a pure carbon chain molecule that has been identified in different astronomical environments, is considered a good probe of kinetic temperatures through observation of transitions involving its low-lying bending mode ($ν_2$) in its ground electronic state. The present laboratory work aims to investigate this bending mode with multiple quanta of excitation by combining recordings of high resolution optical and infrared spectra of C$_3$ produced in discharge experiments. The optical spectra of rovibronic (A $^1Π_u -$ X $^1Σ_g^+$) transitions have been recorded by laser induced fluorescence spectroscopy using a single longitude mode optical parametric oscillator as narrow bandwidth laser source at the University of Science and Technology of China. 36 bands originating from X(0$v_2$0), $v_2 = 0-5$, are assigned. The mid-infrared spectrum of the rovibrational $ν_3$ band has been recorded by Fourier-transform infrared spectroscopy using a globar source on the AILES beamline of the SOLEIL synchrotron facility. The spectrum reveals hot bands involving up to 5 quanta of excitation in $ν_2$. From combining analyses of all the presently recorded spectra and literature data, accurate rotational parameters and absolute energy levels of C$_3$, in particular for states involving the bending mode, are determined. A single PGOPHER file containing all available data involving the X and A states (literature and present study) is used to fit all the data. The spectroscopic information derived from this work enables new interstellar searches for C$_3$, not only in the infrared and optical regions investigated here but also notably in the $ν_2$ band region (around 63 cm$^{-1}$) where vibrational satellites can now be accurately predicted. This makes C$_3$ a universal diagnostic tool to study very different astronomical environments, from dark and dense to translucent clouds.

preprint2022arXiv

A Possible Gamma-Ray Enhancement Event in Tycho's Supernova Remnant

We report a possible $γ$-ray enhancement event detected from Tycho's supernova remnant (SNR), the outcome of a type Ia supernova explosion that occurred in year 1572. The event lasted for 1.5 years and showed a factor of 3.6 flux increase mainly in the energy range of 4--100 GeV, while notably accompanied with two 478\,GeV photons. Several young SNRs (including Tycho's SNR) were previously found to show peculiar X-ray structures with flux variations in one- or several-year timescales, such an event at $γ$-ray energies is for the first time seen. The year-long timescale of the event suggests a synchrotron radiation process, but the hard $γ$-ray emission requires extreme conditions of either ultra-high energies for the electrons upto $\sim$10 PeV (well above the cosmic-ray "knee" energy) or high inhomogeneity of the magnetic field in the SNR. This event in Tycho's SNR is likely analogous to the $γ$-ray flares observed in the Crab nebula, the comparably short timescales of them both requiring a synchrotron process, and similar magnetohydrodynamic processes such as magnetic reconnection would be at work as well in the SNR to accelerate particles to ultra-relativistic energies. The event, if confirmed, helps reveal the more complicated side of the physical processes that can occur in young SNRs.

preprint2022arXiv

Analytical study on magnetic component of geodesic acoustic mode

The magnetic components of geodesic acoustic mode (GAM) are analytically investigated under the gyrokinetic framework with both the m=1 and m=2 harmonics are considered, where m is the poloidal mode number. With the quasi-neutrality condition and Ampere's law, the amplitudes of various poloidal magnetic components are derived. It is shown that both m=1 and m=2 magnetic components exist and are dominated by the cosine and sine components, respectively. In addition, it is found that the amplitudes of all magnetic components increase with respect to the ratio of plasma pressure to magnetic pressure \b{eta} and safety factor q. Most importantly, the amplitude of m=1 magnetic component is significantly enhanced due to the coupling of magnetic drift frequency with the first and second harmonics of the distribution functions, thus it can be comparable to that of m=2 magnetic component under certain conditions.

preprint2022arXiv

Beam pointing stabilization of an acousto-optic modulator with thermal control

Diffraction beams generated by an acousto-optic modulator (AOM) are widely used in various optical experiments, some of which require high angular stability with the temporal modulation of optical power. Usually, it is difficult to realize both angular stability and high-power modulation in a passive setup without a servo system of radio-frequency compensation. Here, we present a method to suppress the angular drift and pointing noise only with the thermal management of the AOM crystal. We analyze the dependence of the angular drift on the refractive index variation, and find that the angular drift is very sensitivity to the temperature gradient which could induce the refractive index gradient inside the AOM crystal. It reminds us such angular drift could be significantly suppressed by carefully overlapping the zero temperature gradient area with the position of the acousto-optic interaction zone. We implement a water-cooling setup, and find that the angular drift of an AOM is reduced over 100 times during the thermal transient, and the angular noise is also suppressed to 1/3 of the non-cooled case. It should be emphasized that this thermal control method is a general to suppress the beam drift in both the diffraction and the perpendicular-to-diffraction directions. The refractive index thermal coefficient of tellurium dioxide crystal at 1064 nm determined by this angular drift-temperature model is 16$\times$10$^{-6}$ K$^{-1}$ consistent with previous studies. This thermal control technique provides potential applications for optical trapping and remote sensoring that demand for intensity ramps.

preprint2022arXiv

Breaking the accuracy and resolution limitation of filter- and frequency-to-time mapping-based time and frequency acquisition methods by broadening the filter bandwidth

In this paper, the filter- and frequency-to-time mapping (FTTM)-based photonics-assisted time and frequency acquisition methods are comprehensively analyzed and the accuracy and resolution limitation in the fast sweep scenario is broken by broadening the filter bandwidth. It is found that when the sweep speed is very fast, the width of the generated pulse via FTTM is mainly determined by the impulse response of the filter. In this case, appropriately increasing the filter bandwidth can significantly reduce the pulse width, so as to improve the measurement accuracy and resolution. FTTM-based short-time Fourier transform (STFT) and microwave frequency measurement using the stimulated Brillouin scattering (SBS) effect is demonstrated by comparing the results with and without SBS gain spectrum broadening and the improvement of measurement accuracy and frequency resolution is well confirmed. The frequency measurement accuracy of the system is improved by around 25 times compared with the former work using a similar sweep speed, while the frequency resolution of the STFT is also much improved compared with our former results.

preprint2022arXiv

Distribution of the Scaled Condition Number of Single-spiked Complex Wishart Matrices

Let $\mathbf{X}\in\mathbb{C}^{n\times m}$ ($m\geq n$) be a random matrix with independent columns each distributed as complex multivariate Gaussian with zero mean and {\it single-spiked} covariance matrix $\mathbf{I}_n+ η\mathbf{u}\mathbf{u}^*$, where $\mathbf{I}_n$ is the $n\times n$ identity matrix, {\color{blue}$\mathbf{u}\in\mathbb{C}^{n\times 1}$} is an arbitrary vector with unit Euclidean norm, $η\geq 0$ is a non-random parameter, and $(\cdot)^*$ represents the conjugate-transpose. This paper investigates the distribution of the random quantity $κ_{\text{SC}}^2(\mathbf{X})=\sum_{k=1}^n λ_k/λ_1$, where {\color{blue}$0\le λ_1\le λ_2\le \ldots\leq λ_n<\infty$} are the ordered eigenvalues of $\mathbf{X}\mathbf{X}^*$ (i.e., single-spiked Wishart matrix). This random quantity is intimately related to the so called {\it scaled condition number} or the Demmel condition number (i.e., $κ_{\text{SC}}(\mathbf{X})$) and the minimum eigenvalue of the fixed trace Wishart-Laguerre ensemble (i.e., $κ_{\text{SC}}^{-2}(\mathbf{X})$). In particular, we use an orthogonal polynomial approach to derive an exact expression for the probability density function of $κ_{\text{SC}}^2(\mathbf{X})$ which is amenable to asymptotic analysis as matrix dimensions grow large. Our asymptotic results reveal that, as $m,n\to\infty$ such that $m-n$ is fixed and when $η$ scales on the order of $1/n$, $κ_{\text{SC}}^2(\mathbf{X})$ scales on the order of $n^3$. In this respect we establish simple closed-form expressions for the limiting distributions. {\color{blue}It turns out that, as $m,n\to\infty$ such that $n/m\to c\in(0,1)$, properly centered $κ_{\text{SC}}^{2}(\mathbf{X})$ fluctuates on the scale $m^{\frac{1}{3}}$}.

preprint2022arXiv

foREST: A Tree-based Approach for Fuzzing RESTful APIs

Representational state transfer (REST) is a widely employed architecture by web applications and cloud. Users can invoke such services according to the specification of their application interfaces, namely RESTful APIs. Existing approaches for fuzzing RESTful APIs are generally based on classic API-dependency graphs. However, such dependencies are inefficient for REST services due to the explosion of dependencies among APIs. In this paper, we propose a novel tree-based approach that can better capture the essential dependencies and largely improve the efficiency of RESTful API fuzzing. In particular, the hierarchical information of the endpoints across multiple APIs enables us to construct an API tree, and the relationships of tree nodes can indicate the priority of resource dependencies, \textit{e.g.,} it's more likely that a node depends on its parent node rather than its offspring or siblings. In the evaluation part, we first confirm that such a tree-based approach is more efficient than traditional graph-based approaches. We then apply our tool to fuzz two real-world RESTful services and compare the performance with two state-of-the-art tools, EvoMaster and RESTler. Our results show that foREST can improve the code coverage in all experiments, ranging from 11.5\% to 82.5\%. Besides, our tool finds 11 new bugs previously unknown.

preprint2022arXiv

Geometric Conditions for the Discrepant Posterior Phenomenon and Connections to Simpson's Paradox

The discrepant posterior phenomenon (DPP) is a counter-intuitive phenomenon that can frequently occur in a Bayesian analysis of multivariate parameters. It refers to the phenomenon that a parameter estimate based on a posterior is more extreme than both of those inferred based on either the prior or the likelihood alone. Inferential claims that exhibit DPP defy the common intuition that the posterior is a prior-data compromise, and the phenomenon can be surprisingly ubiquitous in well-behaved Bayesian models. In this paper we revisit this phenomenon and, using point estimation as an example, derive conditions under which the DPP occurs in Bayesian models with exponential quadratic likelihoods and conjugate multivariate Gaussian priors. The family of exponential quadratic likelihood models includes Gaussian models and those models with local asymptotic normality property. We provide an intuitive geometric interpretation of the phenomenon and show that there exists a nontrivial space of marginal directions such that the DPP occurs. We further relate the phenomenon to the Simpson's paradox and discover their deep-rooted connection that is associated with marginalization. We also draw connections with Bayesian computational algorithms when difficult geometry exists. Our discovery demonstrates that DPP is more prevalent than previously understood and anticipated. Theoretical results are complemented by numerical illustrations. Scenarios covered in this study have implications for parameterization, sensitivity analysis, and prior choice for Bayesian modeling.

preprint2022arXiv

GeV Gamma-ray Emission and Molecular Clouds towards Supernova Remnant G35.6$-$0.4 and the TeV Source HESS J1858+020

It is difficult to distinguish hadronic process from the leptonic one in $γ$-ray observation, which is however crucial in revealing the origin of cosmic rays. As an endeavor in the regard, we focus in this work on the complex $γ$-ray emitting region, which partially overlaps with the unidentified TeV source HESS~J1858+020 and includes supernova remnant (SNR) G35.6$-$0.4 and HII region G35.6$-$0.5. We reanalyze CO-line, HI, and Fermi-LAT GeV $γ$-ray emission data of this region. The analysis of the molecular and HI data suggests that SNR G35.6$-$0.4 and HII region G35.6$-$0.5 are located at different distances. The analysis the GeV $γ$-rays shows that GeV emission arises from two point sources: one (SrcA) coincident with the SNR, and the other (SrcB) coincident with both HESS J1858+020 and HII region G35.6$-$0.5. The GeV emission of SrcA can be explained by the hadronic process in the SNR-MC association scenario. The GeV-band spectrum of SrcB and the TeV-band spectrum of HESS J1858+020 can be smoothly connected by a power-law function, with an index of $\sim$2.2. The connected spectrum is well explained with a hadronic emission, with the cutoff energy of protons above 1 PeV. It thus indicates that there is a potential PeVatron in the HII region and should be further verified with ultra-high energy observations with, e.g., LHAASO.

preprint2022arXiv

Graph Fourier transform based on singular value decomposition of directed Laplacian

Graph Fourier transform (GFT) is a fundamental concept in graph signal processing. In this paper, based on singular value decomposition of Laplacian, we introduce a novel definition of GFT on directed graphs, and use singular values of Laplacian to carry the notion of graph frequencies. % of the proposed GFT. The proposed GFT is consistent with the conventional GFT in the undirected graph setting, and on directed circulant graphs, the proposed GFT is the classical discrete Fourier transform, up to some rotation, permutation and phase adjustment. We show that frequencies and frequency components of the proposed GFT can be evaluated by solving some constrained minimization problems with low computational cost. Numerical demonstrations indicate that the proposed GFT could represent graph signals with different modes of variation efficiently.

preprint2022arXiv

Graph Fourier transforms on directed product graphs

Graph Fourier transform (GFT) is one of the fundamental tools in graph signal processing to decompose graph signals into different frequency components and to represent graph signals with strong correlation by different modes of variation effectively. The GFT on undirected graphs has been well studied and several approaches have been proposed to define GFTs on directed graphs. In this paper, based on the singular value decompositions of some graph Laplacians, we propose two GFTs on the Cartesian product graph of two directed graphs. We show that the proposed GFTs could represent spatial-temporal data sets on directed networks with strong correlation efficiently, and in the undirected graph setting they are essentially the joint GFT in the literature. In this paper, we also consider the bandlimiting procedure in the spectral domain of the proposed GFTs, and demonstrate its performance to denoise the temperature data set in the region of Brest (France) on January 2014.

preprint2022arXiv

Individual-Level Inverse Reinforcement Learning for Mean Field Games

The recent mean field game (MFG) formalism has enabled the application of inverse reinforcement learning (IRL) methods in large-scale multi-agent systems, with the goal of inferring reward signals that can explain demonstrated behaviours of large populations. The existing IRL methods for MFGs are built upon reducing an MFG to a Markov decision process (MDP) defined on the collective behaviours and average rewards of the population. However, this paper reveals that the reduction from MFG to MDP holds only for the fully cooperative setting. This limitation invalidates existing IRL methods on MFGs with non-cooperative environments. To measure more general behaviours in large populations, we study the use of individual behaviours to infer ground-truth reward functions for MFGs. We propose Mean Field IRL (MFIRL), the first dedicated IRL framework for MFGs that can handle both cooperative and non-cooperative environments. Based on this theoretically justified framework, we develop a practical algorithm effective for MFGs with unknown dynamics. We evaluate MFIRL on both cooperative and mixed cooperative-competitive scenarios with many agents. Results demonstrate that MFIRL excels in reward recovery, sample efficiency and robustness in the face of changing dynamics.

preprint2022arXiv

Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering

Effective multi-hop question answering (QA) requires reasoning over multiple scattered paragraphs and providing explanations for answers. Most existing approaches cannot provide an interpretable reasoning process to illustrate how these models arrive at an answer. In this paper, we propose a Question Decomposition method based on Abstract Meaning Representation (QDAMR) for multi-hop QA, which achieves interpretable reasoning by decomposing a multi-hop question into simpler sub-questions and answering them in order. Since annotating the decomposition is expensive, we first delegate the complexity of understanding the multi-hop question to an AMR parser. We then achieve the decomposition of a multi-hop question via segmentation of the corresponding AMR graph based on the required reasoning type. Finally, we generate sub-questions using an AMR-to-Text generation model and answer them with an off-the-shelf QA model. Experimental results on HotpotQA demonstrate that our approach is competitive for interpretable reasoning and that the sub-questions generated by QDAMR are well-formed, outperforming existing question-decomposition-based multi-hop QA approaches.

preprint2022arXiv

Matrix Completion Methods for the Total Electron Content Video Reconstruction

The total electron content (TEC) maps can be used to estimate the signal delay of GPS due to the ionospheric electron content between a receiver and satellite. This delay can result in GPS positioning error. Thus it is important to monitor the TEC maps. The observed TEC maps have big patches of missingness in the ocean and scattered small areas of missingness on the land. In this paper, we propose several extensions of existing matrix completion algorithms to achieve TEC map reconstruction, accounting for spatial smoothness and temporal consistency while preserving important structures of the TEC maps. We call the proposed method Video Imputation with SoftImpute, Temporal smoothing and Auxiliary data (VISTA). Numerical simulations that mimic patterns of real data are given. We show that our proposed method achieves better reconstructed TEC maps as compared to existing methods in literature. Our proposed computational algorithm is general and can be readily applied for other problems besides TEC map reconstruction.

preprint2022arXiv

MetaComp: Learning to Adapt for Online Depth Completion

Relying on deep supervised or self-supervised learning, previous methods for depth completion from paired single image and sparse depth data have achieved impressive performance in recent years. However, facing a new environment where the test data occurs online and differs from the training data in the RGB image content and depth sparsity, the trained model might suffer severe performance drop. To encourage the trained model to work well in such conditions, we expect it to be capable of adapting to the new environment continuously and effectively. To achieve this, we propose MetaComp. It utilizes the meta-learning technique to simulate adaptation policies during the training phase, and then adapts the model to new environments in a self-supervised manner in testing. Considering that the input is multi-modal data, it would be challenging to adapt a model to variations in two modalities simultaneously, due to significant differences in structure and form of the two modal data. Therefore, we further propose to disentangle the adaptation procedure in the basic meta-learning training into two steps, the first one focusing on the depth sparsity while the second attending to the image content. During testing, we take the same strategy to adapt the model online to new multi-modal data. Experimental results and comprehensive ablations show that our MetaComp is capable of adapting to the depth completion in a new environment effectively and robust to changes in different modalities.

preprint2022arXiv

MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation

The nature of thick-slice scanning causes severe inter-slice discontinuities of 3D medical images, and the vanilla 2D/3D convolutional neural networks (CNNs) fail to represent sparse inter-slice information and dense intra-slice information in a balanced way, leading to severe underfitting to inter-slice features (for vanilla 2D CNNs) and overfitting to noise from long-range slices (for vanilla 3D CNNs). In this work, a novel mesh network (MNet) is proposed to balance the spatial representation inter axes via learning. 1) Our MNet latently fuses plenty of representation processes by embedding multi-dimensional convolutions deeply into basic modules, making the selections of representation processes flexible, thus balancing representation for sparse inter-slice information and dense intra-slice information adaptively. 2) Our MNet latently fuses multi-dimensional features inside each basic module, simultaneously taking the advantages of 2D (high segmentation accuracy of the easily recognized regions in 2D view) and 3D (high smoothness of 3D organ contour) representations, thus obtaining more accurate modeling for target regions. Comprehensive experiments are performed on four public datasets (CT\&MR), the results consistently demonstrate the proposed MNet outperforms the other methods. The code and datasets are available at: https://github.com/zfdong-code/MNet

preprint2022arXiv

Multiple Instance Learning with Mixed Supervision in Gleason Grading

With the development of computational pathology, deep learning methods for Gleason grading through whole slide images (WSIs) have excellent prospects. Since the size of WSIs is extremely large, the image label usually contains only slide-level label or limited pixel-level labels. The current mainstream approach adopts multi-instance learning to predict Gleason grades. However, some methods only considering the slide-level label ignore the limited pixel-level labels containing rich local information. Furthermore, the method of additionally considering the pixel-level labels ignores the inaccuracy of pixel-level labels. To address these problems, we propose a mixed supervision Transformer based on the multiple instance learning framework. The model utilizes both slide-level label and instance-level labels to achieve more accurate Gleason grading at the slide level. The impact of inaccurate instance-level labels is further reduced by introducing an efficient random masking strategy in the mixed supervision training process. We achieve the state-of-the-art performance on the SICAPv2 dataset, and the visual analysis shows the accurate prediction results of instance level. The source code is available at https://github.com/bianhao123/Mixed_supervision.

preprint2022arXiv

Optical vortex Brillouin laser

Optical vortices, which have been extensively studied over the last decades, offer an additional degree of freedom useful in many applications, such as optical tweezers and quantum control. Stimulated Brillouin scattering, providing a narrow linewidth and a strong nonlinear response, has been used to realise quasi-continuous wave (CW) lasers. Here, we report stable oscillation of optical vortices and acoustic modes in a Brillouin laser based on chiral photonic crystal fibre, which robustly supports helical Bloch modes (HBMs) that carry circularly-polarized optical vortex and display circular birefringence. We implement a narrow-linewidth Brillouin fibre laser that stably emits 1st- and 2nd-order vortex-carrying HBMs. Angular momentum conservation selection rules dictate that pump and backward Brillouin signals have opposite topological charge and spin. Additionally, we show that when the chiral PCF is placed within a laser ring cavity, the linewidth-narrowing associated with lasing permits the peak of the Brillouin gain that corresponds to acoustic mode to be measured with resolution of 10 kHz and accuracy of 520 kHz. The results pave the way to a new generation of vortex-carrying SBS systems with applications in quantum information processing, vortex-carrying nonreciprocal systems.

preprint2022arXiv

Photonics-Assisted Joint Communication-Radar System Based on a QPSK-Sliced Linearly Frequency-Modulated Signal

A photonics-assisted joint communication-radar system is proposed and experimentally demonstrated, by introducing a quadrature phase-shift keying (QPSK)-sliced linearly frequency-modulated (LFM) signal. An LFM signal is carrier-suppressed single-sideband modulated onto the optical carrier in one dual-parallel Mach-Zehnder modulator (DPMZM) of a dual-polarization dual-parallel Mach-Zehnder modulator (DPol-DPMZM). The other DPMZM of the DPol-DPMZM is biased as an IQ modulator to implement QPSK modulation on the optical carrier. The polarization orthogonal optical signals from the DPol-DPMZM are further combined and detected in a photodetector to generate the QPSK-sliced LFM signal, which is used to realize efficient data transmission and high-performance radar functions including ranging and imaging. An experiment is carried out. Radar range detection with an error of less than 4 cm, ISAR imaging with a resolution of 14.99 cm*3.25 cm, and communication with a data rate of 105.26 Mbit/s are successfully verified.

preprint2022arXiv

Photonics-enabled wavelet-like transform via nonlinear optical frequency sweeping and stimulated Brillouin scattering-based frequency-to-time mapping

A photonics-enabled wavelet-like transform system, characterized by multi-resolution time-frequency analysis, is proposed based on a typical stimulated Brillouin scattering (SBS) pump-probe setup using an optical nonlinear frequency-sweep signal. In the pump path, a continuous-wave optical signal is injected into an SBS medium to generate an SBS gain. In the probe path, a periodic nonlinear frequency-sweep optical signal with a time-varying chirp rate is generated, which is then modulated at a Mach-Zehnder modulator (MZM) by the electrical signal under test (SUT). The optical signal from the MZM is selectively amplified by the SBS gain and converted back to the electrical domain using a low-speed photodetector, implementing the periodic SBS-based frequency-to-time mapping (FTTM). The frequency-domain information corresponding to different periods is mapped to the time domain via the FTTM in the form of low-speed electrical pulses, which is then spliced to analyze the time-frequency relationship of the SUT in real-time. The time-varying chirp rate in each sweep period makes the signals with different frequencies have different frequency resolutions in the FTTM process, which is very similar to the characteristics of the wavelet transform, so we call it wavelet-like transform. An experiment is carried out. Multi-resolution time-frequency analysis of a variety of RF signals is carried out in a 4-GHz bandwidth limited only by the equipment.

preprint2022arXiv

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data

We consider the flare prediction problem that distinguishes flare-imminent active regions that produce an M- or X-class flare in the future 24 hours, from quiet active regions that do not produce any flare within $\pm 24$ hours. Using line-of-sight magnetograms and parameters of active regions in two data products covering Solar Cycle 23 and 24, we train and evaluate two deep learning algorithms -- CNN and LSTM -- and their stacking ensembles. The decisions of CNN are explained using visual attribution methods. We have the following three main findings. (1) LSTM trained on data from two solar cycles achieves significantly higher True Skill Scores (TSS) than that trained on data from a single solar cycle with a confidence level of at least 0.95. (2) On data from Solar Cycle 23, a stacking ensemble that combines predictions from LSTM and CNN using the TSS criterion achieves significantly higher TSS than the "select-best" strategy with a confidence level of at least 0.95. (3) A visual attribution method called Integrated Gradients is able to attribute the CNN's predictions of flares to the emerging magnetic flux in the active region. It also reveals a limitation of CNN as a flare prediction method using line-of-sight magnetograms: it treats the polarity artifact of line-of-sight magnetograms as positive evidence of flares.

preprint2022arXiv

Proximal PanNet: A Model-Based Deep Network for Pansharpening

Recently, deep learning techniques have been extensively studied for pansharpening, which aims to generate a high resolution multispectral (HRMS) image by fusing a low resolution multispectral (LRMS) image with a high resolution panchromatic (PAN) image. However, existing deep learning-based pansharpening methods directly learn the mapping from LRMS and PAN to HRMS. These network architectures always lack sufficient interpretability, which limits further performance improvements. To alleviate this issue, we propose a novel deep network for pansharpening by combining the model-based methodology with the deep learning method. Firstly, we build an observation model for pansharpening using the convolutional sparse coding (CSC) technique and design a proximal gradient algorithm to solve this model. Secondly, we unfold the iterative algorithm into a deep network, dubbed as Proximal PanNet, by learning the proximal operators using convolutional neural networks. Finally, all the learnable modules can be automatically learned in an end-to-end manner. Experimental results on some benchmark datasets show that our network performs better than other advanced methods both quantitatively and qualitatively.

preprint2022arXiv

Simulating the Legacy Survey of Space and Time stellar content with TRILEGAL

We describe a large simulation of the stars to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The simulation is based on the TRILEGAL code, which resorts to large databases of stellar evolutionary tracks, synthetic spectra, and pulsation models, added to simple prescriptions for the stellar density and star formation histories of the main structures of the Galaxy, to generate mock stellar samples through a population synthesis approach. The main bodies of the Magellanic Clouds are also included. A complete simulation is provided for single stars, down to the $r=27.5$ mag depth of the co-added wide-fast-deep survey images. A second simulation is provided for a fraction of the binaries, including the interacting ones, as derived with the BinaPSE module of TRILEGAL. We illustrate the main properties and numbers derived from these simulations, including: comparisons with real star counts; the expected numbers of Cepheids, long-period variables and eclipsing binaries; the crowding limits as a function of seeing and filter; the star-to-galaxy ratios, etc. Complete catalogs are accessible through the NOIRLab Astro Data Lab, while the stellar density maps are incorporated in the LSST metrics analysis framework (MAF).

preprint2022arXiv

Spatially decomposed $γ$-ray features surrounding SNR Kes 79 & PSR J1853+0056

There have been substantial improvements on Fermi Large Area Telescope (LAT) data and analysis tools since the last analysis on the mid-aged supernova remnant (SNR) Kes 79 (Auchettl et al. 2014). Recent multi-wavelength studies confirmed its interaction with molecular clouds. About $0.36\degr$ north from Kes 79, a powerful pulsar -- PSR J1853+0056 also deserves our attention. In this work, we analyse the 11.5-year Fermi-LAT data to investigate the $γ$-ray feature in/around this complex region. Our result shows a more significant detection ($\sim$34.8$σ$ in 0.1--50 GeV) for this region. With $\ge$5 GeV data, we detect two extended sources -- Src-N (the brighter one; radius $\approx0.31\degr$) concentrated at the north of the SNR while enclosing PSR J1853+0056, and Src-S (radius $\approx0.58\degr$) concentrated at the south of the SNR. Their spectra have distinct peak energies ($\sim$1.0 GeV for Src-N and $\lesssim$0.5 GeV for Src-S), suggesting different origins for them. In our hadronic model that includes the leaked cosmic-rays (CRs) from the shock-cloud collision, even with extreme values of parameters, SNR Kes 79 can by no means provide enough CRs reaching clouds at Src-N to explain the local GeV spectrum. We propose that the Src-N emission could be predominantly reproduced by a putative pulsar wind nebula (PWN) powered by PSR J1853+0056. On the other hand, our same hadronic model can reproduce a majority of the GeV emission at Src-S with typical values of parameters, while the three known pulsars inside Src-S release a total power that is too low to account for half of its $γ$-ray emission.

preprint2022arXiv

STELLA: Sparse Taint Analysis for Enclave Leakage Detection

Intel SGX (Software Guard Extension) is a promising TEE (trusted execution environment) technique that can protect programs running in user space from being maliciously accessed by the host operating system. Although it provides hardware access control and memory encryption, the actual effectiveness also depends on the quality of the software. In particular, improper implementation of a code snippet running inside the enclave may still leak private data due to the invalid use of pointers. This paper serves as a first attempt to study the privacy leakage issues of enclave code and proposes a novel static sparse taint analysis approach to detect them. We first summarize five common patterns of leakage code. Based on these patterns, our approach performs forward analysis to recognize all taint sinks and then employs a backward approach to detect leakages. Finally, we have conducted experiments with several open-source enclave programs and found 78 vulnerabilities previously unknown in 13 projects.

preprint2022arXiv

The Eigenvectors of Single-spiked Complex Wishart Matrices: Finite and Asymptotic Analyses

Let $\mathbf{W}\in\mathbb{C}^{n\times n}$ be a {\it single-spiked} Wishart matrix in the class $\mathbf{W}\sim \mathcal{CW}_n(m,\mathbf{I}_n+ θ\mathbf{v}\mathbf{v}^\dagger) $ with $m\geq n$, where $\mathbf{I}_n$ is the $n\times n$ identity matrix, $\mathbf{v}\in\mathbb{C}^{n\times 1}$ is an arbitrary vector with unit Euclidean norm, $θ\geq 0$ is a non-random parameter, and $(\cdot)^\dagger$ represents the conjugate-transpose operator. Let $\mathbf{u}_1$ and $\mathbf{u}_n$ denote the eigenvectors corresponding to the samllest and the largest eigenvalues of $\mathbf{W}$, respectively. This paper investigates the probability density function (p.d.f.) of the random quantity $Z_{\ell}^{(n)}=\left|\mathbf{v}^\dagger\mathbf{u}_\ell\right|^2\in(0,1)$ for $\ell=1,n$. In particular, we derive a finite dimensional closed-form p.d.f. for $Z_{1}^{(n)}$ which is amenable to asymptotic analysis as $m,n$ diverges with $m-n$ fixed. It turns out that, in this asymptotic regime, the scaled random variable $nZ_{1}^{(n)}$ converges in distribution to $χ^2_2/2(1+θ)$, where $χ_2^2$ denotes a chi-squared random variable with two degrees of freedom. This reveals that $\mathbf{u}_1$ can be used to infer information about the spike. On the other hand, the finite dimensional p.d.f. of $Z_{n}^{(n)}$ is expressed as a double integral in which the integrand contains a determinant of a square matrix of dimension $(n-2)$. Although a simple solution to this double integral seems intractable, for special configurations of $n=2,3$, and $4$, we obtain closed-form expressions.

preprint2022arXiv

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

preprint2022arXiv

Time-varying microwave photonic filter for arbitrary waveform signal-to-noise ratio improvement

A time-varying microwave photonic filter (TV-MPF) based on stimulated Brillouin scattering (SBS) is proposed and utilized to suppress the in-band noise of broadband arbitrary microwave waveforms, thereby improving the signal-to-noise ratio (SNR). The filter-controlling signal is designed according to the signal to be filtered and drives the TV-MPF so that the passband of the filter is always aligned with the frequencies of the signal to be filtered. By continuously tracking the signal spectral component, the TV-MPF only retains the spectral components of the signal and filters out the noise other than the spectral component of the signal at the current time, so as to improve the in-band SNR of the signal to be filtered. An experiment is performed. A variety of signals with different formats and in-band SNRs are used to test the noise suppression capability of the TV-MPF, and the waveform mean-square error is calculated to quantify the improvement of the signal, demonstrating the excellent adaptability of the proposed TV-MPF to different kinds of signals.

preprint2022arXiv

Tree level Majorana neutrino mass from Type-1 $\times$ Type-2 Seesaw mechanism with Dark Matter

We propose a type of hybrid Seesaw model that combines Type-1 and Type-2 Seesaw mechanism in multiplicative way to generate tree level Majorana neutrino mass and provides a Dark Matter candidate. The model extends the Standard Model by extra gauge symmetry $U(1)_{D}$ and hidden sector consisted of chiral fermions and additional scalar fields. After spontaneous symmetry breaking, light neutrino masses are generated not only by exchange of the new heavy fermions as Type-1 Seesaw, but also by coupling to the naturally small induced vacuum expectation value of new heavy scalar as Type-2 Seesaw. An unbroken residue of $U(1)_{D}$ protects the lightest Dirac fermion required by anomaly cancellation in hidden sector from decaying, therefore giving rise to a Dark Matter candidate. Due to strong enough Seesaw suppression from our hybridization, new physics scale can be as low as TeV in this model and discovering signal from LHC data is possible in near future.

preprint2022arXiv

Unusually high HCO+/CO ratios in and outside supernova remnant W49B

Galactic supernova remnants (SNRs) and their environments provide the nearest laboratories to study SN feedback. We performed molecular observations toward SNR W49B, the most luminous Galactic SNR in the X-ray band, aiming to explore signs of multiple feedback channels of SNRs on nearby molecular clouds (MCs). We found very broad HCO+ lines with widths of dv = 48--75 km/s in the SNR southwest, providing strong evidence that W49B is perturbing MCs at a systemic velocity of $V_{LSR}=61$--65 km/s, and placing W49B at a distance of $7.9\pm 0.6$ kpc. We observed unusually high-intensity ratios of HCO+ J=1-0/CO J=1-0 not only at shocked regions ($1.1\pm 0.4$ and $0.70\pm 0.16$), but also in quiescent clouds over 1 pc away from the SNR's eastern boundary (> 0.2). By comparing with the magnetohydrodynamics shock models, we interpret that the high ratio in the broad-line regions can result from a cosmic-ray (CR) induced chemistry in shocked MCs, where the CR ionization rate is enhanced to around 10--100 times of the Galactic level. The high HCO+/CO ratio outside the SNR is probably caused by the radiation precursor, while the luminous X-ray emission of W49B can explain a few properties in this region. The above results provide observational evidence that SNRs can strongly influence the molecular chemistry in and outside the shock boundary via their shocks, CRs, and radiation. We propose that the HCO+/CO ratio is a potentially useful tool to probe an SNR's multichannel influence on MCs.

preprint2022arXiv

WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma (LUAD) is the most common subtype. Exploiting the potential value of the histopathology images can promote precision medicine in oncology. Tissue segmentation is the basic upstream task of histopathology image analysis. Existing deep learning models have achieved superior segmentation performance but require sufficient pixel-level annotations, which is time-consuming and expensive. To enrich the label resources of LUAD and to alleviate the annotation efforts, we organize this challenge WSSS4LUAD to call for the outstanding weakly-supervised semantic segmentation (WSSS) techniques for histopathology images of LUAD. Participants have to design the algorithm to segment tumor epithelial, tumor-associated stroma and normal tissue with only patch-level labels. This challenge includes 10,091 patch-level annotations (the training set) and over 130 million labeled pixels (the validation and test sets), from 87 WSIs (67 from GDPH, 20 from TCGA). All the labels were generated by a pathologist-in-the-loop pipeline with the help of AI models and checked by the label review board. Among 532 registrations, 28 teams submitted the results in the test phase with over 1,000 submissions. Finally, the first place team achieved mIoU of 0.8413 (tumor: 0.8389, stroma: 0.7931, normal: 0.8919). According to the technical reports of the top-tier teams, CAM is still the most popular approach in WSSS. Cutmix data augmentation has been widely adopted to generate more reliable samples. With the success of this challenge, we believe that WSSS approaches with patch-level annotations can be a complement to the traditional pixel annotations while reducing the annotation efforts. The entire dataset has been released to encourage more researches on computational pathology in LUAD and more novel WSSS techniques.

preprint2021arXiv

Digital-assisted photonic analog wideband multipath self-interference cancellation

A digital-assisted photonic analog wideband radio-frequency multipath self-interference cancellation (SIC) and frequency downconversion method based on a dual-drive Mach-Zehnder modulator and the recursive least square (RLS) algorithm is proposed and demonstrated for in-band full-duplex systems. Besides the reference for the direct-path self-interference (SI) signal, the RLS algorithm is used to construct another reference for the residual SI signal from the direct path and the SI signals from the reflection paths. The proposed method can solve the performance limitation in the previously reported SIC methods of constructing the multipath SI signal using a single reference caused by the limited dynamic range of the digital-to-analog converter when the direct-path SI signal is much stronger than the sub-weak reflection-path SI signals. An experiment is performed. When the carrier frequency of the multipath SI signal is 10 GHz and the direct-path SI signal is much stronger than the sub-weak multipath SI signal, the cancellation depths of about 26.7 and 26.1 dB are realized with SI baud rates of 0.5 and 1 Gbaud. When the direct-path SI signal and sub-weak multipath SI signal own closer power, the corresponding cancellation depths are 24.7 and 20.8 dB, respectively.

preprint2021arXiv

Genuine tripartite entanglement as a probe of quantum phase transitions in a spin-1 Heisenberg chain with single-ion anisotropy

We study the quantum phase transitions of spin-1 Heisenberg chains with an easy-axis anisotropy $Δ$ and a uniaxial single-ion anisotropy $D$ using a multipartite entanglement approach. The genuine tripartite entanglement between the spin blocks, measured by the tripartite qutrit hyperdeterminant, is calculated within the quantum renormalization group method. Using this approach, the phase boundaries between the topological Haldane, large-D and anti-ferromagnetic Néel phases are determined in the half $Δ-D$ plane with $Δ>0$. When the size of the spin blocks increases, the genuine tripartite entanglement between the blocks exhibits a nonzero plateau in the topological Haldane phase, and experiences abrupt drops at both the phase boundaries between the Haldane--large-D and Haldane--Néel phases, which justifies the usage of genuine multipartite entanglement as a probe of topological phases in spin systems.

preprint2021arXiv

Homotopic Gradients of Generative Density Priors for MR Image Reconstruction

Deep learning, particularly the generative model, has demonstrated tremendous potential to significantly speed up image reconstruction with reduced measurements recently. Rather than the existing generative models that often optimize the density priors, in this work, by taking advantage of the denoising score matching, homotopic gradients of generative density priors (HGGDP) are proposed for magnetic resonance imaging (MRI) reconstruction. More precisely, to tackle the low-dimensional manifold and low data density region issues in generative density prior, we estimate the target gradients in higher-dimensional space. We train a more powerful noise conditional score network by forming high-dimensional tensor as the network input at the training phase. More artificial noise is also injected in the embedding space. At the reconstruction stage, a homotopy method is employed to pursue the density prior, such as to boost the reconstruction performance. Experiment results imply the remarkable performance of HGGDP in terms of high reconstruction accuracy; only 10% of the k-space data can still generate images of high quality as effectively as standard MRI reconstruction with the fully sampled data.

preprint2021arXiv

IRAM 30 m CO-line Observation toward PeVatron Candidate G106.3+2.7: Direct Interaction between the Shock and the Molecular Cloud Remains Uncertain

Supernova remnant (SNR) G106.3+2.7 was recently found to be one of the few potential Galactic hadronic PeVatrons. Aiming to test how solid the SNR is associated with the molecular clouds (MCs) that are thought to be responsible for hadronic interaction, we performed a new CO observation with the IRAM 30m telescope toward its "belly" region, which is coincident with the centroid of the $γ$-ray emission. There is a filament structure in the local-standard-of-rest velocity interval $-8$ to $-5$ km/s that nicely follows the northern radio boundary of the SNR. We have seen asymmetric broad profiles of $^{12}$CO lines, with widths of a few km/s along the northern boundary and in the "belly" region of G106.3+2.7, but similar $^{12}$CO line profiles are also found outside the SNR boundary. Further, the low $^{12}$CO J=2-1/J=1-0 line ratios suggest the MCs are cool. Therefore, it is still uncertain whether the MCs are directly disturbed by the SNR shocks, but we do find some clues that the MCs are nearby and thus can still be illuminated by the escaped protons from the SNR. Notably, we find an expanding molecular structure with a velocity of $\sim$3.5 km/s and a velocity gradient of the MCs across the SNR from $\sim -3$ to $-7$ km/s, which could be explained as the effect of the wind blown by the SNR's progenitor star.

preprint2021arXiv

Photonic-enabled radio-frequency self-interference cancellation incorporated in an in-band full-duplex radio-over-fiber system

A photonic approach for radio-frequency (RF) self-interference cancellation (SIC) incorporated in an in-band full-duplex radio-over-fiber system is proposed. A dual-polarization binary phase-shift keying modulator is used for dual-polarization multiplexing at the central office (CO). A local oscillator signal and an intermediate-frequency signal carrying the downlink data are single-sideband modulated on the two polarization directions of the modulator, respectively. The optical signal is then transmitted to the remote unit, where the optical signals in the two polarization directions are split into two parts. One part is detected to generate the up-converted downlink RF signal, and the other part is re-modulated by the uplink RF signal and the self-interference, which is then transmitted back to the CO for the signal down-conversion and SIC via the optical domain signal adjustment and balanced detection. The functions of SIC, frequency up-conversion, down-conversion, and fiber transmission with dispersion immunity are all incorporated in the system. An experiment is performed. Cancellation depths of more than 39 dB for the single-tone signal and more than 20 dB for the 20-MBaud 16 quadrature amplitude modulation signal are achieved in the back-to-back case. The performance of the system does not have a significant decline when a section of 4.1-km optical fiber is incorporated.

preprint2021arXiv

Photonics-assisted microwave pulse detection and frequency measurement based on pulse replication and frequency-to-time mapping

A photonics-assisted microwave pulse detection and frequency measurement scheme is proposed. The unknown microwave pulse is converted to the optical domain and then injected into a fiber loop for pulse replication, which makes it easier to identify the microwave pulse with large pulse repetition interval (PRI), whereas stimulated Brillouin scattering-based frequency-to-time mapping (FTTM) is utilized to measure the carrier frequency of the microwave pulse. A sweep optical carrier is generated and modulated by the unknown microwave pulse and a continuous-wave single-frequency reference, generating two different frequency sweep optical signals, which are combined and used as the probe wave to detect a fixed Brillouin gain spectrum. When the optical signal is detected in a photodetector, FTTM is realized and the frequency of the microwave pulse can be determined. An experiment is performed. For a fiber loop containing a 210-m fiber, pulse replication and FTTM of the pulses with a PRI of 20 μs and pulse width of 1.20, 1.00, 0.85, and 0.65 μs are realized. Under a certain sweep frequency chirp rate of 0.978 THz/s, the measurement errors are below {\pm}12 and {\pm}5 MHz by using one pair of pulses and multiple pairs of pulses, respectively. The influence of the sweep frequency chirp rate and pulse width on the measurement error has also been studied. To a certain extent, the faster the frequency sweep, the greater the frequency measurement error. For a specific sweep frequency chirp rate, the measurement error is almost unaffected by the pulse width to be measured.

preprint2021arXiv

Quantum key distribution over 658 km fiber with distributed vibration sensing

Twin-field quantum key distribution (TF-QKD) promises ultra-long secure key distribution which surpasses the rate distance limit and can reduce the number of the trusted nodes in long-haul quantum network. Tremendous efforts have been made towards implementation of TF-QKD, among which, the secure key with finite size analysis can distribute more than 500 km in the lab and in the field. Here, we demonstrate the sending-or-not-sending TF-QKD experimentally, achieving a secure key distribution with finite size analysis over 658 km ultra-low-loss optical fiber, improve the secure distance record by around 100 km. Meanwhile, in a TF-QKD system, any phase fluctuation due to temperature variation and ambient variation during the channel must be recorded and compensated, and all these phase information can then be utilized to sense the channel vibration perturbations. With our QKD system, we recovered the external vibrational perturbations on the fiber generated by an artificial vibroseis and successfully located the perturbation position with a resolution better than 1 km. Our results not only set a new distance record of QKD, but also demonstrate that the redundant information of TF-QKD can be used for remote sensing of the channel vibration, which can find applications in earthquake detection and landslide monitoring besides secure communication.

preprint2021arXiv

Short-time Fourier transform based on stimulated Brillouin scattering

In this paper, all-optical short-time Fourier transform (STFT) based on stimulated Brillouin scattering (SBS) is proposed and further used for real-time time-frequency analysis of different radio frequency (RF) signals. In the proposed all-optical STFT system, SBS not only provides a band-pass filter for implementing the window function in conjunction with a periodic frequency-sweep optical signal but also obtains the frequency domain information in different time windows through the generated waveform via frequency-to-time mapping (FTTM). A periodic frequency-sweep optical signal is generated and then modulated at a Mach-Zehnder modulator by the electrical signal under test (SUT). During different sweep periods, the fixed Brillouin gain functions as a bandpass filter to select a specific range of the spectrum, which is equivalent to applying a sliding window function to the corresponding section of the temporal signal with the help of the sweep optical signal. At the same time, after the optical signal is selectively amplified by the SBS gain and converted back to the electrical domain, SBS also implements the real-time FTTM, which can be utilized to obtain the frequency domain information corresponding to different time windows through the generated waveforms via the FTTM. The frequency domain information corresponding to different time windows is formed and spliced to analyze the time-frequency relationship of the SUT in real-time. An experiment is performed. STFTs of a variety of RF signals are carried out in a 12-GHz bandwidth limited only by the equipment, and the dynamic frequency resolution is better than 60 MHz.

preprint2021arXiv

Spatially Resolved X-ray Study of Supernova Remnant G306.3$-$0.9 with Unusually High Calcium Abundance

G306.3$-$0.9 is an asymmetric Galactic supernova remnant (SNR), whose progenitor has been thought to be a Type Ia supernova (SN), but its high Ca abundance appears inconsistent with the Type Ia origin. Hoping to uncover the reason for its asymmetry and the origin of this SNR, we performed a spatially resolved X-ray spectroscopic analysis of XMM-Newton and Chandra observation data. We divided the SNR into 13 regions and analyzed the spectra using two-temperature models (0.2 keV + 1 keV). Compared to the southwestern regions, the northeastern regions have higher metal abundances and a lower gas density. This suggests that the asymmetric morphology results from the non-uniform ambient environment. We found that neither Type Ia nor core-collapse SN models can account for the abnormally high abundance ratios of Ar/Si, Ca/Si, or the shape of the abundance curve. A comparison with the Ca-rich transient models shows that G306.3$-$0.9 is likely to be the first identified Galactic "Ca-rich transient" remnant, although the theoretical production of element S is lower. We also note that the conclusion for the SNR's origin relies on the measured abundance ratios and existing nucleosynthesis models. Between two groups of Ca-rich transient explosion models, we prefer the He shell detonation for an accreting WD, rather than the merger of a white dwarf and a neutron star.

preprint2021arXiv

Time-frequency analysis of microwave signals based on stimulated Brillouin scattering

A novel photonic approach to the time-frequency analysis of microwave signals is proposed based on the stimulated Brillouin scattering (SBS)-assisted frequency-to-time mapping (FTTM). Two types of time-frequency analysis links, namely parallel SBS link and time-division SBS link are proposed. The parallel SBS link can be utilized to perform real-time time-frequency analysis of microwave signal, which provides a promising solution for real-time time-frequency analysis, especially when it is combined with the photonic integration technique. A simulation is made to verify its feasibility by analyzing signals in multiple formats. The time-division SBS link has a simpler and reconfigurable structure, which can realize an ultra-high-resolution time-frequency analysis for periodic signals using the time segmentation and accumulation technique. An experiment is performed for the time-division SBS link. The multi-dimensional reconfigurability of the system is experimentally studied. An analysis bandwidth of 3.9 GHz, an analysis frequency up to 20 GHz, and a frequency resolution of 15 MHz are demonstrated, respectively.

preprint2021arXiv

Transverse mode-encoded quantum gate on a silicon photonic chip

As an important degree of freedom (DoF) in integrated photonic circuits, the orthogonal transverse mode provides a promising and flexible way to increasing communication capability, for both classical and quantum information processing. To construct large-scale on-chip multimode multi-DoF quantum systems, a transverse mode-encoded controlled-NOT (CNOT) gate is necessary. Here, through design and integrate transverse mode-dependent directional coupler and attenuators on a silicon photonic chip, we demonstrate the first multimode implementation of a two-qubit quantum gate. With the aid of state preparation and analysis parts, we show the ability of the gate to entangle two separated transverse mode qubits with an average fidelity of $0.89\pm0.02$ and the achievement of 10 standard deviations of violations in the quantum nonlocality verification. In addition, a fidelity of $0.82\pm0.01$ was obtained from quantum process tomography used to completely characterize the CNOT gate. Our work paves the way for universal transverse mode-encoded quantum operations and large-scale multimode multi-DoF quantum systems.

preprint2020arXiv

2-local derivations on Witt algebras

In this paper, we prove that every 2-local derivation on Witt algebras $W_n, W_n^+$ or $W_n^{++} $ is a derivation for all $n=1,2,\cdots,\infty$. As a consequence we obtain that every 2-local derivation on any centerless generalized Virasoro algebra of higher rank is a derivation.

preprint2020arXiv

A deep learning approach for virtual monochromatic spectral CT imaging with a standard single energy CT scanner

Purpose/Objectives: To develop and assess a strategy of using deep learning (DL) to generate virtual monochromatic CT (VMCT) images from a single-energy CT (SECT) scan. Materials/Methods: The proposed data-driven VMCT imaging consists of two steps: (i) using a supervised DL model trained with a large number of 100 kV and 140 kV dual-energy CT (DECT) image pairs to produce the corresponding high-energy CT image from a low-energy image; and (ii) reconstructing VMCT images with energy ranging from 40 to 150 keV. To evaluate the performance of the method, we retrospectively studied 6,767 abdominal DECT images. The VMCT images reconstructed using both DL-derived DECT (DL-DECT) images and the images from DECT scanner were compared quantitatively. Paired-sample t-tests were used for statistical analysis to show the consistency and precision of calculated HU values. Results: Excellent agreement was found between the DL-DECT and the ground truth DECT images (p values ranged from 0.50 to 0.95). Noise reduction up to 68% (from 163 HU to 51 HU) was achieved for DL-based VMCT imaging as compared to that obtained by using the standard DECT. For the DL-based VMCT, the maximum iodine contrast-to-noise ratio (CNR) for each patient (ranging from 15.1 to 16.6) was achieved at 40 keV. In addition to the enormous benefit of VMCT acquisition with merely a SECT image, an improvement of CNR as high as 55% (from 10.7 to 16.6) was attained with the proposed approach. Conclusions: This study demonstrates that high-quality VMCT images can be obtained with only a SECT scan.

preprint2020arXiv

A Gaia early DR3 mock stellar catalog: Galactic prior and selection function

We present a mock stellar catalog, matching in volume, depth and data model the content of the planned Gaia early data release 3 (Gaia EDR3). We have generated our catalog (GeDR3mock) using galaxia, a tool to sample stars from an underlying Milky Way (MW) model or from N-body data. We used an updated Besançon Galactic model together with the latest PARSEC stellar evolutionary tracks, now also including white dwarfs. We added the Magellanic clouds and realistic open clusters with internal rotation. We empirically modelled uncertainties based on Gaia DR2 (GDR2) and scaled them according to the longer baseline in Gaia EDR3. The apparent magnitudes were reddened according to a new selection of 3D extinction maps. To help with the Gaia selection function we provide all-sky magnitude limit maps in G and BP for a few relevant GDR2 subsets together with the routines to produce these maps for user-defined subsets. We supplement the catalog with photometry and extinctions in non-Gaia bands. The catalog is available in the Virtual Observatory and can be queried just like the actual Gaia EDR3 will be. We highlight a few capabilities of the Astronomy Data Query Language (ADQL) with educative catalog queries. We use the data extracted from those queries to compare GeDR3mock to GDR2, which emphasises the importance of adding observational noise to the mock data. Since the underlying truth, e.g. stellar parameters, is know in GeDR3mock, it can be used to construct priors as well as mock data tests for parameter estimation. All code, models and data used to produce GeDR3mock are linked and contained in galaxia_wrap, a python package, representing a fast galactic forward model, able to project MW models and N-body data into realistic Gaia observables.

preprint2020arXiv

A Small-Scale Investigation of Molecular Emission toward the Tip of the Western Lobe of W50/SS433

We perform a molecular (CO and CN) line observation using IRAM 30m telescope toward two small regions near the western edge of supernova remnant (SNR) W50/SS433. CO observation reveals spatial correspondence of two molecular clumps at the local-standard-of-rest (LSR) velocity around +53 km s$^{-1}$ with multiwavelength local features of W50/SS433 system. One of the two clumps appears to be embedded in a void of diffuse radio and X-ray emission. Toward the two clumps, asymmetric broad line profiles of the $^{12}$CO lines are obtained, which provide kinematic evidence of the association between the clumps and the jet-related gas. The $^{12}$CO $J=2-1$/$J=1-0$ line ratios ($> 0.9$) and the kinetic temperatures ($\sim 30$ K) of the clumps are distinctively higher than all those of the clumps at other LSR velocities along the same line of sight, which may be physical signatures of the association. We show that the clump coincident with the void can survive the thermal heating if it is surrounded by hot gas, with an evaporation timescale much larger than the age of SNR W50. We also show that the thermal equilibrium in the high temperature clumps can be maintained by the heating of the penetrating environmental CRs. CN ($J=3/1-1/2$) line emission is detected in the two clumps, and the CN abundances derived are much higher than that in the interstellar molecular clouds (MCs) and that in the SNR-interacting MCs.

preprint2020arXiv

A Study of Efficient Light Field Subsampling and Reconstruction Strategies

Limited angular resolution is one of the main obstacles for practical applications of light fields. Although numerous approaches have been proposed to enhance angular resolution, view selection strategies have not been well explored in this area. In this paper, we study subsampling and reconstruction strategies for light fields. First, different subsampling strategies are studied with a fixed sampling ratio, such as row-wise sampling, column-wise sampling, or their combinations. Second, several strategies are explored to reconstruct intermediate views from four regularly sampled input views. The influence of the angular density of the input is also evaluated. We evaluate these strategies on both real-world and synthetic datasets, and optimal selection strategies are devised from our results. These can be applied in future light field research such as compression, angular super-resolution, and design of camera systems.

preprint2020arXiv

Active Learning over DNN: Automated Engineering Design Optimization for Fluid Dynamics Based on Self-Simulated Dataset

Optimizing fluid-dynamic performance is an important engineering task. Traditionally, experts design shapes based on empirical estimations and verify them through expensive experiments. This costly process, both in terms of time and space, may only explore a limited number of shapes and lead to sub-optimal designs. In this research, a test-proven deep learning architecture is applied to predict the performance under various restrictions and search for better shapes by optimizing the learned prediction function. The major challenge is the vast amount of data points Deep Neural Network (DNN) demands, which is improvident to simulate. To remedy this drawback, a Frequentist active learning is used to explore regions of the output space that DNN predicts promising. This operation reduces the number of data samples demanded from ~8000 to 625. The final stage, a user interface, made the model capable of optimizing with given user input of minimum area and viscosity. Flood fill is used to define a boundary area function so that the optimal shape does not bypass the minimum area. Stochastic Gradient Langevin Dynamics (SGLD) is employed to make sure the ultimate shape is optimized while circumventing the required area. Jointly, shapes with extremely low drags are found explored by a practical user interface with no human domain knowledge and modest computation overhead.

preprint2020arXiv

An XMM-Newton X-ray View of Supernova Remnant W49B: Revisiting its Recombining Plasmas and Progenitor Type

We present a comprehensive X-ray spectroscopy and imaging study of supernova remnant W49B using archival XMM-Newton observations. The overionization state of the shocked ejecta in W49B is clearly indicated by the radiative recombination continua of Si XIV, S XV, and Fe XXV, combined with the Ly$α$ lines of Ca and Fe. The line flux images of W49B indicate high emission measures of the central bar-like region for almost all the emission lines, while the equivalent width maps reveal a stratified structure for the metal abundance distributions. The global spectrum of W49B is well reproduced by a model containing one collisional ionization equilibrium (CIE) plasma component and two recombining plasma (RP) components. The CIE plasma represents the shocked interstellar medium, which dominates the X-ray emitting volume in W49B with a mass $\sim450M_\odot$. The two RP components with a total mass $\sim4.6M_\odot$ are both dominated by the ejecta material, but characterized by different electron temperatures ($\sim1.60$ keV and $\sim0.64$ keV). The recombination ages of the RP components are estimated as $\sim6000$ yr and $\sim3400$ yr, respectively. We then reveal the possibility of a thermal conduction origin for the high-temperature RP in W49B by calculating the conduction timescale. The metal abundance ratios of the ejecta in W49B are roughly consistent with a core-collapse explosion model with a $\lesssim15M_\odot$ progenitor, except for a rather high Mn/Fe. A Type Ia origin can explain the Mn abundance, while it predicts much higher ejecta masses than observed values for all the metal species considered in our analysis.

preprint2020arXiv

Carbon star formation as seen through the non-monotonic initial-final mass relation

The initial-final mass relation (IFMR) links the birth mass of a star to the mass of the compact remnant left at its death. While the relevance of the IFMR across astrophysics is universally acknowledged, not all of its fine details have yet been resolved. A new analysis of a few carbon-oxygen white dwarfs in old open clusters of the Milky Way led us to identify a kink in the IFMR, located over a range of initial masses, $1.65 \lesssim M_{\rm i}/M_{\odot} \lesssim 2.10$. The kink's peak in WD mass of $\approx 0.70-0.75 \, M_{\odot}$ is produced by stars with $M_{\rm i} \simeq 1.8 - 1.9 \, M_{\odot}$, corresponding to ages of about $1.8 - 1.7 $ Gyr. Interestingly, this peak coincides with the initial mass limit between low-mass stars that develop a degenerate helium core after central hydrogen exhaustion, and intermediate-mass stars that avoid electron degeneracy. We interpret the IFMR kink as the signature of carbon star formation in the Milky Way. This finding is critical to constraining the evolution and chemical enrichment of low-mass stars, and their impact on the spectrophotometric properties of galaxies.

preprint2020arXiv

Chemical abundances in Sgr A East: evidence for a Type Iax supernova remnant

Recent observations have shown a remarkable diversity of observational behaviors and explosion mechanisms in thermonuclear supernovae (SNe). An emerging class of peculiar thermonuclear SNe, called Type Iax, show photometric and spectroscopic behaviors distinct from normal Type Ia. Their origin remains highly controversial, but pure turbulent deflagration of white dwarfs (WDs) has been regarded as the leading formation theory. The large population of Type Iax indicates the existence of unidentified Galactic Type Iax supernova remnants (SNRs). We report evidence that SNR Sgr A East in the Galactic center resulted from a pure turbulent deflagration of a Chandrasekhar-mass carbon-oxygen WD, an explosion mechanism used for Type Iax SNe. Our X-ray spectroscopic study of Sgr A East using 3 Ms of Chandra data shows a low ratio of intermediate-mass elements to Fe and large Mn/Fe and Ni/Fe ratios. This abundance pattern does not accord with the core-collapse or normal Type Ia models. Sgr A East is thus the first Galactic SNR for which a likely Type Iax origin has been proposed and the nearest target for studying this peculiar class. We compared Sgr A East with the Fe-rich SNRs 3C 397 and W49B, which also have high Mn and Cr abundances and were claimed to result from deflagration-to-detonation explosions of Chandrasekhar-mass WDs (although with disputes). Our study shows that they have distinct abundance patterns. The X-ray spectroscopic studies of thermonuclear SNRs provide observational evidence for the theories that there are diverse explosion channels and various metal outputs for Chandrasekhar-mass WDs.

preprint2020arXiv

Constraining the thermally pulsing asymptotic giant branch phase with resolved stellar populations in the Large Magellanic Cloud

Reliable models of the thermally pulsing asymptotic giant branch (TP-AGB) phase are of critical importance across astrophysics, including our interpretation of the spectral energy distribution of galaxies, cosmic dust production, and enrichment of the interstellar medium. With the aim of improving sets of stellar isochrones that include a detailed description of the TP-AGB phase, we extend our recent calibration of the AGB population in the Small Magellanic Cloud (SMC) to the more metal rich Large Magellanic Cloud (LMC). We model the LMC stellar populations with the TRILEGAL code, using the spatially-resolved star formation history derived from the VISTA survey. We characterize the efficiency of the third dredge-up by matching the star counts and the $K_{\rm s}$-band luminosity functions of the AGB stars identified in the LMC. In line with previous findings, we confirm that, compared to the SMC, the third dredge-up in AGB stars of the LMC is somewhat less efficient, as a consequence of the higher metallicity. The predicted range of initial mass of C-rich stars is between $M_{\rm i} \approx 1.7 - 3~\mathrm{M}_{\odot}$ at $Z_{\rm i} = 0.008$. We show how the inclusion of new opacity data in the carbon star spectra will improve the performance of our models. We discuss the predicted lifetimes, integrated luminosities and mass-loss rate distributions of the calibrated models. The results of our calibration are included in updated stellar isochrones publicly available.

preprint2020arXiv

Data Techniques For Online End-to-end Speech Recognition

Practitioners often need to build ASR systems for new use cases in a short amount of time, given limited in-domain data. While recently developed end-to-end methods largely simplify the modeling pipelines, they still suffer from the data sparsity issue. In this work, we explore a few simple-to-implement techniques for building online ASR systems in an end-to-end fashion, with a small amount of transcribed data in the target domain. These techniques include data augmentation in the target domain, domain adaptation using models previously trained on a large source domain, and knowledge distillation on non-transcribed target domain data, using an adapted bi-directional model as the teacher; they are applicable in real scenarios with different types of resources. Our experiments demonstrate that each technique is independently useful in the improvement of the online ASR performance in the target domain.

preprint2020arXiv

Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images

Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region constraints from segmentation) to bring mutual improvement in complex scene and few-shot situation. However, further adoption of the joint models are hindered: 1) the diversity of augmentation data is reduced limiting the further enhancement of segmentation, 2) misaligned regions in weakly supervised data disturb the training process, 3) lack of label-based region constraints in few-shot situation limits the registration performance. We propose a novel Deep Complementary Joint Model (DeepRS) for complex scene registration and few-shot segmentation. We embed a perturbation factor in the registration to increase the activity of deformation thus maintaining the augmentation data diversity. We take a pixel-wise discriminator to extract alignment confidence maps which highlight aligned regions in weakly supervised data so the misaligned regions' disturbance will be suppressed via weighting. The outputs from segmentation model are utilized to implement deep-based region constraints thus relieving the label requirements and bringing fine registration. Extensive experiments on the CT dataset of MM-WHS 2017 Challenge show great advantages of our DeepRS that outperforms the existing state-of-the-art models.

preprint2020arXiv

DIRECT-Net: a unified mutual-domain material decomposition network for quantitative dual-energy CT imaging

By acquiring two sets of tomographic measurements at distinct X-ray spectra, the dual-energy CT (DECT) enables quantitative material-specific imaging. However, the conventionally decomposed material basis images may encounter severe image noise amplification and artifacts, resulting in degraded image quality and decreased quantitative accuracy. Iterative DECT image reconstruction algorithms incorporating either the sinogram or the CT image prior information have shown potential advantages in noise and artifact suppression, but with the expense of large computational resource, prolonged reconstruction time, and tedious manual selections of algorithm parameters. To partially overcome these limitations, we develop a domain-transformation enabled end-to-end deep convolutional neural network (DIRECT-Net) to perform high quality DECT material decomposition. Specifically, the proposed DIRECT-Net has immediate accesses to mutual-domain data, and utilizes stacked convolution neural network (CNN) layers for noise reduction and material decomposition. The training data are numerically simulated based on the underlying physics of DECT imaging.The XCAT digital phantom, iodine solutions phantom, and biological specimen are used to validate the performance of DIRECT-Net. The qualitative and quantitative results demonstrate that this newly developed DIRECT-Net is promising in suppressing noise, improving image accuracy, and reducing computation time for future DECT imaging.

preprint2020arXiv

Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network

Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are usually more expensive than standard single-energy CT (SECT) scanners and thus are less accessible to undeveloped regions. In this paper, we show that the energy-domain correlation and anatomical consistency between standard DECT images can be harnessed by a deep learning model to provide high-performance DECT imaging from fully-sampled low-energy data together with single-view high-energy data, which can be obtained by using a scout-view high-energy image. We demonstrate the feasibility of the approach with contrast-enhanced DECT scans from 5,753 slices of images of twenty-two patients and show its superior performance on DECT applications. The deep learning-based approach could be useful to further significantly reduce the radiation dose of current premium DECT scanners and has the potential to simplify the hardware of DECT imaging systems and to enable DECT imaging using standard SECT scanners.

preprint2020arXiv

EB-dynaRE: Real-Time Adjustor for Brownian Movement with Examples of Predicting Stock Trends Based on a Novel Event-Based Supervised Learning Algorithm

Stock prices are influenced over time by underlying macroeconomic factors. Jumping out of the box of conventional assumptions about the unpredictability of the market noise, we modeled the changes of stock prices over time through the Markov Decision Process, a discrete stochastic control process that aids decision making in a situation that is partly random. We then did a "Region of Interest" (RoI) Pooling of the stock time-series graphs in order to predict future prices with existing ones. Generative Adversarial Network (GAN) is then used based on a competing pair of supervised learning algorithms, to regenerate future stock price projections on a real-time basis. The supervised learning algorithm used in this research, moreover, is original to this study and will have wider uses. With the ensemble of these algorithms, we are able to identify, to what extent, each specific macroeconomic factor influences the change of the Brownian/random market movement. In addition, our model will have a wider influence on the predictions of other Brownian movements.

preprint2020arXiv

Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields

Depth map estimation is a crucial task in computer vision, and new approaches have recently emerged taking advantage of light fields, as this new imaging modality captures much more information about the angular direction of light rays compared to common approaches based on stereoscopic images or multi-view. In this paper, we propose a novel depth estimation method from light fields based on existing optical flow estimation methods. The optical flow estimator is applied on a sequence of images taken along an angular dimension of the light field, which produces several disparity map estimates. Considering both accuracy and efficiency, we choose the feature flow method as our optical flow estimator. Thanks to its spatio-temporal edge-aware filtering properties, the different disparity map estimates that we obtain are very consistent, which allows a fast and simple aggregation step to create a single disparity map, which can then converted into a depth map. Since the disparity map estimates are consistent, we can also create a depth map from each disparity estimate, and then aggregate the different depth maps in the 3D space to create a single dense depth map.

preprint2020arXiv

Gap Probabilities in the Laguerre Unitary Ensemble and Discrete Painlevé Equations

In this paper we study a certain recurrence relation, that can be used to generate ladder operators for the Laguerre Unitary ensemble, from the point of view of Sakai's geometric theory of Painlevé equations. On one hand, this gives us one more detailed example of the appearance of discrete Painlevé equations in the theory of orthogonal polynomials. On the other hand, it serves as a good illustration of the effectiveness of a recently proposed procedure on how to reduce such recurrences to some canonical discrete Painlevé equations.

preprint2020arXiv

Gaussian unitary ensemble with two jump discontinuities, PDEs and the coupled Painlevé II and IV systems

We consider the Hankel determinant generated by the Gaussian weight with two jump discontinuities. Utilizing the results of [C. Min and Y. Chen, Math. Meth. Appl. Sci. {\bf 42} (2019), 301--321] where a second order PDE was deduced for the log derivative of the Hankel determinant by using the ladder operators adapted to orthogonal polynomials, we derive the coupled Painlevé IV system which was established in [X. Wu and S. Xu, arXiv: 2002.11240v2] by a study of the Riemann-Hilbert problem for orthogonal polynomials. Under double scaling, we show that, as $n\rightarrow\infty$, the log derivative of the Hankel determinant in the scaled variables tends to the Hamiltonian of a coupled Painlevé II system and it satisfies a second order PDE. In addition, we obtain the asymptotics for the recurrence coefficients of orthogonal polynomials, which are connected with the solutions of the coupled Painlevé II system.

preprint2020arXiv

General stationary solutions of the nonlocal nonlinear Schrödinger equation and their relevance to the PT-symmetric system

With the stationary solution assumption, we establish the connection between the nonlocal nonlinear Schrödinger (NNLS) equation and an elliptic equation. Then, we obtain the general stationary solutions and discuss the relevance of their smoothness and boundedness to some integral constants. Those solutions, which cover the known results in the literature, include the unbounded Jacobi elliptic-function and hyperbolic-function solutions, the bounded sn-, cn- and dn-function solutions, as well as the hyperbolic soliton solutions. By the imaginary translation transformation of the NNLS equation, we also derive the complex-amplitude stationary solutions, in which all the bounded cases obey either the \PT- or anti-\PT-symmetric relation. In particular, the complex tanh-function solution can exhibit no spatial localization in addition to the dark and anti-dark soliton profiles, which is sharp contrast with the common dark soliton. Considering the physical relevance to \PT-symmetric system, we show that the complex-amplitude stationary solutions can yield a wide class of complex and time-independent \PT-symmetric potentials, and the symmetry breaking does not occur in the \PT-symmetric linear system with the associated potentials.

preprint2020arXiv

Hot-Carrier Separation in Heterostructure Nanowires observed by Electron-Beam Induced Current

The separation of hot carriers in semiconductors is of interest for applications such as thermovoltaic photodetection and third-generation photovoltaics. Semiconductor nanowires offer several potential advantages for effective hot-carrier separation such as: a high degree of control and flexibility in heterostructure-based band engineering, increased hot-carrier temperatures compared to bulk, and a geometry well suited for local control of light absorption. Indeed, InAs nanowires with a short InP energy barrier have been observed to produce electric power under global illumination, with an open-circuit voltage exceeding the Shockley-Queisser limit. To understand this behaviour in more detail, it is necessary to maintain control over the precise location of electron-hole pair-generation in the nanowire. In this work we perform electron-beam induced current measurements with high spatial resolution, and demonstrate the role of the InP barrier in extracting energetic electrons. We interprete the results in terms of hot-carrier separation, and extract estimates of the hot carrier mean free path.

preprint2020arXiv

Interpreting LSTM Prediction on Solar Flare Eruption with Time-series Clustering

We conduct a post hoc analysis of solar flare predictions made by a Long Short Term Memory (LSTM) model employing data in the form of Space-weather HMI Active Region Patches (SHARP) parameters calculated from data in proximity to the magnetic polarity inversion line where the flares originate. We train the the LSTM model for binary classification to provide a prediction score for the probability of M/X class flares to occur in next hour. We then develop a dimension-reduction technique to reduce the dimensions of SHARP parameter (LSTM inputs) and demonstrate the different patterns of SHARP parameters corresponding to the transition from low to high prediction score. Our work shows that a subset of SHARP parameters contain the key signals that strong solar flare eruptions are imminent. The dynamics of these parameters have a highly uniform trajectory for many events whose LSTM prediction scores for M/X class flares transition from very low to very high. The results demonstrate the existence of a few threshold values of SHARP parameters that when surpassed indicate a high probability of the eruption of a strong flare. Our method has distilled the knowledge of solar flare eruption learnt by deep learning model and provides a more interpretable approximation, which provides physical insight to processes driving solar flares.

preprint2020arXiv

Is PSR J0855$-$4644 responsible for the 1.4 TeV electron spectral bump hinted by DAMPE?

DAMPE observation on the cosmic ray electron spectrum hints a narrow excess at $\sim$ 1.4 TeV. Although the excess can be ascribed to dark matter particles, pulsars and pulsar wind nebulae are believed to be a more natural astrophysical origin: electrons injected from nearby pulsars at their early ages can form a bump-like feature in the spectrum due to radiative energy losses. In this paper, with a survey of nearby pulsars, we find 4 pulsars that may have notable contributions to $\sim$ 1.4 TeV cosmic ray electrons. Among them, PSR J0855$-$4644 has a spin down luminosity more than 50 times higher than others and presumably dominates the electron fluxes from them. X-ray observations on the inner compact part (which may represent a tunnel for the transport of electrons from the pulsar) of PWN G267.0$-$01.0 are then used to constrain the spectral index of high energy electrons injected by the pulsar. We show that high-energy electrons released by PSR J0855$-$4644 could indeed reproduce the 1.4 TeV spectral feature hinted by the DAMPE with reasonable parameters.

preprint2020arXiv

Learning Generalized Spoof Cues for Face Anti-spoofing

Many existing face anti-spoofing (FAS) methods focus on modeling the decision boundaries for some predefined spoof types. However, the diversity of the spoof samples including the unknown ones hinders the effective decision boundary modeling and leads to weak generalization capability. In this paper, we reformulate FAS in an anomaly detection perspective and propose a residual-learning framework to learn the discriminative live-spoof differences which are defined as the spoof cues. The proposed framework consists of a spoof cue generator and an auxiliary classifier. The generator minimizes the spoof cues of live samples while imposes no explicit constraint on those of spoof samples to generalize well to unseen attacks. In this way, anomaly detection is implicitly used to guide spoof cue generation, leading to discriminative feature learning. The auxiliary classifier serves as a spoof cue amplifier and makes the spoof cues more discriminative. We conduct extensive experiments and the experimental results show the proposed method consistently outperforms the state-of-the-art methods. The code will be publicly available at https://github.com/vis-var/lgsc-for-fas.

preprint2020arXiv

Local and $2$-local automorphisms of simple generalized Witt algebras

In this paper, we prove that every invertible $2$-local or local automorphism of a simple generalized Witt algebra over any field of characteristic $0$ is an automorphism. In particular, every $2$-local or local automorphism of Witt algebras $W_n$ is an automorphism for all $n\in \mathbb{N}$. But some simple generalized Witt algebras indeed have $2$-local (and local) automorphisms that are not automorphisms.

preprint2020arXiv

MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction

Low-dose computed tomography (LDCT) scans, which can effectively alleviate the radiation problem, will degrade the imaging quality. In this paper, we propose a novel LDCT reconstruction network that unrolls the iterative scheme and performs in both image and manifold spaces. Because patch manifolds of medical images have low-dimensional structures, we can build graphs from the manifolds. Then, we simultaneously leverage the spatial convolution to extract the local pixel-level features from the images and incorporate the graph convolution to analyze the nonlocal topological features in manifold space. The experiments show that our proposed method outperforms both the quantitative and qualitative aspects of state-of-the-art methods. In addition, aided by a projection loss component, our proposed method also demonstrates superior performance for semi-supervised learning. The network can remove most noise while maintaining the details of only 10% (40 slices) of the training data labeled.

preprint2020arXiv

Marginal loss and exclusion loss for partially supervised multi-organ segmentation

Annotating multiple organs in medical images is both costly and time-consuming; therefore, existing multi-organ datasets with labels are often low in sample size and mostly partially labeled, that is, a dataset has a few organs labeled but not all organs. In this paper, we investigate how to learn a single multi-organ segmentation network from a union of such datasets. To this end, we propose two types of novel loss function, particularly designed for this scenario: (i) marginal loss and (ii) exclusion loss. Because the background label for a partially labeled image is, in fact, a `merged' label of all unlabelled organs and `true' background (in the sense of full labels), the probability of this `merged' background label is a marginal probability, summing the relevant probabilities before merging. This marginal probability can be plugged into any existing loss function (such as cross entropy loss, Dice loss, etc.) to form a marginal loss. Leveraging the fact that the organs are non-overlapping, we propose the exclusion loss to gauge the dissimilarity between labeled organs and the estimated segmentation of unlabelled organs. Experiments on a union of five benchmark datasets in multi-organ segmentation of liver, spleen, left and right kidneys, and pancreas demonstrate that using our newly proposed loss functions brings a conspicuous performance improvement for state-of-the-art methods without introducing any extra computation.

preprint2020arXiv

Modeling the broadest spectral band of the Crab nebula and constraining the ions acceleration efficiency

Although it is widely accepted that the electromagnetic spectrum from radio to very-high-energy $γ$-rays of pulsar wind nebulae (PWNe) originates from leptons, there is still an open question that protons (or more generally, ions) may exist in pulsar wind and are further accelerated in PWN. The broadband spectrum of the prototype PWN Crab, extended recently by the detection of the Tibet AS$γ$ and HAWC experiments above 100 TeV, may be helpful in constraining the acceleration efficiency of ions. Here, we model the broadest energy spectrum of Crab and find that the broadband spectrum can be explained by the one-zone leptonic model in which the electrons/positrons produce the emission from radio to soft $γ$-rays via the synchrotron process, and simultaneously generate the GeV-TeV $γ$-rays through inverse Compton scattering including the synchrotron self-Compton process. In the framework of this leptonic model, the fraction of energy converted into the energetic protons is constrained to be below $0.5\ (n_{\rm t}/10\ {\rm cm}^{-3})^{-1}$ per cent, where $n_{\rm t}$ is the target gas density in the Crab. However, this fraction can be up to $7\ (n_{\rm t}/10\ {\rm cm}^{-3})^{-1}$ per cent if only the $γ$-rays are used.

preprint2020arXiv

Molecular Clouds Surrounding Supernova Remnant G43.9+1.6: Associated and Non-associated

Many supernova remnants (SNRs) are considered to evolve in molecular environments, but the associations between SNRs and molecular clouds (MCs) are often unclear. Being aware of such ambiguous case, we report our study on the molecular environment towards the SNR G43.9+1.6 by CO line observations. We investigated the correlations between the SNR and MCs at different velocities, and found two velocity components, i.e. $\sim$5 km s$^{-1}$ and $\sim$50 km s$^{-1}$ velocity components, showing spatial correlations with the remnant. However, no dynamical evidence of disturbance was found for the $\sim$5 km s$^{-1}$ velocity component. At the distance of the $\sim$5 km s$^{-1}$ velocity component, either near or far distance, the derived physical parameters are unreasonable too. We conclude that the SNR is not associated with the $\sim$5 km s$^{-1}$ velocity component, and their spatial correlation is just a chance correlation. For the $\sim$50 km s$^{-1}$ velocity component, dynamical evidence of disturbances, as well as the spatial correlation, indicate that it is associated with the SNR. We found that all the CO spectra extracted from the molecular clumps distributed along the border of the remnant are with broadened components presented, which can be fitted by Gaussian functions. By further analysis, we suggest that the SNR is at a near kinematic distance of about 3.1 kpc.

preprint2020arXiv

Noise-Sampling Cross Entropy Loss: Improving Disparity Regression Via Cost Volume Aware Regularizer

Recent end-to-end deep neural networks for disparity regression have achieved the state-of-the-art performance. However, many well-acknowledged specific properties of disparity estimation are omitted in these deep learning algorithms. Especially, matching cost volume, one of the most important procedure, is treated as a normal intermediate feature for the following softargmin regression, lacking explicit constraints compared with those traditional algorithms. In this paper, inspired by previous canonical definition of cost volume, we propose the noise-sampling cross entropy loss function to regularize the cost volume produced by deep neural networks to be unimodal and coherent. Extensive experiments validate that the proposed noise-sampling cross entropy loss can not only help neural networks learn more informative cost volume, but also lead to better stereo matching performance compared with several representative algorithms.

preprint2020arXiv

Non-adiabatic transitions in parabolic and super-parabolic $\mathcal{PT}$-symmetric non-Hermitian systems

Exceptional points, the spectral degeneracy points in the complex parameter space, are fundamental to non-Hermitian quantum systems. The dynamics of non-Hermitian systems in the presence of exceptional points differ significantly from those of Hermitian ones. Here we investigate non-adiabatic transitions in non-Hermitian $\mathcal{P}\mathcal{T}$-symmetric systems, in which the exceptional points are driven through at finite speed which are quadratic or cubic functions of time. We identity different transmission dynamics separated by exceptional points, and derive analytical approximate formulas for the non-adiabatic transmission probabilities. We discuss possible experimental realizations with a $\mathcal{P}\mathcal{T}$-symmetric non-Hermitian one-dimensional tight-binding optical waveguide lattice.

preprint2020arXiv

PHAT XX. AGB stars and other cool giants in M31 star clusters

The presence of AGB stars in clusters provides key constraints for stellar models, as has been demonstrated with historical data from the Magellanic Clouds. In this work, we look for candidate AGB stars in M31 star clusters from the Panchromatic Hubble Andromeda Treasury (PHAT) survey. Our photometric criteria selects stars brighter than the tip of the red giant branch, which includes the bulk of the thermally-pulsing AGB stars as well as early-AGB stars and other luminous cool giants expected in young stellar populations (e.g. massive red supergiants, and intermediate-mass red helium-burning stars). The AGB stars can be differentiated, a posteriori, using the ages already estimated for our cluster sample. 937 candidates are found within the cluster aperture radii, half (450) of which are very likely cluster members. Cross-matching with additional databases reveals two carbon stars and ten secure variables among them. The field-corrected age distribution reveals the presence of young supergiants peaking at ages smaller than 100 Myr, followed by a long tail of AGB stars extending up to the oldest possible ages. This long tail reveals the general decrease in the numbers of AGB stars from initial values of 50e-6/Msun at 100 Myr down to 5e-6/Msun at 10 Gyr. Theoretical models of near-solar metallicity reproduce this general trend, although with localized discrepancies over some age intervals, whose origin is not yet identified. The entire catalogue is released together with finding charts to facilitate follow-up studies.

preprint2020arXiv

Predicting solar flares with machine learning: investigating solar cycle dependence

A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 hours is class $Γ$. We considered $Γ$ are $\ge M$, $\ge C$ and any flare class. The essence of using LSTM, which is a recurrent neural network, is its capability to capture temporal information of the data samples. The input features are time sequences of 20 magnetic parameters from SHARPs - Space-weather HMI Active Region Patches. We analyzed active regions from June 2010 to Dec 2018, using the Geostationary Operational Environmental Satellite (GOES) X-ray flare catalogs and label the data samples with identified ARs in the GOES X-ray flare catalogs. Our results (i) shows consistent skill scores with recently published results using LSTMs and better than the previous work using single time input (eg. DeFN) (ii) The skill scores from the model show essential differences when different years of data was chosen for training and testing.

preprint2020arXiv

Progressively Unfreezing Perceptual GAN

Generative adversarial networks (GANs) are widely used in image generation tasks, yet the generated images are usually lack of texture details. In this paper, we propose a general framework, called Progressively Unfreezing Perceptual GAN (PUPGAN), which can generate images with fine texture details. Particularly, we propose an adaptive perceptual discriminator with a pre-trained perceptual feature extractor, which can efficiently measure the discrepancy between multi-level features of the generated and real images. In addition, we propose a progressively unfreezing scheme for the adaptive perceptual discriminator, which ensures a smooth transfer process from a large scale classification task to a specified image generation task. The qualitative and quantitative experiments with comparison to the classical baselines on three image generation tasks, i.e. single image super-resolution, paired image-to-image translation and unpaired image-to-image translation demonstrate the superiority of PUPGAN over the compared approaches.

preprint2020arXiv

Quantifying Observed Prior Impact

We distinguish two questions (i) how much information does the prior contain? and (ii) what is the effect of the prior? Several measures have been proposed for quantifying effective prior sample size, for example Clarke [1996] and Morita et al. [2008]. However, these measures typically ignore the likelihood for the inference currently at hand, and therefore address (i) rather than (ii). Since in practice (ii) is of great concern, Reimherr et al. [2014] introduced a new class of effective prior sample size measures based on prior-likelihood discordance. We take this idea further towards its natural Bayesian conclusion by proposing measures of effective prior sample size that not only incorporate the general mathematical form of the likelihood but also the specific data at hand. Thus, our measures do not average across datasets from the working model, but condition on the current observed data. Consequently, our measures can be highly variable, but we demonstrate that this is because the impact of a prior can be highly variable. Our measures are Bayes estimates of meaningful quantities and well communicate the extent to which inference is determined by the prior, or framed differently, the amount of effort saved due to having prior information. We illustrate our ideas through a number of examples including a Gaussian conjugate model (continuous observations), a Beta-Binomial model (discrete observations), and a linear regression model (two unknown parameters). Future work on further developments of the methodology and an application to astronomy are discussed at the end.

preprint2020arXiv

Remote sensing image fusion based on Bayesian GAN

Remote sensing image fusion technology (pan-sharpening) is an important means to improve the information capacity of remote sensing images. Inspired by the efficient arameter space posteriori sampling of Bayesian neural networks, in this paper we propose a Bayesian Generative Adversarial Network based on Preconditioned Stochastic Gradient Langevin Dynamics (PGSLD-BGAN) to improve pan-sharpening tasks. Unlike many traditional generative models that consider only one optimal solution (might be locally optimal), the proposed PGSLD-BGAN performs Bayesian inference on the network parameters, and explore the generator posteriori distribution, which assists selecting the appropriate generator parameters. First, we build a two-stream generator network with PAN and MS images as input, which consists of three parts: feature extraction, feature fusion and image reconstruction. Then, we leverage Markov discriminator to enhance the ability of generator to reconstruct the fusion image, so that the result image can retain more details. Finally, introducing Preconditioned Stochastic Gradient Langevin Dynamics policy, we perform Bayesian inference on the generator network. Experiments on QuickBird and WorldView datasets show that the model proposed in this paper can effectively fuse PAN and MS images, and be competitive with even superior to state of the arts in terms of subjective and objective metrics.

preprint2020arXiv

Self-Organizing Map assisted Deep Autoencoding Gaussian Mixture Model for Intrusion Detection

In the information age, a secure and stable network environment is essential and hence intrusion detection is critical for any networks. In this paper, we propose a self-organizing map assisted deep autoencoding Gaussian mixture model (SOMDAGMM) supplemented with well-preserved input space topology for more accurate network intrusion detection. The deep autoencoding Gaussian mixture model comprises a compression network and an estimation network which is able to perform unsupervised joint training. However, the code generated by the autoencoder is inept at preserving the topology of the input space, which is rooted in the bottleneck of the adopted deep structure. A self-organizing map has been introduced to construct SOMDAGMM for addressing this issue. The superiority of the proposed SOM-DAGMM is empirically demonstrated with extensive experiments conducted upon two datasets. Experimental results show that SOM-DAGMM outperforms state-of-the-art DAGMM on all tests, and achieves up to 15.58% improvement in F1 score and with better stability.

preprint2020arXiv

Self-supervised Light Field View Synthesis Using Cycle Consistency

High angular resolution is advantageous for practical applications of light fields. In order to enhance the angular resolution of light fields, view synthesis methods can be utilized to generate dense intermediate views from sparse light field input. Most successful view synthesis methods are learning-based approaches which require a large amount of training data paired with ground truth. However, collecting such large datasets for light fields is challenging compared to natural images or videos. To tackle this problem, we propose a self-supervised light field view synthesis framework with cycle consistency. The proposed method aims to transfer prior knowledge learned from high quality natural video datasets to the light field view synthesis task, which reduces the need for labeled light field data. A cycle consistency constraint is used to build bidirectional mapping enforcing the generated views to be consistent with the input views. Derived from this key concept, two loss functions, cycle loss and reconstruction loss, are used to fine-tune the pre-trained model of a state-of-the-art video interpolation method. The proposed method is evaluated on various datasets to validate its robustness, and results show it not only achieves competitive performance compared to supervised fine-tuning, but also outperforms state-of-the-art light field view synthesis methods, especially when generating multiple intermediate views. Besides, our generic light field view synthesis framework can be adopted to any pre-trained model for advanced video interpolation.

preprint2020arXiv

Semi-supervised ASR by End-to-end Self-training

While deep learning based end-to-end automatic speech recognition (ASR) systems have greatly simplified modeling pipelines, they suffer from the data sparsity issue. In this work, we propose a self-training method with an end-to-end system for semi-supervised ASR. Starting from a Connectionist Temporal Classification (CTC) system trained on the supervised data, we iteratively generate pseudo-labels on a mini-batch of unsupervised utterances with the current model, and use the pseudo-labels to augment the supervised data for immediate model update. Our method retains the simplicity of end-to-end ASR systems, and can be seen as performing alternating optimization over a well-defined learning objective. We also perform empirical investigations of our method, regarding the effect of data augmentation, decoding beamsize for pseudo-label generation, and freshness of pseudo-labels. On a commonly used semi-supervised ASR setting with the WSJ corpus, our method gives 14.4% relative WER improvement over a carefully-trained base system with data augmentation, reducing the performance gap between the base system and the oracle system by 50%.

preprint2020arXiv

SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization

Nowadays, as data becomes increasingly complex and distributed, data analyses often involve several related datasets that are stored on different servers and probably owned by different stakeholders. While there is an emerging need to provide these stakeholders with a full picture of their data under a global context, conventional visual analytical methods, such as dimensionality reduction, could expose data privacy when multi-party datasets are fused into a single site to build point-level relationships. In this paper, we reformulate the conventional t-SNE method from the single-site mode into a secure distributed infrastructure. We present a secure multi-party scheme for joint t-SNE computation, which can minimize the risk of data leakage. Aggregated visualization can be optionally employed to hide disclosure of point-level relationships. We build a prototype system based on our method, SMAP, to support the organization, computation, and exploration of secure joint embedding. We demonstrate the effectiveness of our approach with three case studies, one of which is based on the deployment of our system in real-world applications.

preprint2020arXiv

Solar Flare Intensity Prediction with Machine Learning Models

We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 0$\sim$24, 6$\sim$30, 12$\sim$36 and 24$\sim$48 hours ahead of time using 6, 12, 24 and 48 hours of data (predictors) for each Helioseismic and Magnetic Imager (HMI) Active Region Patch (HARP). The model makes use of (1) the Space-weather HMI Active Region Patch (SHARP) parameters as predictors and (2) the exact flare intensities instead of class labels recorded in the Geostationary Operational Environmental Satellites (GOES) data set, which serves as the source of the response variables. Compared to solar flare classification, the model offers us more detailed information about the exact maximum flux level, i.e. intensity, for each occurrence of a flare. We also consider classification models built on top of the regression model and obtain better results in solar flare classifications. Our results suggest that the most efficient time period for predicting the solar activity is within 24 hours before the prediction time using the SHARP parameters and the LSTM model.

preprint2020arXiv

The Predicted Properties of Helium-Enriched Globular Cluster Progenitors at High Redshift

Globular cluster progenitors may have been detected by \textit{HST}, and are predicted to be observable with \textit{JWST} and ground-based extremely-large telescopes with adaptive optics. This has the potential to elucidate the issue of globular cluster formation and the origins of significantly helium-enriched subpopulations, a problem in Galactic astronomy with no satisfactory theoretical solution. Given this context, we use model stellar tracks and isochrones to investigate the predicted observational properties of helium-enriched stellar populations in globular cluster progenitors. We find that, relative to helium-normal populations, helium-enriched ($ΔY=+0.12$) stellar populations similar to those inferred in the most massive globular clusters, are expected, modulo some rapid fluctuations in the first $\sim$30 Myr, to be brighter and redder in the rest frame. At fixed age, stellar mass, and metallicity, a helium-enriched population is predicted to converge to being $\sim$0.40 mag brighter at $λ\approx 2.0\, μm$, and to be 0.30 mag redder in the \textit{JWST}-NIRCam colour $(F070W-F200W)$, and to actually be fainter for $λ\lesssim 0.50 \, μm$. Separately, we find that the time-integrated shift in ionizing radiation is a negligible $\sim 5\%$, though we show that the Lyman-$α$ escape fraction could end up higher for helium-enriched stars.

preprint2020arXiv

The smallest eigenvalue of large Hankel matrices generated by a singularly perturbed Laguerre weight

An asymptotic expression of the orthonormal polynomials $\mathcal{P}_{N}(z)$ as $N\rightarrow\infty$, associated with the singularly perturbed Laguerre weight $w_α(x;t)=x^α{\rm e}^{-x-\frac{t}{x}},~x\in[0,\infty),~α>-1,~t\geq0$ is derived. Based on this, we establish the asymptotic behavior of the smallest eigenvalue, $λ_{N}$, of the Hankel matrix generated by the weight $w_α(x;t)$.

preprint2020arXiv

Thermodynamic phase transition of a Schwarzschild black hole with global monopole under GUP

In this paper, considering the influence of the principle of generalized uncertainty (GUP), the phase transition of a Schwarzschild black hole with global monopole is discussed. First, we use the generalized Dirac equation to obtain corrected Hawking temperature, local temperature, black hole residue, black hole entropy, thermal capacity, and other thermodynamic quantities. Then, we use images to analyze the effects of generalized uncertainty parameters on phase transitions and the effects of magnetic monopole parameters on phase transitions. Finally, we study the thermodynamic stability and phase change structure under the influence of the principle of generalized uncertainty. The results show that, in the black hole with global monopole, there are first-order and second-order phase transitions. In addition, the general uncertainty parameters and monopole parameters will affect the black hole residues.

preprint2020arXiv

Vulnerability Assessment of Load Frequency Control Considering Cyber Security

Security is one of the biggest concern in power system operation. Recently, the emerging cyber security threats to operational functions of power systems arouse high public attention, and cybersecurity vulnerability thus become an emerging topic to evaluate compromised operational performance under cyber attack. In this paper, vulnerability of cyber security of load frequency control (LFC) system, which is the key component in energy manage system (EMS), is assessed by exploiting the system response to attacks on LFC variables/parameters. Two types of attacks: 1) injection attack and 2) scale attack are considered for evaluation. Two evaluation criteria reflecting the damage on system stability and power generation are used to quantify system loss under cyber attacks. Through a sensitivity-based method and attack tree models, the vulnerability of different LFC components is ranked. In addition, a post-intrusion cyber attack detection scheme is proposed. Classification-based schemes using typical classification algorithms are studied and compared to identify different attack scenarios.

preprint2019arXiv

Analytical Results for the Dynamics of Parabolic Level-Crossing Model

We study the dynamics of a two-level crossing model with a parabolic separation of the diabatic energies. The solutions are expressed in terms of the tri-confluent Heun equations --- the generalization of the confluent hypergeometric equations. We obtain analytical approximations for the state populations in terms of Airy and Bessel functions. Applicable expressions are derived for a large part of the parameter space. We also provide simple formulas which connect local solution in different time regimes. The validity of the analytical approximations is shown by comparing them to numerical simulations.

preprint2019arXiv

CDEX dark matter experiment: Status and prospects

The China Dark Matter Experiment (CDEX) aims at direct searches of light Weakly Interacting Massive Particles (WIMPs) at the China Jinping Underground Laboratory (CJPL) with an overburden of about 2400m rock. Results from a prototype CDEX-1 994 g p-type Point Contact Germanium(pPCGe) detector are reported. Research programs are pursued to further reduce the physics threshold by improving hardware and data analysis. The CDEX-10 experiment with a pPCGe array of 10 kg target mass range is being tested. The evolution of CDEX program into "CDEX-1T Experiment" with ton-scale germanium detector arrays will also be introduced in this study.

preprint2019arXiv

Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation

Federated learning obtains a central model on the server by aggregating models trained locally on clients. As a result, federated learning does not require clients to upload their data to the server, thereby preserving the data privacy of the clients. One challenge in federated learning is to reduce the client-server communication since the end devices typically have very limited communication bandwidth. This paper presents an enhanced federated learning technique by proposing a synchronous learning strategy on the clients and a temporally weighted aggregation of the local models on the server. In the asynchronous learning strategy, different layers of the deep neural networks are categorized into shallow and deeps layers and the parameters of the deep layers are updated less frequently than those of the shallow layers. Furthermore, a temporally weighted aggregation strategy is introduced on the server to make use of the previously trained local models, thereby enhancing the accuracy and convergence of the central model. The proposed algorithm is empirically on two datasets with different deep neural networks. Our results demonstrate that the proposed asynchronous federated deep learning outperforms the baseline algorithm both in terms of communication cost and model accuracy.

preprint2019arXiv

Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters

We present several methods towards construction of precursors, which show great promise towards early predictions, of solar flare events in this paper. A data pre-processing pipeline is built to extract useful data from multiple sources, Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), to prepare inputs for machine learning algorithms. Two classification models are presented: classification of flares from quiet times for active regions and classification of strong versus weak flare events. We adopt deep learning algorithms to capture both the spatial and temporal information from HMI magnetogram data. Effective feature extraction and feature selection with raw magnetogram data using deep learning and statistical algorithms enable us to train classification models to achieve almost as good performance as using active region parameters provided in HMI/Space-Weather HMI-Active Region Patch (SHARP) data files. Case studies show a significant increase in the prediction score around 20 hours before strong solar flare events.

preprint2019arXiv

local derivations on Witt algebras

In this paper, we prove that every local derivation on Witt algebras $W_n, W_n^+$ or $W_n^{++} $ is a derivation for any $n\in\mathbb{N}$. As a consequence, we obtain that every local derivation on a centerless generalized Virasoro algebra of higher rank is a derivation.

preprint2019arXiv

Orthogonal Polynomials, Asymptotics and Heun Equations

The Painlevé equations arise from the study of Hankel determinants generated by moment matrices, whose weights are expressed as the product of ``classical" weights multiplied by suitable ``deformation factors", usually dependent on a ``time variable'' $t$. From ladder operators one finds second order linear ordinary differential equations for associated orthogonal polynomials with coefficients being rational functions. The Painlevé and related functions appear as the residues of these rational functions. We will be interested in the situation when $n$, the order of the Hankel matrix and also the degree of the polynomials $P_n(x)$ orthogonal with respect to the deformed weights, gets large. We show that the second order linear differential equations satisfied by $P_n(x)$ are particular cases of Heun equations when $n$ is large. In some sense, monic orthogonal polynomials generated by deformed weights mentioned below are solutions of a variety of Heun equa\-tions. Heun equations are of considerable importance in mathematical physics and in the special cases they degenerate to the hypergeometric and confluent hypergeometric equations. In this paper we look at three type of weights: the Jacobi type, which are are supported $(0,1]$ the Laguerre type and the weights deformed by the indicator function of $(a,b)$ $χ_{(a,b)}$ and the step function $θ(x)$.

preprint2019arXiv

Painlevé V, Painlevé XXXIV and the Degenerate Laguerre Unitary Ensemble

In this paper, we study the Hankel determinant associated with the degenerate Laguerre unitary ensemble. This problem originates from the largest or smallest eigenvalue distribution of the degenerate Laguerre unitary ensemble. We derive the ladder operators and its compatibility condition with respect to a general perturbed weight. By applying the ladder operators to our problem, we obtain two auxiliary quantities $R_n(t)$ and $r_n(t)$ and show that they satisfy the coupled Riccati equations, from which we find that $R_n(t)$ satisfies the Painlevé V equation. Furthermore, we prove that $σ_{n}(t)$, a quantity related to the logarithmic derivative of the Hankel determinant, satisfies both the continuous and discrete Jimbo-Miwa-Okamoto $σ$-form of the Painlevé V. In the end, by using Dyson's Coulomb fluid approach, we consider the large $n$ asymptotic behavior of our problem at the soft edge, which gives rise to the Painlevé XXXIV equation.

preprint2019arXiv

Painlevé VI, Painlevé III and the Hankel Determinant Associated with a Degenerate Jacobi Unitary Ensemble

This paper studies the Hankel determinant generated by a perturbed Jacobi weight, which is closely related to the largest and smallest eigenvalue distribution of the degenerate Jacobi unitary ensemble. By using the ladder operator approach for the orthogonal polynomials, we find that the logarithmic derivative of the Hankel determinant satisfies a nonlinear second-order differential equation, which turns out to be the Jimbo-Miwa-Okamoto $σ$-form of the Painlevé VI equation by a translation transformation. We also show that, after a suitable double scaling, the differential equation is reduced to the Jimbo-Miwa-Okamoto $σ$-form of the Painlevé III. In the end, we obtain the asymptotic behavior of the Hankel determinant as $t\rightarrow1^{-}$ and $t\rightarrow0^{+}$ in two important cases, respectively.

preprint2018arXiv

Quantum sensing of local magnetic field texture in strongly correlated electron systems under extreme conditions

An important feature of strong correlated electron systems is the tunability between interesting ground states such as unconventional superconductivity and exotic magnetism. Pressure is a clean, continuous and systematic tuning parameter. However, due to the restricted accessibility introduced by high-pressure devices, compatible magnetic field sensors with sufficient sensitivity are rare. This greatly limits the detections and detailed studies of pressure-induced phenomena. Here, we utilize nitrogen vacancy (NV) centers in diamond as a powerful, spatially-resolved vector field sensor for material research under pressure at cryogenic temperatures. Using a single crystal of BaFe2(As0:59P0:41)2 as an example, we extract the superconducting transition temperature (Tc), the local magnetic field profile in the Meissner state and the critical fields (Hc1 and Hc2). The method developed in this work will become a unique tool for tuning, probing and understanding quantum many body systems.

preprint2017arXiv

Molecular Dynamics Simulations for Anisotropic Thermal Conductivity of Borophene

The present work carries out molecular dynamics simulations to compute the thermal conductivity of the borophene nanoribbon and the borophene nanotube using the Muller-Plathe approach. We investigate the thermal conductivity of the armchair and zigzag borophenes, and show the strong anisotropic thermal conductivity property of borophene. We compare the results of the borophene nanoribbon and the borophene nanotube, and find the thermal conductivity of the borophene is structure dependent.

preprint2016arXiv

Blur Robust Optical Flow using Motion Channel

It is hard to estimate optical flow given a realworld video sequence with camera shake and other motion blur. In this paper, we first investigate the blur parameterization for video footage using near linear motion elements. we then combine a commercial 3D pose sensor with an RGB camera, in order to film video footage of interest together with the camera motion. We illustrates that this additional camera motion/trajectory channel can be embedded into a hybrid framework by interleaving an iterative blind deconvolution and warping based optical flow scheme. Our method yields improved accuracy within three other state-of-the-art baselines given our proposed ground truth blurry sequences; and several other realworld sequences filmed by our imaging system.

preprint2016arXiv

Depict noise-driven nonlinear dynamic networks from output data by using high-order correlations

Many practical systems can be described by dynamic networks, for which modern technique can measure their output signals, and accumulate extremely rich data. Nevertheless, the network structures producing these data are often deeply hidden in these data. Depicting network structures by analysing the available data, i.e., the inverse problems turns to be of great significant. On one hand, dynamics are often driven by various unknown facts, called noises. On the other hand, network structures of practical systems are commonly nonlinear, and different nonlinearities can provide rich dynamic features and meaningful functions of realistic networks. So far, no method, both theoretically or numerically, has been found to systematically treat the both difficulties together. Here we propose to use high-order correlation computations (HOCC) to treat nonlinear dynamics; use two-time correlations to treat noise effects; and use suitable basis and correlator vectors to unifiedly depict all dynamic nonlinearities and topological interaction links and noise statistical structures. All the above theoretical frameworks are constructed in a closed form and numerical simulations fully verify the validity of theoretical predictions.

preprint2016arXiv

Expanding molecular bubble surrounding Tycho's supernova remnant (SN 1572) observed with IRAM 30 m telescope: evidence for a single-degenerate progenitor

Whether the progenitors of SNe Ia are single-degenerate or double-degenerate white dwarf (WD) systems is a highly debated topic. To address the origin of the Type Ia Tycho's supernova remnant (SNR), SN 1572, we have carried out a $^{12}$CO J=2-1 mapping and a 3-mm line survey toward the remnant using the IRAM 30 m telescope. We show that Tycho is surrounded by a clumpy molecular bubble at a local standard of rest velocity of $\sim 61$ km s$^{-1}$ which expands at a speed of $\sim 4.5$ km s$^{-1}$ and has a mass of $\sim 220$ M$_\odot$ (at the distance of 2.5 kpc). Enhanced $^{12}$CO J=2-1 line emission relative to $^{12}$CO J=1-0 emission and possible line broadenings (in velocity range $-64$ to $-60$ km s$^{-1}$) are found at the northeastern boundary of the SNR, where the shell is deformed and decelerated. These features, combined with the morphological correspondence between the expanding molecular bubble and Tycho, suggest that the SNR is associated with the bubble at the velocity range $-66$ to $-57$ km s$^{-1}$. The most plausible origin for the expanding bubble is the fast outflow (with velocity of hundreds km s$^{-1}$) driven from the vicinity of a WD as it accreted matter from a nondegenerate companion star. The SNR has been expanding in the low-density wind-blown bubble, and the shock wave has just reached the molecular cavity wall. The SNR has been expanding in the low-density wind-blown bubble, and the shock wave has just reached the molecular cavity wall. This is the first unambiguous detection of an expanding bubble driven by the progenitor of a Type-Ia SNR, which constitutes evidence for a single-degenerate progenitor for this SN Ia.

preprint2016arXiv

Guiding 2.94 $ μ$m using low-loss microstructured antiresonant triangular-core fibers

We introduce a new simple design of hollow-core microstructured fiber targeted to guide mid-infrared light at a wavelength 2.94 $ μ$m. The fiber has a triangular-core supported via silica-glass webs enclosed by a large hollow capillary tube. The fiber specific dimensions are determined based on the guiding technique, which is based on the anti-resonant mechanism. For a triangular-core with side length $100$ $ μ$m, the fiber has a minimum transmission loss $0.08\pm0.005$ dB/m and dispersion 2.3 ps/km/nm at the operational wavelength 2.94 $ μ$m.

preprint2016arXiv

Interaction between the Supernova Remnant HB 3 and the Nearby Star-Forming Region W3

We performed millimeter observations in CO lines toward the supernova remnant (SNR) HB 3. Substantial molecular gas around -45 km s^-1 is detected in the conjunction region between the SNR HB 3 and the nearby W3 complex. This molecular gas is distributed along the radio continuum shell of the remnant. Furthermore, the shocked molecular gas indicated by line wing broadening features is also distributed along the radio shell and inside it. By both morphological correspondence and dynamical evidence, we confirm that the SNR HB 3 is interacting with the -45 km s^-1 molecular cloud (MC), in essence, with the nearby H II region/MC complex W3. The red-shifted line wing broadening features indicate that the remnant is located at the nearside of the MC. With this association, we could place the remnant at the same distance as the W3/W4 complex, which is 1.95 +- 0.04 kpc. The spatial distribution of aggregated young stellar object candidates (YSOc) shows a correlation to the shocked molecular strip associated with the remnant. We also find a binary clump of CO at (l = 132.94 deg, b = 1.12 deg) around -51.5 km s^-1 inside the projected extent of the remnant, and it is associated with significant mid-infrared (mid-IR) emission. The binary system also has a tail structure resembling the tidal tails of interacting galaxies. According to the analysis of CO emission lines, the larger clump in this binary system is about stable, and the smaller clump is significantly disturbed.

preprint2016arXiv

Low-rank Matrix Factorization under General Mixture Noise Distributions

Many computer vision problems can be posed as learning a low-dimensional subspace from high dimensional data. The low rank matrix factorization (LRMF) represents a commonly utilized subspace learning strategy. Most of the current LRMF techniques are constructed on the optimization problems using L1-norm and L2-norm losses, which mainly deal with Laplacian and Gaussian noises, respectively. To make LRMF capable of adapting more complex noise, this paper proposes a new LRMF model by assuming noise as Mixture of Exponential Power (MoEP) distributions and proposes a penalized MoEP (PMoEP) model by combining the penalized likelihood method with MoEP distributions. Such setting facilitates the learned LRMF model capable of automatically fitting the real noise through MoEP distributions. Each component in this mixture is adapted from a series of preliminary super- or sub-Gaussian candidates. Moreover, by facilitating the local continuity of noise components, we embed Markov random field into the PMoEP model and further propose the advanced PMoEP-MRF model. An Expectation Maximization (EM) algorithm and a variational EM (VEM) algorithm are also designed to infer the parameters involved in the proposed PMoEP and the PMoEP-MRF model, respectively. The superseniority of our methods is demonstrated by extensive experiments on synthetic data, face modeling, hyperspectral image restoration and background subtraction.

preprint2016arXiv

Multi-wavelength study of the supernova remnant Kes 79 (G33.6+0.1): On its supernova properties and expansion into a molecular environment

Kes 79 (G33.6+0.1) is an aspherical thermal composite supernova remnant (SNR) observed across the electromagnetic spectrum and showing an unusual highly-structured morphology, in addition to harboring a central compact object (CCO). Using the CO J=1-0, J=2-1, and J=3-2 data, we provide the first direct evidence and new morphological evidence to support the physical interaction between the SNR and the molecular cloud at $V_LSR\sim 105$ km s$^{-1}$. We revisit the 380 ks XMM-Newton observations and perform a dedicated spatially resolved X-ray spectroscopic study with careful background subtraction. The overall X-ray-emitting gas is characterized by an under-ionized ($τ_c \sim 6\times 10^{11}$ cm^${-3}$) cool ($kT_c \approx 0.20$ keV) plasma with solar abundances, plus an under-ionized ($τ_h\sim 8\times 10^{10}$ cm$^{-3}$) hot ($kT_h\approx 0.80$ keV) plasma with elevated Ne, Mg, Si, S and Ar abundances. Kes 79 appears to have a double-hemisphere morphology viewed along the symmetric axis. Projection effect can explain the multiple shell structures and the thermal composite morphology. The X-ray filaments, spatially correlated with the 24 um IR filaments, are suggested to be due to the SNR shock interaction with dense gas, while the halo forms from SNR breaking out into a tenuous medium. The high-velocity, hot ($kT_h\sim 1.4$--1.6 keV) ejecta patch with high metal abundances, together with the non-uniform metal distribution across the SNR, indicating an asymmetric SN explosion of Kes 79. We refine the Sedov age to 4.4--6.7 kyr and the mean shock velocity to 730 km s$^{-1}$. Our multi-wavelength study suggests a progenitor mass of $\sim 15$--20 solar masses for the core-collapse explosion that formed Kes 79 and its CCO, PSR J1852+0040.

preprint2016arXiv

Performance analysis of a non-beacon enabled IEEE 802.15.4 network with retransmission and ACK mode

The aim of our work is to evaluate the performance of non-beacon IEEE 802.15.4 networks with acknowledgement (ACK) mode and retransmission limits in a finer time unit. Moreover, we predict network performance parameters using backpropagation artificial neural networks (BP-ANNs) with respect to a given quality of service for real-world applications. Therefore, our proposed methods can assist the deployment of a star network with its performance specified in a more practical way. First, the discrete time Markov chain model and M/M/1/k queue are used to describe the full unslotted carrier sense multiple access with collision avoidance (CSMA/CA) algorithm in a non-beacon network. Considering MAC buffer size, unsaturated traffic, and saturated traffic, we build three analytical models to derive eight important performance metrics, e.g., throughput, delay, and reliability. In addition, extensive simulation results show the accuracy of the analytical models in throughput and reliability. Finally, we use the analytical data to train the BP-ANNs models to predict the key parameters such as node number and delay. All results from the simulation data used to test the BP-ANNs show the accuracy these models. Thus, these methods and results can be used to deploy star networks in application environments.

preprint2016arXiv

Phase Retrieval of Real-Valued Signals in a Shift-Invariant Space

Phase retrieval arises in various fields of science and engineering and it is well studied in a finite-dimensional setting. In this paper, we consider an infinite-dimensional phase retrieval problem to reconstruct real-valued signals living in a shift-invariant space from its phaseless samples taken either on the whole line or on a set with finite sampling rate. We find the equivalence between nonseparability of signals in a linear space and its phase retrievability with phaseless samples taken on the whole line. For a spline signal of order $N$, we show that it can be well approximated, up to a sign, from its noisy phaseless samples taken on a set with sampling rate $2N-1$. We propose an algorithm to reconstruct nonseparable signals in a shift-invariant space generated by a compactly supported continuous function. The proposed algorithm is robust against bounded sampling noise and it could be implemented in a distributed manner.

preprint2016arXiv

The Likely Fermi detection of the supernova remnant SN 1006

We report the likely detection of gamma-ray emission from the northeast shell region of the historical supernova remnant (SNR) SN 1006. Having analyzed 7 years of Fermi LAT Pass 8 data for the region of SN 1006, we found a GeV gamma-ray source detected with 4 sigma significance. Both the position and spectrum of the source match those of HESS J1504-418 respectively, which is TeV emission from SN 1006. Considering the source as the GeV gamma-ray counterpart to SN~1006, the broadband spectral energy distribution is found to be approximately consistent with the leptonic scenario that has been proposed for the TeV emission from the SNR. Our result has likely confirmed the previous study of the SNRs with TeV shell-like morphology: SN 1006 is one of them sharing very similar peak luminosity and spectral shape.

preprint2016arXiv

The role of the diffusive protons in the gamma-ray emission of supernova remnant RX J1713.7$-$3946 --- a two-zone model

RX~J1713.7$-$3946 is a prototype in the $γ$-ray-bright supernova remnants (SNRs) and is in continuing debates on its hadronic versus leptonic origin of the $γ$-ray emission. We explore the role played by the diffusive relativistic protons that escape from the SNR shock wave in the $γ$-ray emission, apart from the high-energy particles' emission from the inside of the SNR. In the scenario that the SNR shock propagates in a clumpy molecular cavity, we consider that the$γ$-ray emission from the inside of the SNR may arise either from the inverse Compton scattering or from the interaction between the trapped energetic protons and the shocked clumps. The dominant origin between them depends on the electron-to-proton number ratio. The diffusive protons that escaped from the shock wave during the expansion history can provide an outer hadronic $γ$-ray component by bombarding the surrounding dense matter. The broadband spectrum can be well explained by this two-zone model, in which the $γ$-ray emission from the inside governs the TeV band, while the outer emission component substantially contributes to the GeV $γ$-rays. The two-zone model can also explain the TeV $γ$-ray radial brightness profile that significantly stretches beyond the nonthermal X-ray-emitting region. In the calculation, we present a simplified algorithm for Li & Chen's (2010) "accumulative diffusion" model for escaping protons and apply the Markov Chain Monte Carlo method to constrain the physical parameters.

preprint2015arXiv

A neural network z-vertex trigger for Belle II

We present the concept of a track trigger for the Belle II experiment, based on a neural network approach, that is able to reconstruct the z (longitudinal) position of the event vertex within the latency of the first level trigger. The trigger will thus be able to suppress a large fraction of the dominating background from events outside of the interaction region. The trigger uses the drift time information of the hits from the Central Drift Chamber (CDC) of Belle II within narrow cones in polar and azimuthal angle as well as in transverse momentum (sectors), and estimates the z-vertex without explicit track reconstruction. The preprocessing for the track trigger is based on the track information provided by the standard CDC trigger. It takes input from the 2D ($r - φ$) track finder, adds information from the stereo wires of the CDC, and finds the appropriate sectors in the CDC for each track in a given event. Within each sector, the z-vertex of the associated track is estimated by a specialized neural network, with a continuous output corresponding to the scaled z-vertex. The input values for the neural network are calculated from the wire hits of the CDC.

preprint2015arXiv

A z-Vertex Trigger for Belle II

The Belle II experiment will go into operation at the upgraded SuperKEKB collider in 2016. SuperKEKB is designed to deliver an instantaneous luminosity $\mathcal{L}=8\times10^{35}\,\mathrm{cm}^{-2}\,\mathrm{s}^{-1}$. The experiment will therefore have to cope with a much larger machine background than its predecessor Belle, in particular from events outside of the interaction region. We present the concept of a track trigger, based on a neural network approach, that is able to suppress a large fraction of this background by reconstructing the $z$ (longitudinal) position of the event vertex within the latency of the first level trigger. The trigger uses the hit information from the Central Drift Chamber (CDC) of Belle II within narrow cones in polar and azimuthal angle as well as in transverse momentum ("sectors"), and estimates the $z$-vertex without explicit track reconstruction. The preprocessing for the track trigger is based on the track information provided by the standard CDC trigger. It takes input from the 2D track finder, adds information from the stereo wires of the CDC, and finds the appropriate sectors in the CDC for each track. Within the sector, the $z$-vertex is estimated by a specialized neural network, with the drift times from the CDC as input and a continuous output corresponding to the scaled $z$-vertex. The neural algorithm will be implemented in programmable hardware. To this end a Virtex 7 FPGA board will be used, which provides at present the most promising solution for a fully parallelized implementation of neural networks or alternative multivariate methods. A high speed interface for external memory will be integrated into the platform, to be able to store the $\mathcal{O}(10^9)$ parameters required. The contribution presents the results of our feasibility studies and discusses the details of the envisaged hardware solution.

preprint2015arXiv

Analysis and Design of Multiple-Antenna Cognitive Radios with Multiple Primary User Signals

We consider multiple-antenna signal detection of primary user transmission signals by a secondary user receiver in cognitive radio networks. The optimal detector is analyzed for the scenario where the number of primary user signals is no less than the number of receive antennas at the secondary user. We first derive exact expressions for the moments of the generalized likelihood ratio test (GLRT) statistic, yielding approximations for the false alarm and detection probabilities. We then show that the normalized GLRT statistic converges in distribution to a Gaussian random variable when the number of antennas and observations grow large at the same rate. Further, using results from large random matrix theory, we derive expressions to compute the detection probability without explicit knowledge of the channel, and then particularize these expressions for two scenarios of practical interest: 1) a single primary user sending spatially multiplexed signals, and 2) multiple spatially distributed primary users. Our analytical results are finally used to obtain simple design rules for the signal detection threshold.

preprint2015arXiv

Asymptotics of determinants of Hankel matrices via non-linear difference equations

E. Heine in the 19th century studied a system of orthogonal polynomials associated with the weight $\left[x(x-α)(x-β)\right]^{-\frac{1}{2}}$, $x\in[0,α]$, $0<α<β$. A related system was studied by C. J. Rees in 1945, associated with the weight $\left[(1-x^2)(1-k^2x^2)\right]^{-\frac{1}{2}}$, $x\in[-1,1]$, $k^2\in(0,1)$. These are also known as elliptic orthogonal polynomials, since the moments of the weights maybe expressed in terms of elliptic integrals. Such orthogonal polynomials are of great interest because the corresponding Hankel determinant, depending on a parameter $k^2$, where $0<k^2<1$ is the $τ$~function of a particular Painlevé VI, the special cases of which are related to enumerative problems arising from string theory. We show that the recurrence coefficients, denoted by $β_n(k^2),\;n=1,2,\dots$; and ${\rm p}_1(n,k^2)$, the coefficients of $x^{n-2}$ of the monic polynomials orthogonal with respect to a generalized version of the weight studied by Rees, $$ (1-x^2)^α(1-k^2x^2)^β,\;\;x\in[-1,1],\;α>-1,\;β\in \mathbb{R}, $$ satisfy second order non-linear difference equations. The large $n$ expansion based on the difference equations when combined with known asymptotics of the leading terms of the associated Hankel determinant yields a complete asymptotic expansion of the Hankel determinant. The Painlevé equation is also discussed as well as the generalization of the linear second order differential equation found by Rees.

preprint2015arXiv

Color Image Classification via Quaternion Principal Component Analysis Network

The Principal Component Analysis Network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in various databases. However, the performance of PCANet may be degraded when dealing with color images. In this paper, a Quaternion Principal Component Analysis Network (QPCANet), which is an extension of PCANet, is proposed for color images classification. Compared to PCANet, the proposed QPCANet takes into account the spatial distribution information of color images and ensures larger amount of intra-class invariance of color images. Experiments conducted on different color image datasets such as Caltech-101, UC Merced Land Use, Georgia Tech face and CURet have revealed that the proposed QPCANet achieves higher classification accuracy than PCANet.

preprint2015arXiv

GeV γ-ray Emission Detected by Fermi-LAT Probably Associated with the Thermal Composite Supernova Remnant Kesteven 41 in a Molecular Environment

Hadron emission from supernova remnant (SNR)-molecular cloud (MC) association systems has been widely regarded as a probe of the shock-accelerated cosmic-ray protons. Here, we report on the detection of a γ-ray emission source, with a significance of 24σ in 0.2-300 GeV, projected to lie to the northwest of the thermal composite SNR Kesteven 41, using 5.6 years of Fermi-Large Area Telescope (LAT) observation data. No significant long-term variability in the energy range 0.2--300 GeV is detected around this source. The 3σ error circle, 0.09 degree; in radius, covers the 1720MHz OH maser and is essentially consistent with the location of the V_{LSR} ~-50 km/s MC with which the SNR interacts. The source emission has an exponential cutoff power-law spectrum with a photon index of 1.9+/-0.1 and a cutoff energy of 4.0+/-0.9 GeV, and the corresponding 0.2-300 GeV luminosity is ~1.3*10^36 erg/s at a distance of 12 kpc. There is no radio pulsar in the 3σ circle responsible for the high γ-ray luminosity. While the inverse Compton scattering scenario would lead to a difficulty in the electron energy budget, the source emission can naturally be explained by the hadronic interaction between the relativistic protons accelerated by the shock of SNR Kesteven 41 and the adjacent northwestern MC. In this paper, we present a list of Galactic thermal composite SNRs detected at GeV γ-ray energies by Fermi-LAT is presented.

preprint2015arXiv

Large n-limit for Random matrices with External Source with 3 eigenvalues

In this paper, we analyze the large n-limit for random matrix with external source with three distinct eigenvalues. And we confine ourselves in the Hermite case and the three distinct eigenvalues are $-a,0,a$. For the case $a^2>3$, we establish the universal behavior of local eigenvalue correlations in the limit $n\rightarrow \infty$, which is known from unitarily invariant random matrix models. Thus, local eigenvalue correlations are expressed in terms of the sine kernel in the bulk and in terms of the Airy kernel at the edge of the spectrum. The result can be obtained by analyzing $4\times 4$ Riemann-Hilbert problem via nonlinear steepest decent method.

preprint2015arXiv

Locally weighted Markov chain Monte Carlo

We propose a weighting scheme for the proposals within Markov chain Monte Carlo algorithms and show how this can improve statistical efficiency at no extra computational cost. These methods are most powerful when combined with multi-proposal MCMC algorithms such as multiple-try Metropolis, which can efficiently exploit modern computer architectures with large numbers of cores. The locally weighted Markov chain Monte Carlo method also improves upon a partial parallelization of the Metropolis-Hastings algorithm via Rao-Blackwellization. We derive the effective sample size of the output of our algorithm and show how to estimate this in practice. Illustrations and examples of the method are given and the algorithm is compared in theory and applications with existing methods.

preprint2015arXiv

Morphology and structure of BzK-selected galaxies at z~2 in the CANDELS-COSMOS field

Utilizing a BzK-selected technique, we obtain 14550 star-forming galaxies (sBzKs) and 1763 passive galaxies (pBzKs) at z~2 from the K-selected (K<22.5) catalog in the COSMOS/UltraVISTA field. The differential number counts of sBzKs and pBzKs are consistent with the results from the literature. Compared to the observed results, semi-analytic models of galaxy formation and evolution provide too few (many) galaxies at high (low)-mass end. Moreover, we find that the star formation rate (SFR) and stellar mass of sBzKs follow the relation of main sequence. Based on the HST/Wide Field Camera 3 (WFC3) F160W imaging, we find a wide range of morphological diversities for sBzKs, from diffuse to early-type spiral structures, with relatively high M20, large size and low G, while pBzKs are elliptical-like compact morphologies with lower M20, smaller size and higher G, indicating the more concentrated and symmetric spatial extent of stellar population distribution in pBzKs than sBzKs. Furthermore, the sizes of pBzKs (sBzKs) at z~2 are on average two to three (one to two) times smaller than those of local early-type (late-type) galaxies with similar stellar mass. Our findings imply that the two classes have different evolution modes and mass assembly histories.

preprint2015arXiv

OI and CaII observations in intermediate redshift quasars

We present an unprecedented spectroscopic survey of the CaII triplet + OI for a sample of 14 luminous ($-$26 $\gtrsim$ M$_V$ $\gtrsim$ $-$29), intermediate redshift (0.85 $\lesssim$ $z$ $\lesssim$ 1.65) quasars. The ISAAC spectrometer at ESO VLT allowed us to cover the CaII NIR spectral region redshifted into the H and K windows. We describe in detail our data analysis which enabled us to detect CaII triplet emission in all 14 sources (with the possible exception of HE0048-2804) and to retrieve accurate line widths and fluxes of the triplet and OI $λ$8446. The new measurements show trends consistent with previous lower $z$ observations, indicating that CaII and optical FeII emission are probably closely related. The ratio between the CaII triplet and the optical FeII blend at $λ$4570 $Å$ is apparently systematically larger in our intermediate redshift sample relative to a low-$z$ control sample. Even if this result needs a larger sample for adequate interpretation, higher CaII/optical FeII should be associated with recent episodes of star formation in the intermediate redshift quasars and, at least in part, explain an apparent correlation of CaII triplet equivalent width with $z$ and $L$. The CaII triplet measures yield significant constraints on the emitting region density and ionization parameter, implying CaII triplet emission from log n$_H$ $\gtrsim$ 11 [cm$^{-3}$] and ionization parameter log $U$ $\lesssim$ 1.5. Line width and intensity ratios suggest properties consistent with emission from the outer part of a high density broad line region (a line emitting accretion disk?).

preprint2015arXiv

PARSEC evolutionary tracks of massive stars up to $350 M_\odot$ at metallicities 0.0001$\leq Z \leq$0.04

We complement the PARSEC data base of stellar evolutionary tracks with new models of massive stars, from the pre-main sequence phase to the central carbon ignition. We consider a broad range of metallicities, 0.0001$\leq Z \leq$0.04 and initial masses up to $M_{\rm ini}=350\,M_\odot$. The main difference with respect to our previous models of massive stars is the adoption of a recent formalism accounting for the mass-loss enhancement when the ratio of the stellar to the Eddington luminosity, $Γ_e$, approaches unity. With this new formalism, the models are able to reproduce the Humphreys-Davidson limit observed in the Galactic and Large Magellanic Cloud colour-magnitude diagrams, without an ad hoc mass-loss enhancement. We also follow the predictions of recent wind models indicating that the metallicity dependence of the mass-loss rates becomes shallower when $Γ_e$ approaches unity. We thus find that the more massive stars may suffer from substantial mass-loss even at low metallicity. We also predict that the Humphreys-Davidson limit should become brighter at decreasing metallicity. We supplement the evolutionary tracks with new tables of theoretical bolometric corrections, useful to compare tracks and isochrones with the observations. For this purpose, we homogenize existing stellar atmosphere libraries of hot and cool stars (PoWR, ATLAS9 and Phoenix) and we add, where needed, new atmosphere models computed with WM-basic. The mass, age and metallicity grids are fully adequate to perform detailed investigations of the properties of very young stellar systems, both in local and distant galaxies. The new tracks supersede the previous old Padova models of massive stars.

preprint2015arXiv

Perturbed Hankel determinant, correlation functions and Painlevé equations

We continue with the study of the Hankel determinant, $$ D_{n}(t,α,β):=\det\left(\int_{0}^{1}x^{j+k}w(x;t,α,β)dx\right)_{j,k=0}^{n-1}, $$ generated by a Pollaczek-Jacobi type weight, $$ w(x;t,α,β):=x^α(1-x)^β{\rm e}^{-t/x}, \quad x\in [0,1], \quad α>0, \quad β>0, \quad t\geq 0. $$ This reduces to the "pure" Jacobi weight at $t=0.$ We may take $α\in \mathbb{R}$, in the situation while $t$ is strictly greater than $0.$ It was shown in Chen and Dai (2010), that the logarithmic derivative of this Hankel determinant satisfies a Jimbo-Miwa-Okamoto $σ$-form of Painlevé \uppercase\expandafter{\romannumeral5} (${\rm P_{\uppercase\expandafter{\romannumeral5}}}$). In fact the logarithmic of the Hankel determinant has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral5}}}.$ \\ In this paper, we show that, under a double scaling, where $n$ the dimension of the Hankel matrix tends to $\infty$, and $t$ tends to $0^{+},$ such that $s:=2n^2t$ is finite, the double scaled Hankel determinant (effectively an operator determinant) has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral3}'}}.$ Expansions of the scaled Hankel determinant for small and large $s$ are found. A further double scaling with $α=-2n+λ,$ where $n\rightarrow \infty$ and $t,$ tends to $0^{+},$ such that $s:=nt$ is finite. In this situation the scaled Hankel determinant has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral5}}},$ %which can be degenerate to a particular ${\rm P_{\uppercase\expandafter{\romannumeral3}}}$ and its small and large $s$ asymptotic expansions are also found.

preprint2015arXiv

Reconstruction of sparse wavelet signals from partial Fourier measurements

In this paper, we show that high-dimensional sparse wavelet signals of finite levels can be constructed from their partial Fourier measurements on a deterministic sampling set with cardinality about a multiple of signal sparsity.

preprint2015arXiv

Singular linear statistics of the Laguerre Unitary Ensemble and Painlevé III (${\rm P_{III}}$): Double scaling analysis

We continue with the study of the Hankel determinant, $$ D_{n}(t,α):=\det\left(\int_{0}^{\infty}x^{j+k}w(x;t,α)dx\right)_{j,k=0 }^{n-1}, $$ generated by singularly perturbed Laguerre weight, $$ w(x;t,α):=x^α{\rm e}^{-x}\:{\rm e}^{-t/x}, \quad 0\leq x<\infty,\;\;\;α>0,\;\;\;\;t>0, $$ obtained through a deformation of the Laguerre weight function, $$ w(x;0,α):=x^α{\rm e}^{-x},\quad 0\leq x<\infty,\;\; α>0, $$ via the multiplicative factor ${\rm e}^{-t/x}$. \\ An earlier investigation was made on the finite $n$ aspect of the problem, this has appeared in \cite{ci1}. There, it was found that the logarithm of the Hankel determinant has an integral representation in terms of a particular ${\rm P_{III}},$ and its derivative with $t.$ In this paper we show that, under a double scaling, where $n$, the order of the Hankel matrix tends to $\infty,$ and $t$, tends to $0$, the scaled---and therefore, in some sense, infinite dimensional---Hankel determinant, has an integral representation in terms of the $C$ potential, and its derivatives. The second order non-linear differential equation which the $C$ potential satisfies, after a minor change of variables, is another ${\rm P_{III}},$ albeit with fewer number of parameters. \\ Expansions of the double scaled determinant for small and large parameter are obtained.

preprint2015arXiv

Spectra of Bochner-Riesz means on $L^p$

The Bochner-Riesz means are shown to have either the unit interval $[0,1]$ or the whole complex plane as their spectra on $L^p, 1\le p<\infty$

preprint2015arXiv

Supernova Remnant Kesteven 27: Interaction with A Neighbor HI Cloud Viewed by Fermi

We report on the likely detection of gamma-ray emission from the supernova remnant (SNR) Kesteven 27 (Kes 27). We analyze 5.7 yr Fermi Large Area Telescope data of the SNR region and find an unresolved source at a position consistent with the radio brightness peak and the X-ray knot of Kes 27, which is located in the eastern region of the SNR and caused by the interaction with a nearby HI cloud. The source's emission is best fit with a power-law spectrum with a photon index of 2.5 +/- 0.1 and a >0.2 GeV luminosity of 5.8*10^34 erg s^-1 assuming a distance of 4.3 kpc, as derived from radio observations of the nearby HI cloud. Comparing the properties of the source with that of other SNRs that are known to be interacting with nearby high-density clouds, we discuss the origin of the source's emission. The spectral energy distribution of the source can be described by a hadronic model that considers the interaction of energetic protons, escaping from the shock front of Kes 27, with a high-density cloud.

preprint2015arXiv

The Metal-enriched Thermal Composite Supernova Remnant Kesteven 41 (G337.8-0.1) in a Molecular Environment

The physical nature of thermal composite supernova remnants (SNRs) remains controversial. We have revisited the archival XMM-Newton and Chandra data of the thermal composite SNR Kesteven 41 (Kes 41 or G337.8-0.1) and performed a millimeter observation toward this source in the $^{12}$CO, $^{13}$CO, and C$^{18}$O lines. The X-ray emission, mainly concentrated toward the southwestern part of the SNR, is characterized by distinct S and Ar He-like lines in the spectra. The X-ray spectra can be fitted with an absorbed nonequilibrium ionization collisional plasma model at a temperature of 1.3-2.6 keV and an ionization timescale of 0.1-1.2$\times$10$^{12}$ cm$^{-3}$ s. The metal species S and Ar are overabundant, with 1.2-2.7 and 1.3-3.8 solar abundances, respectively, which strongly indicate the presence of a substantial ejecta component in the X-ray-emitting plasma of this SNR. Kes 41 is found to be associated with a giant molecular cloud (MC) at a systemic local standard of rest velocity of -50 km s$^{-1}$ and confined in a cavity delineated by a northern molecular shell, a western concave MC that features a discernible shell, and an HI cloud seen toward the southeast of the SNR. The birth of the SNR in a preexisting molecular cavity implies a mass of $\gtrsim$18 M$_{\odot}$ for the progenitor if it was not in a binary system. Thermal conduction and cloudlet evaporation seem to be feasible mechanisms to interpret the X-ray thermal composite morphology, and the scenario of gas reheating by the shock reflected from the cavity wall is quantitatively consistent with the observations. An updated list of thermal composite SNRs is also presented in this paper.

preprint2015arXiv

Thermal conductivity of graphene kirigami: ultralow and strain robustness

Kirigami structure, from the macro- to the nanoscale, exhibits distinct and tunable properties from original 2-dimensional sheet by tailoring. In present work, the extreme reduction of the thermal conductivity by tailoring sizes in graphene nanoribbon kirigami (GNR-k) is demonstrated using nonequilibrium molecular dynamics simulations. The results show that the thermal conductivity of GNR-k (around 5.1 Wm-1K-1) is about two orders of magnitude lower than that of the pristine graphene nanoribbon (GNR) (around 151.6 Wm-1K-1), while the minimum value is expected to be approaching zero in extreme case from our theoretical model. To explore the origin of the reduction of the thermal conductivity, the micro-heat flux on each atoms of GNR-k has been further studied. The results attribute the reduction of the thermal conductivity to three main sources as: the elongation of real heat flux path, the overestimation of real heat flux area and the phonon scattering at the vacancy of the edge. Moreover, the strain engineering effect on the thermal conductivity of GNR-k and a thermal robustness property has been investigated. Our results provide physical insights into the origins of the ultralow and robust thermal conductivity of GNR-k, which also suggests that the GNR-k can be used for nanaoscale heat management and thermoelectric application.

preprint2014arXiv

An XMM-Newton study of the mixed-morphology supernova remnant W28 (G6.4-0.1)

We have performed an XMM-Newton imaging and spectroscopic study of supernova remnant (SNR) W28, a prototype mixed-morphology or thermal composite SNR, believed to be interacting with a molecular cloud. The observed hot X-ray emitting plasma is characterized by low metal abundances, showing no evidence of ejecta. The X-rays arising from the deformed northeast shell consist of a thermal component with a temperature of $\sim0.3$ keV plus a hard component of either thermal (temperature $\sim 0.6$ keV) or non-thermal (photon index $=0.9$-2.4) origin. The X-ray emission in the SNR interior is blobby and the corresponding spectra are best described as the emission from a cold ($kT\sim0.4$ keV) plasma in non-equilibrium ionization with an ionization timescale of $\sim4.3\times 10^{11}$ cm$^{-3}$ s plus a hot ($kT \sim 0.8$ keV) gas in collisional ionization equilibrium. Applying the two-temperature model to the smaller central regions, we find non-uniform interstellar absorption, temperature and density distribution, which indicates that the remnant is evolving in a non-uniform environment with denser material in the east and north. The cloudlet evaporation mechanism can essentially explain the properties of the X-ray emission in the center and thermal conduction may also play a role for length scales comparable to the remnant radius. A recombining plasma model with an electron temperature of $\sim 0.6$ keV is also feasible for describing the hot central gas with the recombination age of the gas estimated at $\sim2.9\times 10^4$ yr.

preprint2014arXiv

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrix Models

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central $F$ matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an $O(1)$ correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

preprint2014arXiv

Continuous and discrete Painleve equations arising from the gap probability distribution of the finite $n$ Gaussian Unitary Ensembles

In this paper we study the gap probability problem in the Gaussian Unitary Ensembles of $n$ by $n$ matrices : The probability that the interval $J := (-a,a)$ is free of eigenvalues. In the works of Tracy and Widom, Adler and Van Moerbeke and Forrester and Witte on this subject, it has been shown that two Painleve type differential equations arise in this context. The first is the Jimbo-Miwa-Okomoto $σ-$form and the second is a particular Painleve IV. Using the ladder operator technique of orthogonal polynomials we derive three quantities associated with the gap probability, denoted by $σ_n(a)$, $R_n(a)$ and $r_n(a)$, and show that each one satisfying a second order, non-linear, differential equation as well as a second order, non-linear difference equation. In particular, in addition to providing an elementary derivation of the aforementioned $σ-$form and Painleve IV we show that the quantity $r_n(a)$ satisfies a particular case of Chazy's second degree second order differential equation. For the discrete equations we show that the quantity $r_n(a)$ satisfies a particular form of the modified discrete Painleve II equation obtained by Grammaticos and Ramani in the context of Backlund transformations. We also derive second order second degree difference equations for the quantities $R_n(a)$ and $σ_n(a)$.

preprint2014arXiv

Discovery of the transient magnetar 3XMM J185246.6+003317 near supernova remnant Kesteven 79 with XMM-Newton

We report the serendipitous discovery with XMM-Newton that 3XMM J185246.6+003317 is an 11.56 s X-ray pulsar located 1' away from the southern boundary of supernova remnant Kes 79. The spin-down rate of 3XMM J185246.6+003317 is $<1.1\times 10^{-13}$ s s$^{-1}$, which, together with the long period P=11.558714(2) s, indicates a dipolar surface magnetic field of $<3.6\times 10^{-13}$ G, a characteristic age of $>1.7$ Myr, and a spin-down luminosity of $<2.8\times 10^{30}$ erg s$^{-1}$. The X-ray spectrum of the source is best-fitted with a resonant Compton scattering model, and can be also adequately described by a blackbody model. The observations covering a seven month span from 2008 to 2009 show variations in the spectral properties of the source, with the luminosity decreasing from $2.7\times 10^{34}$ erg s$^{-1}$ to $4.6 \times 10^{33}$ erg s$^{-1}$, along with a decrease of the blackbody temperature from $kT\approx 0.8$ keV to $\approx0.6$ keV. The X-ray luminosity of the source is higher than its spin-down luminosity, ruling out rotation as a power source. The combined timing and spectral properties, the non-detection of any optical or infrared counterpart, together with the lack of detection of the source in archival X-ray data prior to the 2008 XMM-Newton observation, point to this source being a newly discovered transient low-B magnetar undergoing an outburst decay during the XMM-Newton observations. The non-detection by Chandra in 2001 sets an upper limit $4\times 10^{32}$ erg s$^{-1}$ to the quiescent luminosity of 3XMM J185246.6+003317. Its period is the longest among currently known transient magnetars. The foreground absorption toward 3XMM J185246.6+003317 is similar to that of Kes 79, suggesting a similar distance of $\sim$7.1 kpc.

preprint2014arXiv

Finding representative sets of optimizations for adaptive multiversioning applications

Iterative compilation is a widely adopted technique to optimize programs for different constraints such as performance, code size and power consumption in rapidly evolving hardware and software environments. However, in case of statically compiled programs, it is often restricted to optimizations for a specific dataset and may not be applicable to applications that exhibit different run-time behavior across program phases, multiple datasets or when executed in heterogeneous, reconfigurable and virtual environments. Several frameworks have been recently introduced to tackle these problems and enable run-time optimization and adaptation for statically compiled programs based on static function multiversioning and monitoring of online program behavior. In this article, we present a novel technique to select a minimal set of representative optimization variants (function versions) for such frameworks while avoiding performance loss across available datasets and code-size explosion. We developed a novel mapping mechanism using popular decision tree or rule induction based machine learning techniques to rapidly select best code versions at run-time based on dataset features and minimize selection overhead. These techniques enable creation of self-tuning static binaries or libraries adaptable to changing behavior and environments at run-time using staged compilation that do not require complex recompilation frameworks while effectively outperforming traditional single-version non-adaptable code.

preprint2014arXiv

Hypergeometric Functions of Matrix Arguments and Linear Statistics of Multi-Spiked Hermitian Matrix Models

This paper derives central limit theorems (CLTs) for general linear spectral statistics (LSS) of three important multi-spiked Hermitian random matrix ensembles. The first is the most common spiked scenario, proposed by Johnstone, which is a central Wishart ensemble with fixed-rank perturbation of the identity matrix, the second is a non-central Wishart ensemble with fixed-rank noncentrality parameter, and the third is a similarly defined non-central $F$ ensemble. These CLT results generalize our recent work to account for multiple spikes, which is the most common scenario met in practice. The generalization is non-trivial, as it now requires dealing with hypergeometric functions of matrix arguments. To facilitate our analysis, for a broad class of such functions, we first generalize a recent result of Onatski to present new contour integral representations, which are particularly suitable for computing large-dimensional properties of spiked matrix ensembles. Armed with such representations, our CLT formulas are derived for each of the three spiked models of interest by employing the Coulomb fluid method from random matrix theory along with saddlepoint techniques. We find that for each matrix model, and for general LSS, the individual spikes contribute additively to yield a $O(1)$ correction term to the asymptotic mean of the linear statistic, which we specify explicitly, whilst having no effect on the leading order terms of the mean or variance.

preprint2014arXiv

Improving PARSEC models for very low mass stars

Many stellar models present difficulties in reproducing basic observational relations of very low mass stars (VLMS), including the mass--radius relation and the optical colour--magnitudes of cool dwarfs. Here, we improve PARSEC models on these points. We implement the T--tau relations from PHOENIX BT-Settl model atmospheres as the outer boundary conditions in the PARSEC code, finding that this change alone reduces the discrepancy in the mass--radius relation from 8 to 5 per cent. We compare the models with multi--band photometry of clusters Praesepe and M67, showing that the use of T--tau relations clearly improves the description of the optical colours and magnitudes. But anyway, using both Kurucz and PHOENIX model spectra, model colours are still systematically fainter and bluer than the observations. We then apply a shift to the above T--tau relations, increasing from 0 at T_eff = 4730 K to ~14% at T_eff = 3160 K, to reproduce the observed mass--radius radius relation of dwarf stars. Taking this experiment as a calibration of the T--tau relations, we can reproduce the optical and near infrared CMDs of low mass stars in the old metal--poor globular clusters NGC6397 and 47Tuc, and in the intermediate--age and young solar--metallicity open clusters M67 and Praesepe. Thus, we extend PARSEC models using this calibration, providing VLMS models more suitable for the lower main sequence stars over a wide range of metallicities and wavelengths. Both sets of models are available on PARSEC webpage.

preprint2014arXiv

Interaction Between Supernova Remnant G22.7-0.2 And The Ambient Molecular Clouds

We have carried out 12CO (J=1-0 and 2-1), 13CO (J=1-0), and C18O (J=1-0) observations in the direction of the supernova remnant (SNR) G22.7-0.2. A filamentary molecular gas structure, which is likely part of a larger molecular complex with VLSR~75-79 km/s, is detected and is found to surround the southern boundary of the remnant. In particular, the high-velocity wing (77-110 km/s) in the 12CO (J=1-0 and J=2-1) emission shows convincing evidence of the interaction between SNR G22.7-0.2 and the 75-79 km/s molecular clouds (MCs). Spectra with redshifted profiles, a signature of shocked molecular gas, are seen in the southeastern boundary of the remnant. The association between the remnant and the 77 km/s MCs places the remnant at the near distance of 4.0-4.8 kpc, which agrees with a location on the Scutum-Crux arm. We suggest that SNR G22.7-0.2, SNR W41, and HII region G022.760-0.485 are at the same distance and are associated with GMC G23.0-0.4.

preprint2014arXiv

Molecular Environment of the Supernova Remnant IC 443: Discovery of the Molecular Shells Surrounding the Remnant

We have carried out 12CO, 13CO, and C18O observations toward the mixed morphology supernova remnant (SNR) IC 443. The observations cover a 1.5*1.5 deg^2 area and allow us to investigate the overall molecular environment of the remnant. Some northern and northeastern partial shell structure of CO gas is around the remnant. One of the partial shells, about 5' extending beyond the northeastern border of the remnant's bright radio shell, seems to just confine the faint radio halo. On the other hand, some faint CO clumps can be discerned along the eastern boundary of the faint remnant's radio halo. Connecting the eastern CO clumps, the northeastern partial shell structures, and the northern CO partial shell, we can see that a half molecular ring structure appears to surround the remnant. The LSR velocity of the half-ring structure is in the range of -5 km/s to -2 km/s, which is consistent with that of the -4 km/s molecular clouds. We suggest that the half-ring structure of the CO emission at V_LSR -4 km/s is associated with the SNR. The structures are possibly swept up by the stellar winds of SNR IC 443's massive progenitor. Based on the Wide-field Infrared Survey Explorer and the Two Micron All Sky Survey near-IR database, 62 young stellar object (YSO) candidates are selected within the radio halo of the remnant. These YSO candidates concentrated along the boundary of the remnant's bright radio shell are likely to be triggered by the stellar winds from the massive progenitor of SNR IC 443.

preprint2014arXiv

Morphology and structure of extremely red objects at $z\sim1$ in the CANDELS-COSMOS field

Using high-resolution HST/Wide Field Camera 3 F125W imaging from the CANDELS-COSMOS field, we report the the structural and morphological properties of Extremely Red Objects (EROs) at $z\sim1$. Based on the UVJ color criteria, we separate EROs into two types: old passive galaxies (OGs) and dusty star-forming galaxies (DGs). For a given stellar mass, we find that the mean size of OGs (DGs) is smaller by a factor of $\sim2$ (1.5) than that of present-day early-type (late-type) galaxies at rest-frame optical wavelength. We derive the average effective radii of OGs and DGs, corresponding to $2.09\pm1.13$ kpc and $3.27\pm1.14$ kpc, respectively. Generally, The DGs are heterogeneous, with mixed features including bulges, disks, and irregular structures, with relatively high $M_{\rm 20}$, small size and low $G$, while OGs are elliptical-like compact morphologies with lower $M_{\rm 20}$, larger size and higher $G$, indicating the more concentrated and symmetric spatial extent of stellar population distribution in OGs than DGs. The findings imply that OGs and DGs have different evolutionary processes, and the minor merger scenario is the most likely mechanism for the structural properties of OGs. However, the size evolution of DGs is possibly due to the secular evolution of galaxies.

preprint2014arXiv

Perturbed Laguerre Unitary Ensembles, Painlevé V and Information Theory

In this review, we investigate a key information-theoretic performance metric in multiple-antenna wireless communications, the so-called outage probability. This quantity may be expressed in terms of a moment generating function, for which we present two separate integral representations, one involving a particular $σ$-form of Painlevé V. We also present a representation involving a non-linear second order difference equation.

preprint2014arXiv

Physical Nature of the [S II]-Bright Shell Nebulae N70 and N185

N70 and N185 are two large ($\ge$100 pc in diameter) shell nebulae in the Large Magellanic Cloud (LMC). Their high [\ion{S}{2}]/H$α$ ratios rival those of supernova remnants (SNRs), but they are not confirmed as SNRs. To study their physical nature, we have obtained \emph{XMM-Newton} X-ray observations and high-dispersion long-slit echelle spectroscopic observations of these two nebulae. The X-ray spectra of both nebulae can be well interpreted with an optically thin thermal ($\sim$0.2 keV) plasma with the average LMC abundance in a collisional ionization equilibrium. N70 encompasses the OB association LH114. Although N70 has a modest expansion velocity and essentially thermal radio emission, its diffuse X-ray luminosity ($\sim6.1\times10^{35}$ erg s$^{-1}$) is higher than that from a quiescent superbubble with N70's density, size, and expansion velocity; thus, N70 is most likely a superbubble that is recently energized by an interior SNR. N185 does not contain any known OB association, and its X-ray luminosity is an order of magnitude lower than expected if it is a quiescent superbubble. N185 has nonthermal radio emission and has high-velocity material expanding at nearly 200 km s$^{-1}$, similar to many known SNRs in the LMC. Its X-ray luminosity ($\sim1.9\times10^{35}$ erg s$^{-1}$) is also consistent with that of an evolved SNR. We therefore suggest that N185 is energized by a recent supernova.

preprint2014arXiv

Selection and Mid-infrared Spectroscopy of Ultraluminous Star-Forming Galaxies at z~2

Starting from a sample of 24 \micron\ sources in the Extended Groth Strip, we use 3.6 to 8 \micron\ color criteria to select ultraluminous infrared galaxies (ULIRGs) at $z\sim2$. Spectroscopy from 20-38 \micron\ of 14 objects verifies their nature and gives their redshifts. Multi-wavelength data for these objects imply stellar masses ${>}10^{11}$ \Msun\ and star formation rates $\ge$410 \Msun yr$^{-1}$. Four objects of this sample observed at 1.6 \micron\ (rest-frame visible) with {\it HST}/WFC3 show diverse morphologies, suggesting that multiple formation processes create ULIRGs. Four of the 14 objects show signs of active galactic nuclei, but the luminosity appears to be dominated by star formation in all cases.

preprint2014arXiv

Structure and morphology of X-ray selected AGN hosts at 1<z<3 in CANDELS-COSMOS field

We analyze morphologies of the host galaxies of 35 X-ray selected active galactic nucleus (AGNs) at $z\sim2$ in the Cosmic Evolution Survey (COSMOS) field using Hubble Space Telescope/WFC3 imaging taken from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). We build a control sample of 350 galaxies in total, by selecting ten non-active galaxies drawn from the same field with the similar stellar mass and redshift for each AGN host. By performing two dimensional fitting with GALFIT on the surface brightness profile, we find that the distribution of S$è$rsic index (n) of AGN hosts does not show a statistical difference from that of the control sample. We measure the nonparametric morphological parameters (the asymmetry index A, the Gini coefficient G, the concentration index C and the M20 index) based on point source subtracted images. All the distributions of these morphological parameters of AGN hosts are consistent with those of the control sample. We finally investigate the fraction of distorted morphologies in both samples by visual classification. Only $\sim$15% of the AGN hosts have highly distorted morphologies, possibly due to a major merger or interaction. We find there is no significant difference in the distortion fractions between the AGN host sample and control sample. We conclude that the morphologies of X-ray selected AGN hosts are similar to those of nonactive galaxies and most AGN activity is not triggered by major merger.

preprint2014arXiv

Ultraslow Optical Solitons and Their Storage and Retrieval in an Ultracold Ladder-Type Atomic System

We propose a scheme to obtain stable nonlinear optical pulses and realize their storage and retrieval in an ultracold ladder-type three-level atomic gas via electromagnetically induced transparency. Based on Maxwell-Bloch equations we derive a nonlinear equation governing the evolution of probe field envelope, and show that optical solitons with ultraslow propagating velocity and extremely low generation power can be created in the system. Furthermore, we demonstrate that such ultraslow optical solitons can be stored and retrieved by switching off and on a control field. Due to the balance between dispersion and nonlinearity, the ultraslow optical solitons are robust during propagation, and hence their storage and retrieval are more desirable than that of linear optical pulses. This raises the possibility of realizing the storage and retrieval of light and quantum information by using solitonic pulses.

preprint2013arXiv

Linear relation for wind-blown bubble sizes of main-sequence OB stars in a molecular environment and implication for supernova progenitors

We find a linear relationship between the size of a massive star's main-sequence bubble in a molecular environment and the star's initial mass: R_b \approx 1.22M/Msun - 9.16 pc, assuming a constant interclump pressure. Since stars in the mass range of 8 to 25-30 Msun will end their evolution in the red supergiant phase without launching a Wolf-Rayet wind, the main-sequence wind-blown bubbles are mainly responsible for the extent of molecular gas cavities, while the effect of the photoionization is comparatively small. This linear relation can thus be used to infer the masses of the massive star progenitors of supernova remnants (SNRs) that are discovered to evolve in molecular cavities, while few other means are available for inferring properties of SNR progenitors. We have used this method to estimate the initial masses of the progenitors of eight SNRs: Kes 69, Kes 75, Kes 78, 3C 396, 3C 397, HC 40, Vela, and RX J1713-3946.

preprint2013arXiv

Low ionization lines in high luminosity quasars: The calcium triplet

In order to investigate where and how low ionization lines are emitted in quasars we are studying a new collection of spectra of the CaII triplet at $λ$8498, $λ$8542, $λ$8662 observed with the Very Large Telescope (VLT) using the Infrared Spectrometer And Array Camera (ISAAC). Our sample involves luminous quasars at intermediate redshift for which CaII observations are almost nonexistent. We fit the CaII triplet and the OI $λ$8446 line using the H$β$ profile as a model. We derive constraints on the line emitting region from the relative strength of the CaII triplet, OI $λ$8446 and H$β$.

preprint2013arXiv

Moduli space of supersymmetric QCD in the Veneziano limit

We study the moduli space of 4d N=1 supersymmetric QCD in the Veneziano limit using Hilbert series. In this limit, the numbers of colours and flavours are taken to be large with their ratio fixed. It is shown that the Hilbert series, which is a partition function of an ensemble of gauge invariant quantities parametrising the moduli space, can also be realised as a partition function of a system of interacting Coulomb gas in two dimensions. In the electrostatic equilibrium, exact and asymptotic analyses reveal that such a system exhibits two possible phases. Physical quantities, such as charge densities, free energies, and Hilbert series, associated with each phase, are computed explicitly and discussed in detail. We then demonstrate the existence of the third order phase transition in this system.

preprint2013arXiv

Molecular Environments of SNRs

There are about 70 Galactic supernova remnants (SNRs) that are now confirmed or suggested to be in physical contact with molecular clouds (MCs) with six kinds of evidence of multiwavelength observations. Recent detailed CO-line spectroscopic mappings of a series of SNRs reveal them to be in cavities of molecular gas, implying the roles the progenitors may have played. We predict a linear correlation between the wind bubble sizes of main-sequence OB stars in a molecular environment and the stellar masses and discuss its implication for supernova progenitors. The molecular environments of SNRs can serve as a good probe for the gamma-rays arising from the hadronic interaction of the accelerated protons, and this paper also discusses the gamma-ray emission from MCs illuminated by diffusive protons that escape from SNR shocks.

preprint2013arXiv

On the Distribution of MIMO Mutual Information: An In-Depth Painlevé Based Characterization

This paper builds upon our recent work which computed the moment generating function of the MIMO mutual information exactly in terms of a Painlevé V differential equation. By exploiting this key analytical tool, we provide an in-depth characterization of the mutual information distribution for sufficiently large (but finite) antenna numbers. In particular, we derive systematic closed-form expansions for the high order cumulants. These results yield considerable new insight, such as providing a technical explanation as to why the well known Gaussian approximation is quite robust to large SNR for the case of unequal antenna arrays, whilst it deviates strongly for equal antenna arrays. In addition, by drawing upon our high order cumulant expansions, we employ the Edgeworth expansion technique to propose a refined Gaussian approximation which is shown to give a very accurate closed-form characterization of the mutual information distribution, both around the mean and for moderate deviations into the tails (where the Gaussian approximation fails remarkably). For stronger deviations where the Edgeworth expansion becomes unwieldy, we employ the saddle point method and asymptotic integration tools to establish new analytical characterizations which are shown to be very simple and accurate. Based on these results we also recover key well established properties of the tail distribution, including the diversity-multiplexing-tradeoff.

preprint2013arXiv

Random Matrix Models, Double-Time Painlevé Equations, and Wireless Relaying

This paper gives an in-depth study of a multiple-antenna wireless communication scenario in which a weak signal received at an intermediate relay station is amplified and then forwarded to the final destination. The key quantity determining system performance is the statistical properties of the signal-to-noise ratio (SNR) γ at the destination. Under certain assumptions on the encoding structure, recent work has characterized the SNR distribution through its moment generating function, in terms of a certain Hankel determinant generated via a deformed Laguerre weight. Here, we employ two different methods to describe the Hankel determinant. First, we make use of ladder operators satisfied by orthogonal polynomials to give an exact characterization in terms of a "double-time" Painlevé differential equation, which reduces to Painlevé V under certain limits. Second, we employ Dyson's Coulomb Fluid method to derive a closed form approximation for the Hankel determinant. The two characterizations are used to derive closed-form expressions for the cumulants of γ, and to compute performance quantities of engineering interest.

preprint2013arXiv

The likely Fermi Detection of the Supernova Remnant RCW 103

We report on the results from our $γ$-ray analysis of the supernova remnant (SNR) RCW 103 region. The data were taken with the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. An extended source is found at a position consistent with that of RCW 103, and its emission was only detected above 1 GeV (10$σ$ significance), having a power-law spectrum with a photon index of 2.0$\pm$0.1. We obtain its 1--300 GeV spectrum, and the total flux gives a luminosity of 8.3$\times 10^{33}$ erg s$^{-1}$ at a source distance of 3.3 kpc. Given the positional coincidence and property similarities of this source with other SNRs, we identify it as the likely Fermi $γ$-ray counterpart to RCW 103. Including radio measurements of RCW 103, the spectral energy distribution (SED) is modeled by considering emission mechanisms based on both hadronic and leptonic scenarios. We find that models in the two scenarios can reproduce the observed SED, while in the hadronic scenario the existence of SNR--molecular-cloud interaction is suggested as a high density of the target protons is required.

preprint2013arXiv

The Mid-Infrared Extinction Law and its Variation in the Coalsack Nebula

In recent years the wavelength dependence of interstellar extinction from the ultraviolet (UV), optical, through the near- and mid-infrared (IR) has been studied extensively. Although it is well established that the UV/optical extinction law varies significantly among the different lines of sight, it is not clear how the IR extinction varies among various environments. In this work, using the color-excess method and taking red giants as the extinction tracer, we determine the interstellar extinction Alambda in the four Spitzer/IRAC bands of the Coalsack nebula, a nearby starless dark cloud, based on the data obtained from the 2MASS and Spitzer/GLIMPSE surveys. We select five individual regions across the nebula that span a wide variety of physical conditions, ranging from diffuse, translucent to dense environments, as traced by the visual extinction, the Spitzer/MIPS 24micron emission, and CO emission. We find that Alambda/AKs, the mid-IR extinction relative to AKs, decreases from diffuse to dense environments, which may be explained in terms of ineffective dust growth in dense regions. The mean extinction (relative to AKs) is calculated for the four IRAC bands as well, which exhibits a flat mid-IR extinction law, consistent with previous determinations for other regions. The extinction in the IRAC 4.5micron band is anomalously high, much higher than that of the other three IRAC bands. It cannot be explained in terms of CO and CO2 ices. The mid-IR extinction in the four IRAC bands have also been derived for four representative regions in the Coalsack Globule 2 which respectively exhibit strong ice absorption, moderate or weak ice absorption, and very weak or no ice absorption. The derived mid-IR extinction curves are all flat, with Alambda/AKs increasing with the decrease of the H2O ice absorption optical depth.

preprint2013arXiv

The structure of massive quiescent galaxies at z~3 in the CANDELS-COSMOS field

In this letter, we use a two-color (J-L) vs. (V-J) selection criteria to search massive, quiescent galaxy candidates at 2.5<z<4.0 in the CANDELS-COSMOS field. We construct a H-selected catalogue and complement it with public auxiliary data. We finally obtain 19 passive VJL-selected (hereafter pVJL) galaxies as the possible massive quiescent galaxy candidates at z~3 by several constrains. We find the sizes of our pVJL galaxies are on average 3-4 times smaller than those of local ETGs with analogous stellar mass. The compact size of these z~3 galaxies can be modelled by assuming their formation at z ~ 4-6 according to the dissipative collapse of baryons. Up to z<4, the mass-normalized size evolution can be described by $r_e\propto (1+z)^{-1.0}$. Low Sersic index and axis ratio, with median values n~1.5 and b/a~0.65 respectively, indicate most of pVJL galaxies are disk-dominated. Despite large uncertainty, the inner region of the median mass profile of our pVJL galaxies is similar to those of quiescent galaxies (QGs) at 0.5<z<2.5 and local Early-type galaxies (ETGs). It indicates local massive ETGs have been formed according to an inside-out scenario: the compact galaxies at high redshift make up the cores of local massive ETGs and then build up the outskirts according to dissipationless minor mergers.

preprint2012arXiv

Distributions of Demmel and Related Condition Numbers

Consider a random matrix $\mathbf{A}\in\mathbb{C}^{m\times n}$ ($m \geq n$) containing independent complex Gaussian entries with zero mean and unit variance, and let $0<λ_1\leq λ_{2}\leq ...\leq λ_n<\infty$ denote the eigenvalues of $\mathbf{A}^{*}\mathbf{A}$ where $(\cdot)^*$ represents conjugate-transpose. This paper investigates the distribution of the random variables $\frac{\sum_{j=1}^n λ_j}{λ_k}$, for $k = 1$ and $k = 2$. These two variables are related to certain condition number metrics, including the so-called Demmel condition number, which have been shown to arise in a variety of applications. For both cases, we derive new exact expressions for the probability densities, and establish the asymptotic behavior as the matrix dimensions grow large. In particular, it is shown that as $n$ and $m$ tend to infinity with their difference fixed, both densities scale on the order of $n^3$. After suitable transformations, we establish exact expressions for the asymptotic densities, obtaining simple closed-form expressions in some cases. Our results generalize the work of Edelman on the Demmel condition number for the case $m = n$.

preprint2012arXiv

Giant H II Regions in M101. I. X-ray Analysis of Hot Gas

We performed a Chandra X-ray study of three giant H II regions (GHRs), NGC 5461, NGC 5462, and NGC 5471, in the spiral galaxy M101. The X-ray spectra of the three GHRs all contain a prominent thermal component with a temperature of ~0.2 keV. In NGC 5461, the spatial distribution of the soft (< 1.5 keV) X-ray emission is generally in agreement with the extent of H1105, the most luminous H II region therein, but extends beyond its southern boundary, which could be attributed to outflows from the star cloud between H1105 and H1098. In NGC 5462, the X-ray emission is displaced from the H II regions and a ridge of blue stars; the H-alpha filaments extending from the ridge of star cloud to the diffuse X-rays suggest that hot gas outflows have occurred. The X-rays from NGC 5471 are concentrated at the B-knot, a "hypernova remnant" candidate. Assuming a Sedov-Taylor evolution, the derived explosion energy, on the order of 10^52 ergs, is consistent with a hypernova origin. In addition, a bright source in the field of NGC 5462 has been identified as a background AGN, instead of a black hole X-ray binary in M101.

preprint2012arXiv

Global Gyrokinetic Simulation of Tokamak Edge Pedestal Instabilities

Global electromagnetic gyrokinetic simulations show the existence of near threshold conditions for both a high-$n$ kinetic ballooning mode (KBM) and an intermediate-$n$ kinetic version of peeling-ballooning mode (KPBM) in the edge pedestal of two DIII-D H-mode discharges. When the magnetic shear is reduced in a narrow region of steep pressure gradient, the KPBM is significantly stabilized, while the KBM is weakly destabilized and hence becomes the most-unstable mode. Collisions decrease the KBM's critical $β$ and increase the growth rate.

preprint2012arXiv

Large Size Scatter of Passively Evolving Lensed Galaxies at z~2 in CLASH

In a systematic search over 11 cluster fields from Cluster Lensing And Supernova survey with Hubble (CLASH) we identify ten passively evolving massive galaxies at redshift z~2.We derive the stellar properties of these galaxies using HST WFC3/ACS multiband data, together with Spitzer IRAC observations. We also deduce the optical rest-frame effective radius of these high redshift objects. The derived stellar masses and measured effective radii have been corrected by the lensing magnification factors, which are estimated by simply adopting the spherical NFW model for the foreground cluster lens. The observed near-IR images, obtained by HST WFC3 camera with high spatial resolution and lensed by the foreground clusters, enable us to study the structures of such systems. Nine out of ten galaxies have on average three times smaller effective radius than local ETGs of similar stellar masses, in agreement with previous works at redshift 1.5 < z < 2.5. Combined with literature data for z~2, we find that the mass-normalized effective radius scales with redshift as re/M^0.56 \propto (1 + z)^{-1.13}. We confirm that their size distribution shows a large scatter: from normal size to ~5 times smaller compared to local ETGs with similar stellar masses. The 1-σ scatter σ_{logre} of the size distribution is 0.22 and 0.34 at z~1.6 and z~2.1,respectively.The observed large size scatter has to be carefully taken into account in galaxy evolution model predictions.

preprint2012arXiv

On the Hadronic Gamma-ray Emission from Tycho's Supernova Remnant

Hadronic gamma-ray emission from supernova remnants (SNRs) is an important tool to test shock acceleration of cosmic ray protons. Tycho is one of nearly a dozen Galactic SNRs which are suggested to emit hadronic gamma-ray emission. Among them, however, it is the only one in which the hadronic emission is proposed to arise from the interaction with low-density (~0.3 cm^{-3}) ambient medium. Here we present an alternative hadronic explanation with a modest conversion efficiency (of order 1%) for this young remnant. With such an efficiency, a normal electron-proton ratio (of order 10^{-2}) is derived from the radio and X-ray synchrotron spectra and an average ambient density that is at least one-order-of-magnitude higher is derived from the hadronic gamma-ray flux. This result is consistent with the multi-band evidence of the presence of dense medium from the north to the east of the Tycho SNR. The SNR-cloud association, in combination with the HI absorption data, helps to constrain the so-far controversial distance to Tycho and leads to an estimate of 2.5 kpc.

preprint2012arXiv

Passive and star-forming galaxies at $1.4 \leq z \leq2.5$ in the Aegis field

Using a simple two-color selection based on $g$-, $z$-, and $K$-band photometry, we pick out 1609 star-forming galaxies (sgzKs) and 422 passively evolving galaxies (pgzKs) at z\sim2$ from a $K$-band-selected sample ($K_{\rm AB} < 22.0$) in an area of $\sim 0.44$ deg$^{2}$ of the All-wavelength Extended Groth Strip International Survey. The number counts of pgzKs\ in our sample turn over at $K_{\rm AB} \sim 21.0$, and both the number of faint and bright objects (including sgzKs\ and pgzKs) exceed the predictions of a recent semi-analytic model of galaxy formation, a more successful model is need to explain this diversity. We also find that the star formation rate (SFR) and specific SFR (sSFR) of sgzKs\ increases with redshift at all masses, implying that star-forming galaxies were much more active on average in the past. Moreover, the sSFR of massive galaxies is lower at all redshifts, suggesting that star formation contributes more to the mass growth of low-mass galaxies than to high-mass galaxies. From {\it Hubble Space Telescope} Wide Field Camera 3 near-infrared imaging data, we find that morphologies of $z\sim2$ galaxies not only have diffuse structures with lower $G$ and higher $M_{20}$ values, but also have single-object morphologies (higher $G$ and lower $M_{20}$), implying that there are morphological variety and different formation process for these galaxies at $z\sim2$. Finally, we also study the fraction of active galactic nuclei (AGNs) in the gzKs, 82 of 828 gzKs\ with four IRAC bands can be classified as AGNs ($\sim$ 10%). Most of these AGN candidates have $L_{\rm 0.5-10\ keV}>10^{41}\,\rm erg\,s^{-1}$.

preprint2012arXiv

Star Formation Rate Indicators in Wide-Field Infrared Survey Preliminary Release

With the goal of investigating the degree to which theMIR luminosity in theWidefield Infrared Survey Explorer (WISE) traces the SFR, we analyze 3.4, 4.6, 12 and 22 μm data in a sample of » 140,000 star-forming galaxies or star-forming regions covering a wide range in metallicity 7.66 < 12 + log(O/H) < 9.46, with redshift z < 0.4. These star-forming galaxies or star-forming regions are selected by matching the WISE Preliminary Release Catalog with the star-forming galaxy Catalog in SDSS DR8 provided by JHU/MPA 1.We study the relationship between the luminosity at 3.4, 4.6, 12 and 22 μm from WISE and Hαluminosity in SDSS DR8. From these comparisons, we derive reference SFR indicators for use in our analysis. Linear correlations between SFR and the 3.4, 4.6, 12 and 22 μm luminosity are found, and calibrations of SFRs based on L(3.4), L(4.6), L(12) and L(22) are proposed. The calibrations hold for galaxies with verified spectral observations. The dispersion in the relation between 3.4, 4.6, 12 and 22 μm luminosity and SFR relates to the galaxy's properties, such as 4000 °A break and galaxy color.

preprint2011arXiv

Capturing Near Earth Objects

Recently, Near Earth Objects (NEOs) have been attracting great attention, and thousands of NEOs have been found to date. This paper examines the NEOs' orbital dynamics using the framework of an accurate solar system model and a Sun-Earth-NEO three-body system when the NEOs are close to Earth to search for NEOs with low-energy orbits. It is possible for such an NEO to be temporarily captured by Earth; its orbit would thereby be changed and it would become an Earth-orbiting object after a small increase in its velocity. From the point of view of the Sun-Earth-NEO restricted three-body system, it is possible for an NEO whose Jacobian constant is slightly lower than C1 and higher than C3 to be temporarily captured by Earth. When such an NEO approaches Earth, it is possible to change its orbit energy to close up the zero velocity surface of the three-body system at point L1 and make the NEO become a small satellite of the Earth. Some such NEOs were found; the best example only required a 410m/s increase in velocity.

preprint2011arXiv

Cosmic rays in the surroundings of SNR G35.6-0.4

HESS J1858+020 is a TeV gamma-ray source that was reported not to have any clear cataloged counterpart at any wavelength. However, it has been recently proposed that this source is indirectly associated with the radio source, re-identified as a supernova remnant (SNR), G35.6-0.4. The latter is found to be middle-aged ($\sim 30$ kyr) and to have nearby molecular clouds (MCs). HESS J1858+020 was proposed to be the result of the interaction of protons accelerated in the SNR shell with target ions residing in the clouds. The Fermi Large Area Telescope (LAT) First Source Catalog does not list any source coincident with the position of HESS J1858+020, but some lie close. Here, we analyse more than 2 years of data obtained with the Fermi-LAT for the region of interest, and consider whether it is indeed possible that the closest LAT source, 1FGL J1857.1+0212c, is related to HESS J1858+020. We conclude it is not, and we impose upper limits on the GeV emission originating from HESS J1858+020. Using a simplified 3D model for the cosmic-ray propagation out from the shell of the SNR, we consider whether the interaction between SNR G35.6-0.4 and the MCs nearby could give rise to the TeV emission of HESS J1858+020 without producing a GeV counterpart. If so, the pair of SNR/TeV source with no GeV detection would be reminiscent of other similarly-aged SNRs, such as some of the TeV hotspots near W28, for which cosmic-ray diffusion may be used to explain their multi-frequency phenomenology. However, for HESS J1858+020, we found that although the phase space in principle allows for such GeV--TeV non-correlation to appear, usual and/or observationally constrained values of the parameters (e.g., diffusion coefficients and cloud-SNR likely distances) would disfavor it.

preprint2011arXiv

Derivation of the Electron Distribution in SNR RX J1713.7-3946 via a Spectral Inversion Method

We show that the radio, X-ray and gamma-ray spectrum of the supernova remnant RX J1713.7-3946 can be accounted for with the simplest emission model, where all of these emissions are attributed to a population of relativistic electrons interacting with the cosmic microwave background radiation, IR interstellar photons, and a background magnetic field. With a spectral inversion method (Johns & Lin 1992), the parent electron distribution and its uncertainties are derived from the observed photon spectrum. These results are independent on the model of particle acceleration and strongly support the leptonic scenario for the TeV emission.

preprint2011arXiv

Dynamic S0 Galaxies II: the Role of Diffuse Hot Gas

Gas loss is thought to be important in SF quenching and morphological transition during the evolution of S0 galaxies. In high density environments, gas loss can be achieved via many external mechanisms. However, in relatively isolated environments, where these external mechanisms cannot be efficient, gas loss must be dominated by some internal processes. We perform Chandra analysis of hot gas in five nearby isolated S0 galaxies, based on quantitative subtraction of various stellar contributions. We find that all the galaxies studied in the present work are X-ray faint, with the hot gas luminosity LX<5% of the expected Ia SN energy injection rate. We further compare our results with those from relevant recent papers, in order to investigate the energy budget, cold-hot gas relation, and gas removal from S0 galaxies in isolated environments. We find that elliptical and S0 galaxies are not significantly different in LX at the low mass end (typically with LK<1e11Lsun). However, at the high mass end, S0 galaxies tend to have significantly lower LX than elliptical galaxies of the same stellar masses. We further discuss the potential relation of the diffuse X-ray emission with the cold gas content in S0 and elliptical galaxies. We find that LX/LK^2 tends to correlate positively with the total cold gas mass M(H2+HI) for gas-poor galaxies with M(H2+HI)<1e8Msun, while they anti-correlate with each other for gas-rich ones. This cold-hot gas relation can be explained in a scenario of galaxy evolution, with the leftover cold gas from the precursor star forming galaxy mainly removed by the long-lasting Ia SN feedback. The two different trends for gas-rich and -poor galaxies may be the results of the initial fast decreasing SN rate and the later fast decreasing mass-loading to hot gas, respectively.

preprint2011arXiv

Gamma-rays from molecular clouds illuminated by accumulated diffusive protons. II: interacting supernova remnants

Recent observations reveal that spectral breaks at ~GeV are commonly present in Galactic gamma-ray supernova remnants (SNRs) interacting with molecular clouds and that most of them have a spectral ($E^2dF/dE$) "platform" extended from the break to lower energies. In paper I (Li & Chen 2010), we developed an accumulative diffusion model by considering an accumulation of the diffusive protons escaping from the shock front throughout the history of the SNR expansion. In this paper, we improve the model by incorporating finite-volume of MCs, demonstrate the model dependence on particle diffusion parameters and cloud size, and apply it to nine interacting SNRs (W28, W41, W44, W49B, W51C, Cygnus Loop, IC443, CTB 37A, and G349.7+0.2). This refined model naturally explains the GeV spectral breaks and, especially, the "platform"s, together with available TeV data. We find that the index of the diffusion coeffcient δ is in the range of 0.5-0.7, similar to the galactic averaged value, and the diffusion coefficient for cosmic rays around the SNRs is essentially two orders of magnitude lower than the Galactic average, which is a good indication for the suppression of cosmic ray diffusion near SNRs.

preprint2011arXiv

Molecular Environment and an X-ray Spectroscopy of Supernova Remnant Kesteven 78

We investigate the molecular environment of the Galactic supernova remnant (SNR) Kesteven 78 and perform an XMM-Newton X-ray spectroscopic study for the northeastern edge of the remnant. SNR Kes78 is found to interact with the molecular clouds (MCs) at a systemic local standard of rest velocity of 81km/s. At around this velocity, the SNR appears to contact a long molecular strip in the northeast and a large cloud in the east as revealed in the 13CO line, which may be responsible for the radio brightness peak and the OH maser, respectively. The 12CO-line bright region morphologically matches the eastern bright radio shell in general, and the SNR is consistent in extent with a CO cavity. Broadened 12CO line profiles discerned in the eastern maser region and the western clumpy molecular arc and the elevated 12CO J=2-1/J=1-0 ratios along the SNR boundary may be signatures of shock perturbation in the molecular gas. The SNR-MC association places the SNR at a kinematic distance of 4.8 kpc. The X-rays arising from the northeastern radio shell are emitted by underionized hot (~1.5 keV), low-density (~0.1 cm^{-3}) plasma with solar abundance, and the plasma may be of intercloud origin. The age of the remnant is inferred to be about 6 kyr. The size of the molecular cavity in Kes78 implies an initial mass around 22Msun for the progenitor.

preprint2011arXiv

PDEs satisfied by extreme eigenvalues distributions of GUE and LUE

In this paper we study, $\textsf{Prob}(n,a,b),$ the probability that all the eigenvalues of finite $n$ unitary ensembles lie in the interval $(a,b)$. This is identical to the probability that the largest eigenvalue is less than $b$ and the smallest eigenvalue is greater than $a$. It is shown that a quantity allied to $\textsf{Prob}(n,a,b)$, namely, $$ H_n(a,b):=\left[\frac{\partial}{\partial a}+\frac{\partial}{\partial b}\right]\ln\textsf{Prob}(n,a,b),$$ in the Gaussian Unitary Ensemble (GUE) and $$ H_n(a,b):=\left[a\frac{\partial}{\partial a}+b\frac{\partial}{\partial b}\right]\ln \textsf{Prob}(n,a,b),$$ in the Laguerre Unitary Ensemble (LUE) satisfy certain nonlinear partial differential equations for fixed $n$, interpreting $H_n(a,b)$ as a function of $a$ and $b$. These partial differential equations maybe considered as two variable generalizations of a Painlevé IV and a Painlevé V system, respectively. As an application of our result, we give an analytic proof that the extreme eigenvalues of the GUE and the LUE, when suitably centered and scaled, are asymptotically independent.

preprint2011arXiv

The Hilbert series of N=1 SO(N_c) and Sp(N_c) SQCD, Painlevé VI and Integrable Systems

We present a novel approach for computing the Hilbert series of 4d N=1 supersymmetric QCD with SO(N_c) and Sp(N_c) gauge groups. It is shown that such Hilbert series can be recast in terms of determinants of Hankel matrices. With the aid of results from random matrix theory, such Hankel determinants can be evaluated both exactly and asymptotically. Several new results on Hilbert series for general numbers of colours and flavours are thus obtained in this paper. We show that the Hilbert series give rise to families of rational solutions, with palindromic numerators, to the Painlevé VI equations. Due to the presence of such Painlevé equations, there exist integrable Hamiltonian systems that describe the moduli spaces of SO(N_c) and Sp(N_c) SQCD. To each system, we explicitly state the corresponding Hamiltonian and family of elliptic curves. It turns out that such elliptic curves take the same form as the Seiberg-Witten curves for 4d N=2 SU(2) gauge theory with 4 flavours.

preprint2011arXiv

The Hilbert series of U/SU SQCD and Toeplitz Determinants

We present a new technique for computing Hilbert series of N=1 supersymmetric QCD in four dimensions with unitary and special unitary gauge groups. We show that the Hilbert series of this theory can be written in terms of determinants of Toeplitz matrices. Applying related theorems from random matrix theory, we compute a number of exact Hilbert series as well as asymptotic formulae for large numbers of colours and flavours -- many of which have not been derived before.

preprint2011arXiv

Unveiling the spatial structure of the overionized plasma in the supernova remnant W49B

W49B is a mixed-morphology supernova remnant with thermal X-ray emission dominated by the ejecta. In this remnant, the presence of overionized plasma has been directly established, with information about its spatial structure. However, the physical origin of the overionized plasma in W49B has not yet been understood. We investigate this intriguing issue through a 2D hydrodynamic model that takes into account, for the first time, the mixing of ejecta with the inhomogeneous circumstellar and interstellar medium, the thermal conduction, the radiative losses from optically thin plasma, and the deviations from equilibrium of ionization induced by plasma dynamics. The model was set up on the basis of the observational results. We found that the thermal conduction plays an important role in the evolution of W49B, in- ducing the evaporation of the circumstellar ring-like cloud (whose presence has been deduced from previous observations) that mingles with the surrounding hot medium, cooling down the shocked plasma, and pushes the ejecta backwards to the center of the remnant, forming there a jet-like structure. During the evolution, a large region of overionized plasma forms within the remnant. The overionized plasma originates from the rapid cooling of the hot plasma originally heated by the shock reflected from the dense ring-like cloud. In particular, we found two different ways for the rapid cooling of plasma to appear: i) the mixing of relatively cold and dense material evaporated from the ring with the hot shocked plasma and ii) the rapid adiabatic expansion of the ejecta. The spatial distribution of the radiative recombination continuum predicted by the numerical model is in good agreement with that observed.

preprint2010arXiv

Cavity of Molecular Gas Associated with Supernova Remnant 3C 397

3C 397 is a radio and X-ray bright Galactic supernova remnant (SNR) with an unusual rectangular morphology. Our CO observation obtained with the Purple Mountain Observatory at Delingha reveals that the remnant is well confined in a cavity of molecular gas, and embedded at the edge of a molecular cloud (MC) at the local standard of rest systemic velocity of ~32 km/s. The cloud has a column density gradient increasing from southeast to northwest, perpendicular to the Galactic plane, in agreement with the elongation direction of the remnant. This systemic velocity places the cloud and SNR 3C 397 at a kinematic distance of ~10.3 kpc. The derived mean molecular density (~10-30 cm^-3) explains the high volume emission measure of the X-ray emitting gas. A 12CO line broadening of the ~32 km/s component is detected at the westmost boundary of the remnant, which provides direct evidence of the SNR-MC interaction and suggests multi-component gas there with dense (~10^4 cm^-3) molecular clumps. We confirm the previous detection of a MC at ~38 km/s to the west and south of the SNR and argue, based on HI self-absorption, that the cloud is located in the foreground of the remnant. A list of Galactic SNRs presently known and suggested to be in physical contact with environmental MCs is appended in this paper.

preprint2010arXiv

Gamma rays from molecular clouds illuminated by accumulated diffusive protons from supernova remnant W28

W28 is one of the archetype supernova remnants (SNRs) interacting with molecular clouds. H.E.S.S. observation found four TeV sources which are coincident with the molecular clouds (MCs) around W28, but Fermi LAT detected no prominent GeV counterparts for two of them. An accumulative diffusion model is established in this Letter and the energetic protons colliding the nearby MCs are considered to be an accumulation of the diffusive protons escaping from the shock front throughout the history of the SNR expansion. We have fitted the gamma ray spectra of the four sources and naturally explained the GeV spectral break of the northeastern source (source N) and the nonsignificant GeV emission of the southern sources A and C. The distances of sources A and C from the SNR centre are found to be much larger than those of sources N and B, which may be the basic reason for the faint GeV gamma rays of the two former sources.

preprint2010arXiv

Lepto-Hadronic Origin of gamma-rays from the G54.1+0.3 Pulsar Wind Nebula

G54.1+0.3 is a Crab-like pulsar wind nebula (PWN) with the highest $γ$-ray to X-ray luminosity ratio among all the nebulae driven by young rotation-powered pulsars. We model the spectral evolution of the PWN and find it difficult to match the observed multi-band data with leptons alone using reasonable model parameters. In lepton-hadron hybrid model instead, TeV photons come mainly from $π^0$ decay in proton-proton interaction and the observed photon spectrum can be well reproduced. The newly discovered infrared loop and molecular cloud in or closely around the PWN can work as the target for the bombardment of the PWN protons.

preprint2010arXiv

Molecular environment and thermal X-ray spectroscopy of the semicircular young composite supernova remnant 3C 396

We have investigated the molecular environment of the semicircular composite supernova remnant (SNR) 3C396 and performed a Chandra spatially resolved thermal X-ray spectroscopic study of this young SNR. With our CO millimeter observations, we find that the molecular clouds (MCs) at V(LSR)~84km/s can better explain the multiwavelength properties of the remnant than the V(LSR)=67-72km/s MCs that are suggested by Lee et al. (2009). At around 84km/s, the western boundary of the SNR is perfectly confined by the western molecular wall. The CO emission fades out from west to east, indicating that the eastern region is of low gas density. In particular, an intruding finger/pillar-like MC, which may be shocked at the tip, can well explain the X-ray and radio enhancement in the southwest and some infrared filaments there. The SNR-MC interaction is also favored by the relatively elevated 12CO J=2-1/J=1-0 line ratios in the southwestern "pillar tip" and the molecular patch on the northwestern boundary. The redshifted 12CO (J=1-0 and J=2-1) wings (86-90km/s) of an eastern 81km/s molecular patch may be the kinematic evidence for shock-MC interaction. We suggest that the 69km/s MCs are in the foreground based on HI self-absorption while the 84km/s MCs at a distance of 6.2 kpc (the tangent point) are in physical contact with SNR 3C396. The X-ray spectral analysis suggests an SNR age of ~3kyr. The metal enrichment of the X-ray emitting gas in the north and south implies a 13-15Msun B1-B2 progenitor star.

preprint2010arXiv

Perturbed Hankel Determinants: Applications to the Information Theory of MIMO Wireless Communications

In this paper we compute two important information-theoretic quantities which arise in the application of multiple-input multiple-output (MIMO) antenna wireless communication systems: the distribution of the mutual information of multi-antenna Gaussian channels, and the Gallager random coding upper bound on the error probability achievable by finite-length channel codes. It turns out that the mathematical problem underpinning both quantities is the computation of certain Hankel determinants generated by deformed versions of classical weight functions. For single-user MIMO systems, it is a deformed Laguerre weight, whereas for multi-user MIMO systems it is a deformed Jacobi weight. We apply two different methods to characterize each of these Hankel determinants. First, we employ the ladder operators of the corresponding monic orthogonal polynomials to give an exact characterization of the Hankel determinants in terms of Painlevé differential equations. This turns out to be a Painlevé V for the single-user MIMO scenario and a Painlevé VI for the multi user scenario. We then employ Coulomb fluid methods to derive new closed-form approximations for the Hankel determinants which, although formally valid for large matrix dimensions, are shown to give accurate results for both the MIMO mutual information distribution and the error exponent even when the matrix dimensions are small. Focusing on the single-user mutual information distribution, we then employ both the exact Painlevé representation and the Coulomb fluid approximation to yield deeper insights into the scaling behavior in terms of the number of antennas and signal-to-noise ratio. Among other things, these results allow us to study the asymptotic Gaussianity of the distribution as the number of antennas increase, and to explicitly compute the correction terms to the mean, variance, and higher order cumulants.

preprint2010arXiv

Reaction of C_2(a^3Pi_u) with methanol: Temperature dependence and deuterium isotope effect

We present a first temperature dependence and kinetic isotope effect study on the reaction of C_2(a^3Pi_u) with methanol. The bimolecular rate constants for a series of methanol isotopomers have been measured as a function of temperature between 293 and 673 K. The observed positive temperature dependences as well as deuterium kinetic isotope effects permit determination of the reaction mechanism as a site-specific hydrogen abstraction from the methyl site rather than from the hydroxyl site.

preprint2010arXiv

Reactions of C$_2$({\it a}$^3Pi_u$) with selected saturated alkanes: A temperature dependence study

We present a temperature dependence study on the gas phase reactions of the C$_2$({\it a}$^3Pi_u$) radical with a selected series of saturated alkanes (C$_2$H$_6$, C$_3$H$_8$, n-C$_4$H$_10$, i-C$_4$H$_10$, and n-C$_6$H$_14$) by means of pulsed laser photolysis/laser-induced fluorescence technique. The bimolecular rate constants for these reactions were obtained between 298 and 673 K. A pronounced negative temperature effect was observed for n-C$_4$H$_10$, i-C$_4$H$_10$, and n-C$_6$H$_14$ and interpreted in terms of steric hindrance of the more reactive secondary or tertiary C-H bonds by less reactive CH$_3$ groups. Detailed analysis of our experimental results reveals quantitatively the temperature dependence of reactivities for the primary, secondary, and tertiary C-H bonds in these saturated alkanes and further lends support to a mechanism of hydrogen abstraction.

preprint2010arXiv

Smallest eigenvalue distribution of the fixed trace Laguerre beta-ensemble

In this paper we study entanglement of the reduced density matrix of a bipartite quantum system in a random pure state. It transpires that this involves the computation of the smallest eigenvalue distribution of the fixed trace Laguerre ensemble of $N\times N$ random matrices. We showed that for finite $N$ the smallest eigenvalue distribution may be expressed in terms of Jack polynomials. Furthermore, based on the exact results, we found, a limiting distribution, when the smallest eigenvalue is suitably scaled with $N$ followed by a large $N$ limit. Our results turn out to be the same as the smallest eigenvalue distribution of the classical Laguerre ensembles without the fixed trace constraint. This suggests in a broad sense, the global constraint does not influence local correlations, at least, in the large $N$ limit. Consequently, we have solved an open problem: The determination of the smallest eigenvalue distribution of the reduced density matrix---obtained by tracing out the environmental degrees of freedom---for a bipartite quantum system of unequal dimensions.

preprint2010arXiv

Spatial Distribution of Metal Emissions in SNR 3C 397 Viewed with Chandra and XMM

We present X-ray equivalent width imaging of the supernova remnant (SNR) 3C 397 for Mg Heα, Si Heα, S Heα, and Fe Kαcomplex lines with the Chandra and XMM-Newton observations. The images reveal that the heavier the element is, the smaller the extent of the element distribution is. The Mg emission is evidently enhanced in the southeastern blow-out region, well along the radio boundary there, and appears to partially envelope the eastern Fe knot. Two bilateral hat-like Si line-emitting structures are along the northern and southern borders, roughly symmetric with respect to the southeast-northwest elongation axis. An S line-emitting shell is located just inner to the northern radio and IR shell, indicating of a layer of reversely shocked sulphur in the ejecta. A few enhanced Fe features are basically aligned along the diagonal of the rectangular shape of the SNR, which implicates an early asymmetric SN explosion.

preprint2010arXiv

Spectroscopy of nickel monosulfide in 450 - 560 nm by laser-induced fluorescence and dispersed fluorescence techniques

Laser-induced fluorescence excitation spectrum of NiS in the wavelength range of 450 - 560 nm has been recorded and analyzed. Thirty-five vibronic transition bands have been observed, 29 of which are reported for the first time. Rotational analyses indicated that all the observed bands can be attributable to the [Omega = 0] - X^3 Sigma^- transitions of ^58 NiS (and ^60 NiS). Twenty-five bands have been suggested to be grouped into four vibrational progressions. Furthermore, through dispersed fluorescence measurements we directly obtained the energies for the ground-state vibrational levels up to v" = 6 as well as the vibrational frequency and the anharmonicity constant for the ground state of ^58 NiS.

preprint2010arXiv

The B-X and C-X band systems of CuCl revisited: A laser-induced fluorescence study in 465-490 nm

We have reinvestigated the B-X and C-X band systems of CuCl by recording the laser-induced fluorescence excitation spectra in 20400-21800 cm^{-1}. The rotational analyses in Hund's case (a) revealed unambiguously a singlet-to-singlet transition nature. The measured lifetimes of a few microseconds seem too long for singlets and too short for triplets, which we think is actually in favor of a picture of singlet ({1}^Pi and {1}^Sigma^{+})-triplet ({3}^Pi_{0,1,2}) mixed states in the B and C band systems of CuCl. The two excited states we observed in our spectra may be the singlets that have been strongly "contaminated" by their triplet neighbors.

preprint2009arXiv

Discovery of Molecular Shells Associated with Supernova Remnants. I. Kesteven 69

Supernova remnant (SNR) Kes 69 is morphologically characterized by brightened radio, infrared, and X-ray emission on the southeastern rim, with the 1720 MHz OH masers detected in the northeastern and southeastern regions at various local standard rest (LSR) velocities. We have performed a millimeter observation in CO and HCO+ lines toward \snr. From the northeastern compact maser region, 12CO and 13CO emission's peaks around 65 km/s and 85 km/s, which are consistent with the masers' LSR velocities, are detected. In the southeast, a molecular (12CO) arc is revealed at 77--86 km/s, well coincident with the partial SNR shell detected in the radio continuum and mid-infrared observations. An 85 km/s HCO+ emission is found to arise from a radio peak on the shell. Both the molecular arc and the HCO+ emission at ~85 km/s seem to be consistent with the presence of extended OH masers along the southeastern boundary of Kes 69. The morphology correspondence between the CO arc and other band emission of the Kes 69 shell provides strong evidence for the association between SNR Kes 69 and the ~85 km/s component of molecular gas. The multiwavelength emissions along the southeastern shell can be accounted for by the impact of the SNR shock on a dense, clumpy patch of molecular gas. This pre-existing gas is likely to be a part of the cooled debris of the material swept up by the progenitor's stellar wind. The association of SNR Kes 69 with the molecular cloud at the systemic velocity of ~85 km/s enables us to place the SNR at a kinematic distance of 5.2 kpc.

preprint2009arXiv

Dynamic S0 Galaxies: a Case Study of NGC 5866

S0 galaxies are often thought to be passively evolved from spirals after star formation is quenched. To explore what is occurring in S0s, we present a multi-wavelength study of NGC5866--an isolated nearby edge-on S0. This study shows strong evidence for dynamic activities in the interstellar medium, which are most likely driven by supernova explosions in the galactic disk and bulge. We utilize Chandra, HST, and Spitzer data as well as ground-based observations to characterize the content, structure, and physical state of the medium and its interplay with stars in NGC5866. A cold gas disk is detected with an exponential scale height of 100pc. Numerous off-disk dusty spurs are clearly present: prominent ones can extend as far as 300pc from the galactic plane and are probably produced by individual SNe, whereas faint filaments can have ~ kpc scale and are likely produced by SNe collectively in disk/bulge. We also detect substantial amounts of diffuse Ha- and Pa-emitting gas with a comparable scale height as the cold gas. We find that the heating of the dust and warm ionized gas cannot be explained by the radiation from evolved stars alone, strongly indicating the presence of young stars in the disk at a low formation rate of ~ 0.05Msun/yr. We reveal the presence of diffuse X-ray-emitting hot gas, which extends as far as 3.5kpc from the disk and can be heated easily by Type Ia SNe in the bulge. However, the temperature of this gas is ~ 0.2keV, substantially lower than what might be expected from the mass-loss of evolved stars and Type Ia SNe heating alone, indicating mass loading from cool gas is important. The total masses of the cold, warm and hot gases are ~ 5*10^8, 10^4 and 3*10^7Msun. The relative richness of the gases, undergoing circulations between disk/halo, is perhaps a result of its relative isolation.

preprint2009arXiv

Natural Fueling of a Tokamak Fusion Reactor

A natural fueling mechanism that helps to maintain the main core deuterium and tritium (DT) density profiles in a tokamak fusion reactor is discussed. In H-mode plasmas dominated by ion- temperature gradient (ITG) driven turbulence, cold DT ions near the edge will naturally pinch radially inward towards the core. This mechanism is due to the quasi-neutral heat flux dominated nature of ITG turbulence and still applies when trapped and passing kinetic electron effects are included. Fueling using shallow pellet injection or supersonic gas jets is augmented by an inward pinch of could DT fuel. The natural fueling mechanism is demonstrated using the three-dimensional toroidal electromagnetic gyrokinetic turbulence code GEM and is analyzed using quasilinear theory. Profiles similar to those used for conservative ITER transport modeling that have a completely flat density profile are examined and it is found that natural fueling actually reduces the linear growth rates and energy transport.

preprint2009arXiv

Painlevé V and time dependent Jacobi polynomials

In this paper we study the simplest deformation on a sequence of orthogonal polynomials, namely, replacing the original (or reference) weight $w_0(x)$ defined on an interval by $w_0(x)e^{-tx}.$ It is a well-known fact that under such a deformation the recurrence coefficients denoted as $α_n$ and $β_n$ evolve in $t$ according to the Toda equations, giving rise to the time dependent orthogonal polynomials, using Sogo's terminology. The resulting "time-dependent" Jacobi polynomials satisfy a linear second order ode. We will show that the coefficients of this ode are intimately related to a particular Painlevé V. In addition, we show that the coefficient of $z^{n-1}$ of the monic orthogonal polynomials associated with the "time-dependent" Jacobi weight, satisfies, up to a translation in $t,$ the Jimbo-Miwa $σ$-form of the same $P_{V};$ while a recurrence coefficient $α_n(t),$ is up to a translation in $t$ and a linear fractional transformation $P_{V}(α^2/2,-β^2/2, 2n+1+α+β,-1/2).$ These results are found from combining a pair of non-linear difference equations and a pair of Toda equations. This will in turn allow us to show that a certain Fredholm determinant related to a class of Toeplitz plus Hankel operators has a connection to a Painlevé equation.

preprint2009arXiv

Painlevé VI and the Unitary Jacobi ensembles

The six Painlevé transcendants which originally appeared in the studies of ordinary differential equations have been found numerous applications in physical problems. The well-known examples among which include symmetry reduction of the Ernst equation which arises from stationary axial symmetric Einstein manifold and the spin-spin correlation functions of the two-dimensional Ising model in the work of McCoy, Tracy and Wu. The problem we study in this paper originates from random matrix theory, namely, the smallest eigenvalues distribution of the finite $n$ Jacobi unitary ensembles which was first investigated by Tracy and Widom. This is equivalent to the computation of the probability that the spectrum is free of eigenvalues on the interval $[0,t]$. Such ensembles also appears in multivariate statistics known as the double-Wishart distribution. We consider a more general model where the Jacobi weight is perturbed by a discontinuous factor and study the associated finite Hankel determinant. It is shown that the logarithmic derivative of Hankel determinant satisfies a particular $σ-$form of Painlevé VI, which holds for the gap probability as well. We also compute exactly the leading term of the gap probability as $t\to 1^-$.

preprint2008arXiv

Discovery of molecular shells associated with supernova remnants. (II) Kesteven 75

The young composite supernova remnant (SNR) Kesteven 75, with a pulsar wind nebula at its center, has an unusual morphology with a bright southern half-shell structure in multiwavelengths. The distance to Kes 75 has long been uncertain. Aiming to address these issues, we have made millimeter spectroscopic observations of the molecular gas toward the remnant. The V_{LSR}~83--96 km/s molecular clouds (MCs) are found to overlap a large north-western region of the remnant and are suggested to be located in front of the SNR along the line of sight. Also in the remnant area, the V_{LSR}= 45--58 km/s MC shows a blue-shifted broadening in the 12CO (J=1-0) line profile and a perturbed position-velocity structure near the edge of the remnant, with the intensity centroid sitting in the northern area of the remnant. In particular, a cavity surrounded by a molecular shell is unveiled in the intensity map in the broadened blue wing (45--51 km/s), and the southern molecular shell follows the bright partial SNR shell seen in X-rays, mid-infrared, and radio continuum. These observational features provide effective evidences for the association of Kes 75 with the adjacent 54 km/s MC. This association leads to a determination of the kinematic distance at ~10.6 kpc to the remnant, which agrees with a location at the far side of the Sagittarius arm. The morphological coincidence of the shell seen in multiwavelengths is consistent with a scenario in which the SNR shock hits a pre-existing dense shell. This dense molecular shell is suggested to likely represent the debris of the cooled, clumpy shell of the progenitor's wind bubble proximately behind the 54 km/s cloud. The discovery of the association with MC provides a possible explanation for the gamma-ray excess of the remnant.

preprint2008arXiv

Ladder Operators for q-orthogonal Polynomials

The q-difference analog of the classical ladder operators is derived for those orthogonal polynomials arising from a class of indeterminate moments problem.

preprint2008arXiv

Painlevé V and a Pollaczek-Jacobi type orthogonal polynomials

We study a sequence of polynomials orthogonal with respect to a one parameter family of weights $$ w(x):=w(x,t)=\rex^{-t/x}\:x^{\al}(1-x)^{\bt},\quad t\geq 0, $$ defined for $x\in[0,1].$ If $t=0,$ this reduces to a shifted Jacobi weight. Our ladder operator formalism and the associated compatibility conditions give an easy determination of the recurrence coefficients. For $t>0,$ the factor $\rex^{-t/x}$ induces an infinitely strong zero at $x=0.$ With the aid of the compatibility conditions, the recurrence coefficients are expressed in terms of a set of auxiliary quantities that satisfy a system of difference equations. These, when suitably combined with a pair of Toda-like equations derived from the orthogonality principle, show that the auxiliary quantities are a particular Painlevé V and/or allied functions. It is also shown that the logarithmic derivative of the Hankel determinant, $$ D_n(t):=\det(\int_{0}^{1} x^{i+j} \:\rex^{-t/x}\:x^{\al}(1-x)^{\bt}dx)_{i,j=0}^{n-1}, $$ satisfies the Jimbo-Miwa-Okamoto $σ-$form of the Painlevé V and that the same quantity satisfies a second order non-linear difference equation which we believe to be new.

preprint2005arXiv

Narrow Band Chandra X-ray Analysis of Supernova Remnant 3C391

We present the narrow-band and the equivalent width (EW) images of the thermal composite supernova remnant (SNR) 3C391 for the X-ray emission lines of elements Mg, Si, & S using the Chandra ACIS Observational data. These EW images reveal the spatial distribution of the emission of the metal species Mg, Si, & S in the remnant. They have clumpy structure similar to that seen from the broadband diffuse emission, suggesting that they are largely of interstellar origin. We find an interesting finger-like feature protruding outside the southwestern radio border of the remnant, which is somewhat similar to the jet-like Si structure found in the famous SNR Cas A. This feature may possibly be the debris of the jet of ejecta which implies an asymmetrical supernova explosion of a massive progenitor star.

preprint2005arXiv

Perturbed Hankel Determinants

In this short note, we compute, for large n the determinant of a class of n x n Hankel matrices, which arise from a smooth perturbation of the Jacobi weight. For this purpose, we employ the same idea used in previous papers, where the unknown determinant, D_n[w_{α,β}h] is compared with the known determinant D_n[w_{α,β}]. Here w_{α,β} is the Jacobi weight and w_{α,β}h, where h=h(x),x\in[-1,1] is strictly positive and real analytic, is the smooth perturbation on the Jacobi weight w_{α,β}(x):=(1-x)^α(1+x)^β. Applying a previously known formula on the distribution function of linear statistics, we compute the large n asymptotics of D_n[w_{α,β}h] and supply a missing constant of the expansion.

preprint2000arXiv

Small Eigenvalues of Large Hankel Matrices

In this paper we investigate the smallest eigenvalue, denoted as $\la_N,$ of a $(N+1)\times (N+1)$ Hankel or moments matrix, associated with the weight, $w(x)=\exp(-x^{\bt}),x>0,\bt>0$, in the large $N$ limit. Using a previous result, the asymptotics for the polynomials, $P_n(z),z\notin[0,\infty)$, orthonormal with respect to $w,$ which are required in the determination of $\la_N$ are found. Adopting an argument of Szegö the asymptotic behaviour of $\la_N$, for $\bt>1/2$ where the related moment problem is determinate, is derived. This generalises the result given by Szegö for $\bt=1$. It is shown that for $\bt>1/2$ the smallest eigenvalue of the infinite Hankel matrix is zero, while for $0<\bt<1/2$ it is greater then a positive constant. This shows a phase transition in the corresponding Hermitian random matrix model as the parameter $\bt$ varies with $\bt=1/2$ identified as the critical point. The smallest eigenvalue at this point is conjectured.

preprint1997arXiv

The Cone-Like H-alpha Nebula in NGC 4945: A Galactic Superwind Bow Shock ?

We find that a non-axisymmetric bow shock model, with an appropriate choice of parameters, could fit the line splitting velocity field of the cone-like H$α$ nebula in NGC 4945 better than a canonical cone model. Meanwhile, the bow shock model could also reproduce the morphology of the H$α$ nebula. The bow shock results from the interaction of the galactic superwinds with a giant HII region. It is implied that the starburst ring or disk around the galactic nucleus should be generating strong winds, and the bright H$α$ knot northwest of the nucleus be suffering an anisotropic mass loss process.

preprint1994arXiv

Gap Formation Probability of the $α-$ Ensemble

In this paper we employ the continuum approximation of Dyson to determine the asymptotic gap formation probability in the spectrum of $N\times N$ Hermitean random matrices. The associated orthogonal polynomials has weight function, $w(x)=e^{-u(x)},$ where $u(x)=x^α,\;α>0,\;0<x<\infty.$ It is shown that the probability that the scaled interval $(0,s)$ contains no eigenvalues is universal for $α>1/2$ and depends on $α$ for $0<α<1/2.$

Yang Chen

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201 published item(s)

A neural network for modeling human concept formation, understanding and communication

DB-MSMUNet:Dual Branch Multi-scale Mamba UNet for Pancreatic CT Scans Segmentation

HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer

LLMRouterBench: A Massive Benchmark and Unified Framework for LLM Routing

Mitigating Prompt-Induced Hallucinations in Large Language Models via Structured Reasoning

Residual Gaussian Splatting for Ultra Sparse-View CBCT Reconstruction

Towards Understanding and Characterizing Vulnerabilities in Intelligent Connected Vehicles through Real-World Exploits

Ultrahigh-Energy Gamma-ray Emission Associated with Black Hole-Jet Systems

tf.data service: A Case for Disaggregating ML Input Data Processing

Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning

Analytical Approximations for Generalized Landau-Zener Transitions in Multi-level Non-Hermitian Systems

The Bending of C$_3$: Experimentally Probing the $l$-type Doubling and Resonance

A Possible Gamma-Ray Enhancement Event in Tycho's Supernova Remnant

Analytical study on magnetic component of geodesic acoustic mode

Beam pointing stabilization of an acousto-optic modulator with thermal control

Breaking the accuracy and resolution limitation of filter- and frequency-to-time mapping-based time and frequency acquisition methods by broadening the filter bandwidth

Distribution of the Scaled Condition Number of Single-spiked Complex Wishart Matrices

foREST: A Tree-based Approach for Fuzzing RESTful APIs

Geometric Conditions for the Discrepant Posterior Phenomenon and Connections to Simpson's Paradox

GeV Gamma-ray Emission and Molecular Clouds towards Supernova Remnant G35.6$-$0.4 and the TeV Source HESS J1858+020

Graph Fourier transform based on singular value decomposition of directed Laplacian

Graph Fourier transforms on directed product graphs

Individual-Level Inverse Reinforcement Learning for Mean Field Games

Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering

Matrix Completion Methods for the Total Electron Content Video Reconstruction

MetaComp: Learning to Adapt for Online Depth Completion

MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation

Multiple Instance Learning with Mixed Supervision in Gleason Grading

Optical vortex Brillouin laser

Photonics-Assisted Joint Communication-Radar System Based on a QPSK-Sliced Linearly Frequency-Modulated Signal

Photonics-enabled wavelet-like transform via nonlinear optical frequency sweeping and stimulated Brillouin scattering-based frequency-to-time mapping

Predicting Solar Flares Using CNN and LSTM on Two Solar Cycles of Active Region Data

Proximal PanNet: A Model-Based Deep Network for Pansharpening

Simulating the Legacy Survey of Space and Time stellar content with TRILEGAL

Spatially decomposed $γ$-ray features surrounding SNR Kes 79 & PSR J1853+0056

STELLA: Sparse Taint Analysis for Enclave Leakage Detection

The Eigenvectors of Single-spiked Complex Wishart Matrices: Finite and Asymptotic Analyses

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Time-varying microwave photonic filter for arbitrary waveform signal-to-noise ratio improvement

Tree level Majorana neutrino mass from Type-1 $\times$ Type-2 Seesaw mechanism with Dark Matter

Unusually high HCO+/CO ratios in and outside supernova remnant W49B

WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma

Digital-assisted photonic analog wideband multipath self-interference cancellation

Genuine tripartite entanglement as a probe of quantum phase transitions in a spin-1 Heisenberg chain with single-ion anisotropy

Homotopic Gradients of Generative Density Priors for MR Image Reconstruction

IRAM 30 m CO-line Observation toward PeVatron Candidate G106.3+2.7: Direct Interaction between the Shock and the Molecular Cloud Remains Uncertain

Photonic-enabled radio-frequency self-interference cancellation incorporated in an in-band full-duplex radio-over-fiber system

Photonics-assisted microwave pulse detection and frequency measurement based on pulse replication and frequency-to-time mapping

Quantum key distribution over 658 km fiber with distributed vibration sensing

Short-time Fourier transform based on stimulated Brillouin scattering

Spatially Resolved X-ray Study of Supernova Remnant G306.3$-$0.9 with Unusually High Calcium Abundance

Time-frequency analysis of microwave signals based on stimulated Brillouin scattering

Transverse mode-encoded quantum gate on a silicon photonic chip

2-local derivations on Witt algebras

A deep learning approach for virtual monochromatic spectral CT imaging with a standard single energy CT scanner

A Gaia early DR3 mock stellar catalog: Galactic prior and selection function

A Small-Scale Investigation of Molecular Emission toward the Tip of the Western Lobe of W50/SS433

A Study of Efficient Light Field Subsampling and Reconstruction Strategies

Active Learning over DNN: Automated Engineering Design Optimization for Fluid Dynamics Based on Self-Simulated Dataset

An XMM-Newton X-ray View of Supernova Remnant W49B: Revisiting its Recombining Plasmas and Progenitor Type

Carbon star formation as seen through the non-monotonic initial-final mass relation

Chemical abundances in Sgr A East: evidence for a Type Iax supernova remnant

Constraining the thermally pulsing asymptotic giant branch phase with resolved stellar populations in the Large Magellanic Cloud

Data Techniques For Online End-to-end Speech Recognition

Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images

DIRECT-Net: a unified mutual-domain material decomposition network for quantitative dual-energy CT imaging

Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network

EB-dynaRE: Real-Time Adjustor for Brownian Movement with Examples of Predicting Stock Trends Based on a Novel Event-Based Supervised Learning Algorithm

Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields

Gap Probabilities in the Laguerre Unitary Ensemble and Discrete Painlevé Equations

Gaussian unitary ensemble with two jump discontinuities, PDEs and the coupled Painlevé II and IV systems

General stationary solutions of the nonlocal nonlinear Schrödinger equation and their relevance to the PT-symmetric system

Hot-Carrier Separation in Heterostructure Nanowires observed by Electron-Beam Induced Current

Interpreting LSTM Prediction on Solar Flare Eruption with Time-series Clustering