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Feng Liu

Feng Liu contributes to research discovery and scholarly infrastructure.

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preprint2026arXiv

UniCorrn: Unified Correspondence Transformer Across 2D and 3D

Visual correspondence across image-to-image (2D-2D), image-to-point cloud (2D-3D), and point cloud-to-point cloud (3D-3D) geometric matching forms the foundation for numerous 3D vision tasks. Despite sharing a similar problem structure, current methods use task-specific designs with separate models for each modality combination. We present UniCorrn, the first correspondence model with shared weights that unifies geometric matching across all three tasks. Our key insight is that Transformer attention naturally captures cross-modal feature similarity. We propose a dual-stream decoder that maintains separate appearance and positional feature streams. This design enables end-to-end learning through stack-able layers while supporting flexible query-based correspondence estimation across heterogeneous modalities. Our architecture employs modality-specific backbones followed by shared encoder and decoder components, trained jointly on diverse data combining pseudo point clouds from depth maps with real 3D correspondence annotations. UniCorrn achieves competitive performance on 2D-2D matching and surpasses prior state-of-the-art by 8% on 7Scenes (2D-3D) and 10% on 3DLoMatch (3D-3D) in registration recall. Project website: https://neu-vi.github.io/UniCorrn

preprint2025arXiv

Generalising Traffic Forecasting to Regions without Traffic Observations

Traffic forecasting is essential for intelligent transportation systems. Accurate forecasting relies on continuous observations collected by traffic sensors. However, due to high deployment and maintenance costs, not all regions are equipped with such sensors. This paper aims to forecast for regions without traffic sensors, where the lack of historical traffic observations challenges the generalisability of existing models. We propose a model named GenCast, the core idea of which is to exploit external knowledge to compensate for the missing observations and to enhance generalisation. We integrate physics-informed neural networks into GenCast, enabling physical principles to regularise the learning process. We introduce an external signal learning module to explore correlations between traffic states and external signals such as weather conditions, further improving model generalisability. Additionally, we design a spatial grouping module to filter localised features that hinder model generalisability. Extensive experiments show that GenCast consistently reduces forecasting errors on multiple real-world datasets.

preprint2025arXiv

SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents

We introduce SCP: the Science Context Protocol, an open-source standard designed to accelerate discovery by enabling a global network of autonomous scientific agents. SCP is built on two foundational pillars: (1) Unified Resource Integration: At its core, SCP provides a universal specification for describing and invoking scientific resources, spanning software tools, models, datasets, and physical instruments. This protocol-level standardization enables AI agents and applications to discover, call, and compose capabilities seamlessly across disparate platforms and institutional boundaries. (2) Orchestrated Experiment Lifecycle Management: SCP complements the protocol with a secure service architecture, which comprises a centralized SCP Hub and federated SCP Servers. This architecture manages the complete experiment lifecycle (registration, planning, execution, monitoring, and archival), enforces fine-grained authentication and authorization, and orchestrates traceable, end-to-end workflows that bridge computational and physical laboratories. Based on SCP, we have constructed a scientific discovery platform that offers researchers and agents a large-scale ecosystem of more than 1,600 tool resources. Across diverse use cases, SCP facilitates secure, large-scale collaboration between heterogeneous AI systems and human researchers while significantly reducing integration overhead and enhancing reproducibility. By standardizing scientific context and tool orchestration at the protocol level, SCP establishes essential infrastructure for scalable, multi-institution, agent-driven science.

preprint2024arXiv

From Data to Insights: A Comprehensive Survey on Advanced Applications in Thyroid Cancer Research

Thyroid cancer, the most prevalent endocrine cancer, has gained significant global attention due to its impact on public health. Extensive research efforts have been dedicated to leveraging artificial intelligence (AI) methods for the early detection of this disease, aiming to reduce its morbidity rates. However, a comprehensive understanding of the structured organization of research applications in this particular field remains elusive. To address this knowledge gap, we conducted a systematic review and developed a comprehensive taxonomy of machine learning-based applications in thyroid cancer pathogenesis, diagnosis, and prognosis. Our primary objective was to facilitate the research community's ability to stay abreast of technological advancements and potentially lead the emerging trends in this field. This survey presents a coherent literature review framework for interpreting the advanced techniques used in thyroid cancer research. A total of 758 related studies were identified and scrutinized. To the best of our knowledge, this is the first review that provides an in-depth analysis of the various aspects of AI applications employed in the context of thyroid cancer. Furthermore, we highlight key challenges encountered in this domain and propose future research opportunities for those interested in studying the latest trends or exploring less-investigated aspects of thyroid cancer research. By presenting this comprehensive review and taxonomy, we contribute to the existing knowledge in the field, while providing valuable insights for researchers, clinicians, and stakeholders in advancing the understanding and management of this disease.

preprint2024arXiv

Investigation of the $ΔI = 1/2$ rule and test of CP violation through the measurement of decay asymmetry parameters in $Ξ^-$ decays

Using $(10087\pm44)\times 10^{6}$ $J/ψ$ events collected with the BESIII detector, numerous $Ξ^-$ and $Λ$ decay asymmetry parameters are simultaneously determined from the process $J/ψ\to Ξ^- \barΞ^+ \to Λ(pπ^-) π^- \barΛ(\bar{n} π^0) π^+$ and its charge-conjugate channel. The precisions of $α_0$ for $Λ\to nπ^0$ and $\barα_0$ for $\barΛ \to \bar{n}π^0$ compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of $Λ\to nπ^0$ to that of $Λ\to pπ^-$, $\langle α_0 \rangle/ \langle α_{Λ-} \rangle $, is determined to be $ 0.873 \pm 0.012^{+0.011}_{-0.010}$, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than $5σ$, which signifies the existence of the $ΔI = 3/2$ transition in $Λ$ for the first time. Beside, we test for CP violation in $Ξ^- \to Λπ^-$ and in $Λ\to n π^{0}$ with the best precision to date.

preprint2024arXiv

Millikelvin confocal microscope with free-space access and high-frequency electrical control

Cryogenic confocal microscopy is a powerful method for studying solid state quantum devices such as single photon sources and optically controlled qubits. While the vast majority of such studies have been conducted at temperatures of a few Kelvin, experiments involving fragile quantum effects often require lower operating temperatures. To also allow for electrical dynamic control, microwave connectivity is required. For polarization-sensitive studies, free space optical access is advantageous compared to fiber coupling. Here we present a confocal microscope in a dilution refrigerator providing all the above features at temperatures below 100 mK. The installed high frequency cabling meets the requirements for state of the art spin qubit experiments. As another unique advantage of our system, the sample fitting inside a large puck can be exchanged while keeping the cryostat cold with minimal realignment. Assessing the performance of the instrument, we demonstrate confocal imaging, sub-nanosecond modulation of the emission wavelength of a suitable sample and an electron temperature of 76 mK. While the instrument was constructed primarily with the development of optical interfaces to electrically controlled qubits in mind, it can be used for many experiments involving quantum transport, solid state quantum optics and microwave-optical transducers.

preprint2023arXiv

Search for hidden-charm tetraquark with strangeness in $e^{+}e^{-}\rightarrow K^+ D_{s}^{-} D^{0}+c.c.$

We report a search for a heavier partner of the recently observed $Z_{cs}(3985)^{-}$ state, denoted as $Z_{cs}^{\prime -}$, in the process $e^{+} e^{-}\rightarrow K^{+}D_{s}^{*-}D^{* 0}+c.c.$, based on $e^+e^-$ collision data collected at the center-of-mass energies of $\sqrt{s}=4.661$, 4.682 and 4.699 GeV with the BESIII detector. The $Z_{cs}^{\prime -}$ is of interest as it is expected to be a candidate for a hidden-charm and open-strange tetraquark. A partial-reconstruction technique is used to isolate $K^+$ recoil-mass spectra, which are probed for a potential contribution from $Z_{cs}^{\prime -}\to D_{s}^{*-}D^{* 0}$ ($c.c.$). We find an excess of $Z_{cs}^{\prime -}\rightarrow D_{s}^{*-}D^{*0}$ ($c.c.$) candidates with a significance of $2.1σ$, after considering systematic uncertainties, at a mass of $(4123.5\pm0.7_\mathrm{stat.}\pm4.7_\mathrm{syst.})\ \mathrm{MeV}/c^{2}$. As the data set is limited in size, the upper limits are evaluated at the 90\% confidence level on the product of the Born cross sections ($σ^{\mathrm{Born}}$) and the branching fraction ($\mathcal{B}$) of $Z_{cs}^{\prime-}\rightarrow D_{s}^{*-}D^{* 0}$, under different assumptions of the $Z_{cs}^{\prime -}$ mass from 4.120 to 4.140 MeV and of the width from 10 to 50 MeV at the three center-of-mass energies. The upper limits of $σ^{\rm Born}\cdot\mathcal{B}$ are found to be at the level of $\mathcal{O}(1)$ pb at each energy. Larger data samples are needed to confirm the $Z_{cs}^{\prime -}$ state and clarify its nature in the coming years.

preprint2022arXiv

2D GANs Meet Unsupervised Single-view 3D Reconstruction

Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks. However, less attention has been devoted to 3D vision tasks. In light of this, we propose a novel image-conditioned neural implicit field, which can leverage 2D supervisions from GAN-generated multi-view images and perform the single-view reconstruction of generic objects. Firstly, a novel offline StyleGAN-based generator is presented to generate plausible pseudo images with full control over the viewpoint. Then, we propose to utilize a neural implicit function, along with a differentiable renderer to learn 3D geometry from pseudo images with object masks and rough pose initializations. To further detect the unreliable supervisions, we introduce a novel uncertainty module to predict uncertainty maps, which remedy the negative effect of uncertain regions in pseudo images, leading to a better reconstruction performance. The effectiveness of our approach is demonstrated through superior single-view 3D reconstruction results of generic objects.

preprint2022arXiv

A novel stereo matching pipeline with robustness and unfixed disparity search range

Stereo matching is an essential basis for various applications, but most stereo matching methods have poor generalization performance and require a fixed disparity search range. Moreover, current stereo matching methods focus on the scenes that only have positive disparities, but ignore the scenes that contain both positive and negative disparities, such as 3D movies. In this paper, we present a new stereo matching pipeline that first computes semi-dense disparity maps based on binocular disparity, and then completes the rest depending on monocular cues. The new stereo matching pipeline have the following advantages: It 1) has better generalization performance than most of the current stereo matching methods; 2) relaxes the limitation of a fixed disparity search range; 3) can handle the scenes that involve both positive and negative disparities, which has more potential applications, such as view synthesis in 3D multimedia and VR/AR. Experimental results demonstrate the effectiveness of our new stereo matching pipeline.

preprint2022arXiv

A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images

Since data scarcity and data heterogeneity are prevailing for medical images, well-trained Convolutional Neural Networks (CNNs) using previous normalization methods may perform poorly when deployed to a new site. However, a reliable model for real-world clinical applications should be able to generalize well both on in-distribution (IND) and out-of-distribution (OOD) data (e.g., the new site data). In this study, we present a novel normalization technique called window normalization (WIN) to improve the model generalization on heterogeneous medical images, which is a simple yet effective alternative to existing normalization methods. Specifically, WIN perturbs the normalizing statistics with the local statistics computed on the window of features. This feature-level augmentation technique regularizes the models well and improves their OOD generalization significantly. Taking its advantage, we propose a novel self-distillation method called WIN-WIN for classification tasks. WIN-WIN is easily implemented with twice forward passes and a consistency constraint, which can be a simple extension for existing methods. Extensive experimental results on various tasks (6 tasks) and datasets (24 datasets) demonstrate the generality and effectiveness of our methods.

preprint2022arXiv

Adversarial Attack and Defense for Non-Parametric Two-Sample Tests

Non-parametric two-sample tests (TSTs) that judge whether two sets of samples are drawn from the same distribution, have been widely used in the analysis of critical data. People tend to employ TSTs as trusted basic tools and rarely have any doubt about their reliability. This paper systematically uncovers the failure mode of non-parametric TSTs through adversarial attacks and then proposes corresponding defense strategies. First, we theoretically show that an adversary can upper-bound the distributional shift which guarantees the attack's invisibility. Furthermore, we theoretically find that the adversary can also degrade the lower bound of a TST's test power, which enables us to iteratively minimize the test criterion in order to search for adversarial pairs. To enable TST-agnostic attacks, we propose an ensemble attack (EA) framework that jointly minimizes the different types of test criteria. Second, to robustify TSTs, we propose a max-min optimization that iteratively generates adversarial pairs to train the deep kernels. Extensive experiments on both simulated and real-world datasets validate the adversarial vulnerabilities of non-parametric TSTs and the effectiveness of our proposed defense. Source code is available at https://github.com/GodXuxilie/Robust-TST.git.

preprint2022arXiv

Amplitude analysis and branching fraction measurement of the decay $D_{s}^{+} \to K^+π^+π^-$

Using $6.32$ fb$^{-1}$ of $e^{+}e^{-}$ collision data collected at the center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we perform an amplitude analysis of the decay $D^+_s \to K^+π^+π^-$ and determine the amplitudes of the various intermediate states. The absolute branching fraction of $D^+_s\to K^+π^+π^-$ is measured to be ($6.11\pm0.18_{\rm stat.}\pm0.11_{\rm syst.})\times 10^{-3}$. The branching fractions of the dominant intermediate processes $D_{s}^{+} \to K^+ρ^0, ρ^0 \to π^+π^-$ and $D_{s}^{+} \to K^*(892)^0π^+, K^*(892)^0 \to K^+π^-$ are determined to be $(1.96\pm0.19_{\rm stat.}\pm0.23_{\rm syst.})\times 10^{-3}$ and $(1.85\pm0.12_{\rm stat.}\pm0.13_{\rm syst.})\times 10^{-3}$, respectively. The intermediate resonances $f_0(500)$, $f_0(980)$, and $f_0(1370)$ are observed for the first time in this channel.

preprint2022arXiv

Amplitude analysis and branching-fraction measurement of $D_{s}^{+} \to π^{+}π^{0}η^{\prime}$

Using data collected with the BESIII detector in $e^+e^-$ collisions at center-of-mass energies between 4.178 and 4.226 GeV and corresponding to 6.32~fb$^{-1}$ of integrated luminosity, we report the amplitude analysis and branching-fraction measurement of the $D^+_s \to π^+ π^0 η^{\prime}$ decay. We find that the dominant intermediate process is $D^+_s \toρ^+ η^{\prime}$ and the significances of other resonant and nonresonant processes are all less than $3σ$. The upper limits on the branching fractions of $S$-wave and $P$-wave nonresonant components are set to $0.10\%$ and $0.74\%$ at the $90\%$ confidence level, respectively. In addition, the branching fraction of the $D^+_s \to π^+ π^0 η^{\prime}$ decay is measured to be $(6.15\pm0.25(\rm stat.)\pm0.18(\rm syst.))\%$, which receives significant contribution only from $D_s^+\to ρ^+η^{\prime}$ according to the amplitude analysis.

preprint2022arXiv

Balanced Graph Structure Learning for Multivariate Time Series Forecasting

Accurate forecasting of multivariate time series is an extensively studied subject in finance, transportation, and computer science. Fully mining the correlation and causation between the variables in a multivariate time series exhibits noticeable results in improving the performance of a time series model. Recently, some models have explored the dependencies between variables through end-to-end graph structure learning without the need for predefined graphs. However, current models do not incorporate the trade-off between efficiency and flexibility and lack the guidance of domain knowledge in the design of graph structure learning algorithms. This paper alleviates the above issues by proposing Balanced Graph Structure Learning for Forecasting (BGSLF), a novel deep learning model that joins graph structure learning and forecasting. Technically, BGSLF leverages the spatial information into convolutional operations and extracts temporal dynamics using the diffusion convolutional recurrent network. The proposed framework balance the trade-off between efficiency and flexibility by introducing Multi-Graph Generation Network (MGN) and Graph Selection Module. In addition, a method named Smooth Sparse Unit (SSU) is designed to sparse the learned graph structures, which conforms to the sparse spatial correlations in the real world. Extensive experiments on four real-world datasets demonstrate that our model achieves state-of-the-art performances with minor trainable parameters. Code will be made publicly available.

preprint2022arXiv

BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources

Introduction: Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial hemorrhages, is challenging due to the relatively large scale of the field induced by these pathological susceptibility sources. Method: This study proposes a new deep learning-based method, BFRnet, to remove background field in healthy and hemorrhagic subjects. The network is built with the dual-frequency octave convolutions on the U-net architecture, trained with synthetic field maps containing significant susceptibility sources. The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects. Robustness against acquisition field-of-view (FOV) orientation and brain masking are also investigated. Results: For both simulation and in vivo experiments, BFRnet led to the best visually appealing results in the local field and QSM results with the minimum contrast loss and the most accurate hemorrhage susceptibility measurements among all five methods. In addition, BFRnet produced the most consistent local field and susceptibility maps between different sizes of brain masks, while conventional methods depend drastically on precise brain extraction and further brain edge erosions. It is also observed that BFRnet performed the best among all BFR methods for acquisition FOVs oblique to the main magnetic field. Conclusion: The proposed BFRnet improved the accuracy of local field reconstruction in the hemorrhagic subjects compared with conventional BFR algorithms. The BFRnet method was effective for acquisitions of titled orientations and retained whole brains without edge erosion as often required by traditional BFR methods.

preprint2022arXiv

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks

Through using only a well-trained classifier, model-inversion (MI) attacks can recover the data used for training the classifier, leading to the privacy leakage of the training data. To defend against MI attacks, previous work utilizes a unilateral dependency optimization strategy, i.e., minimizing the dependency between inputs (i.e., features) and outputs (i.e., labels) during training the classifier. However, such a minimization process conflicts with minimizing the supervised loss that aims to maximize the dependency between inputs and outputs, causing an explicit trade-off between model robustness against MI attacks and model utility on classification tasks. In this paper, we aim to minimize the dependency between the latent representations and the inputs while maximizing the dependency between latent representations and the outputs, named a bilateral dependency optimization (BiDO) strategy. In particular, we use the dependency constraints as a universally applicable regularizer in addition to commonly used losses for deep neural networks (e.g., cross-entropy), which can be instantiated with appropriate dependency criteria according to different tasks. To verify the efficacy of our strategy, we propose two implementations of BiDO, by using two different dependency measures: BiDO with constrained covariance (BiDO-COCO) and BiDO with Hilbert-Schmidt Independence Criterion (BiDO-HSIC). Experiments show that BiDO achieves the state-of-the-art defense performance for a variety of datasets, classifiers, and MI attacks while suffering a minor classification-accuracy drop compared to the well-trained classifier with no defense, which lights up a novel road to defend against MI attacks.

preprint2022arXiv

Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels

Deep models trained with noisy labels are prone to over-fitting and struggle in generalization. Most existing solutions are based on an ideal assumption that the label noise is class-conditional, i.e., instances of the same class share the same noise model, and are independent of features. While in practice, the real-world noise patterns are usually more fine-grained as instance-dependent ones, which poses a big challenge, especially in the presence of inter-class imbalance. In this paper, we propose a two-stage clean samples identification method to address the aforementioned challenge. First, we employ a class-level feature clustering procedure for the early identification of clean samples that are near the class-wise prediction centers. Notably, we address the class imbalance problem by aggregating rare classes according to their prediction entropy. Second, for the remaining clean samples that are close to the ground truth class boundary (usually mixed with the samples with instance-dependent noises), we propose a novel consistency-based classification method that identifies them using the consistency of two classifier heads: the higher the consistency, the larger the probability that a sample is clean. Extensive experiments on several challenging benchmarks demonstrate the superior performance of our method against the state-of-the-art.

preprint2022arXiv

Controllable and Guided Face Synthesis for Unconstrained Face Recognition

Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained training datasets and unconstrained testing scenarios. To address this problem, we propose a controllable face synthesis model (CFSM) that can mimic the distribution of target datasets in a style latent space. CFSM learns a linear subspace with orthogonal bases in the style latent space with precise control over the diversity and degree of synthesis. Furthermore, the pre-trained synthesis model can be guided by the FR model, making the resulting images more beneficial for FR model training. Besides, target dataset distributions are characterized by the learned orthogonal bases, which can be utilized to measure the distributional similarity among face datasets. Our approach yields significant performance gains on unconstrained benchmarks, such as IJB-B, IJB-C, TinyFace and IJB-S (+5.76% Rank1).

preprint2022arXiv

Cross section measurements of the processes $e^+e^- \rightarrow ωπ^{0}$ and $ωη$ at center-of-mass energies between 3.773 and 4.701 GeV

The Born cross sections of the processes $e^+e^- \rightarrow ωπ^{0}$ and $e^+e^- \rightarrow ωη$ are measured at center-of-mass energies between 3.773 and 4.701 GeV using a total integrated luminosity of 22.7 fb$^{-1}$ collected with the BESIII detector operating at the BEPCII collider. A simple $s^{-n}$ dependence for the continuum process can describe the measured Born cross sections. No significant contributions from the $ψ(4160)$, $Y(4230)$, $Y(4360)$, $ψ(4415)$, $Y(4660)$ resonances are found, which indicates relative small branching fractions for these resonances into the $ωπ^{0}$ and $ωη$ final states.

preprint2022arXiv

Disentangleing Content and Fine-grained Prosody Information via Hybrid ASR Bottleneck Features for Voice Conversion

Non-parallel data voice conversion (VC) have achieved considerable breakthroughs recently through introducing bottleneck features (BNFs) extracted by the automatic speech recognition(ASR) model. However, selection of BNFs have a significant impact on VC result. For example, when extracting BNFs from ASR trained with Cross Entropy loss (CE-BNFs) and feeding into neural network to train a VC system, the timbre similarity of converted speech is significantly degraded. If BNFs are extracted from ASR trained using Connectionist Temporal Classification loss (CTC-BNFs), the naturalness of the converted speech may decrease. This phenomenon is caused by the difference of information contained in BNFs. In this paper, we proposed an any-to-one VC method using hybrid bottleneck features extracted from CTC-BNFs and CE-BNFs to complement each other advantages. Gradient reversal layer and instance normalization were used to extract prosody information from CE-BNFs and content information from CTC-BNFs. Auto-regressive decoder and Hifi-GAN vocoder were used to generate high-quality waveform. Experimental results show that our proposed method achieves higher similarity, naturalness, quality than baseline method and reveals the differences between the information contained in CE-BNFs and CTC-BNFs as well as the influence they have on the converted speech.

preprint2022arXiv

Double-Pulse Generation of Indistinguishable Single Photons with Optically Controlled Polarization

Single-photon sources play a key role in photonic quantum technologies. Semiconductor quantum dots can emit indistinguishable single photons under resonant excitation. However, the resonance fluorescence technique typically requires cross-polarization filtering which causes a loss of the unpolarized quantum dot emission by 50%. To solve this problem, we demonstrate a method to generate indistinguishable single photons with optically controlled polarization by two laser pulses off-resonant with neutral exciton states. This scheme is realized by exciting the quantum dot to the biexciton state and subsequently driving the quantum dot to an exciton eigenstate. Combining with magnetic field, we demonstrated the generation of photons with optically controlled polarization (polarization degree of 101(2)%), laser-neutral exciton detuning up to 0.81 meV, high single-photon purity (99.6(1)%) and indistinguishability (85(4)%). Laser pulses can be blocked using polarization and spectral filtering. Our work makes an important step towards indistinguishable single-photon sources with near-unity collection efficiency.

preprint2022arXiv

Edge states in a non-Hermitian topological crystalline insulator

Breaking Hermiticity in topological systems gives rise to intriguing phenomena, such as the exceptional topology and the non-Hermitian skin effect. In this work, we study a non-Hermitian topological crystalline insulator sitting on the Kekulé-modulated honeycomb lattice with balanced gain and loss. We find that the gaplessness of the topological edge states in the non-Hermitian system is insensitive to edge geometries under moderate strength of gain and loss, unlike the cases of Hermitian topological crystalline insulators that depend on edge geometries crucially. We focus on two types of gain and loss configurations, which are $PT$-symmetric and $PT$-asymmetric, respectively. For the $PT$-symmetric configuration, the Dirac point of the topological edge states in the Hermitian molecular-zigzag-terminated ribbons splits into a pair of exceptional points. The edge gap in the Hermitian armchair-terminated ribbons vanishes and a Dirac point forms as far as moderate gain and loss is induced. The band gaps of edge and bulk states in the Hermitian armchair-terminated ribbons close simultaneously for the $PT$-asymmetric configuration.

preprint2022arXiv

Effective Model for Fractional Topological Corner Modes in Quasicrystals

High-order topological insulators (HOTIs), as generalized from topological crystalline insulators (TCIs), are characterized with lower-dimensional metallic boundary states protected by spatial symmetries of a crystal, whose theoretical framework based on band inversion at special $k$-points cannot be readily extended to quasicrystals because quasicrystals contain rotational symmetries that are not compatible with crystals, and momentum is no longer a good quantum number. Here, we develop a low-energy effective model underlying HOTI states in 2D quasicrystals for all possible rotational symmetries. By implementing a novel Fourier transform developed recently for quasicrystals and approximating the long-wavelength behavior by their large-scale average, we construct an effective $k \cdot p$ Hamiltonian to capture the band inversion at the center of a pseudo-Brillouin zone (PBZ). We show that an in-plane Zeeman field can induce mass-kinks at the intersection of adjacent edges of a 2D quasicrystal TI and generate corner modes (CMs) with fractional charge, protected by rotational symmetries. Our model predictions are confirmed by numerical tight-binding calculations. Furthermore, when the quasicrystal is proximitized by an \textit{s}-wave superconductor, Majorana CMs can also be created by tuning the field strength and chemical potential. Our work affords a generic approach to studying the low-energy physics of quasicrystals, in association with topological excitations and fractional statistics.

preprint2022arXiv

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack

The AutoAttack (AA) has been the most reliable method to evaluate adversarial robustness when considerable computational resources are available. However, the high computational cost (e.g., 100 times more than that of the project gradient descent attack) makes AA infeasible for practitioners with limited computational resources, and also hinders applications of AA in the adversarial training (AT). In this paper, we propose a novel method, minimum-margin (MM) attack, to fast and reliably evaluate adversarial robustness. Compared with AA, our method achieves comparable performance but only costs 3% of the computational time in extensive experiments. The reliability of our method lies in that we evaluate the quality of adversarial examples using the margin between two targets that can precisely identify the most adversarial example. The computational efficiency of our method lies in an effective Sequential TArget Ranking Selection (STARS) method, ensuring that the cost of the MM attack is independent of the number of classes. The MM attack opens a new way for evaluating adversarial robustness and provides a feasible and reliable way to generate high-quality adversarial examples in AT.

preprint2022arXiv

First Observation of the Semileptonic Decay $Λ_c^+\rightarrow pK^- e^+ν_e$

Using $4.5~\mathrm{fb}^{-1}$ of $e^+e^-$ annihilation data samples collected at the center-of-mass energies ranging from 4.600~GeV to 4.699~GeV with the BESIII detector at the BEPCII collider, a first study of the semileptonic decays $Λ_c^+\rightarrow pK^-e^+ν_e$, $Λ_c^+\rightarrow Λ(1520) e^+ν_e$ and $Λ_c^+\rightarrow Λ(1405) e^+ν_e$ is performed. The $Λ_c^+\rightarrow pK^-e^+ν_e$ decay is observed with a significance of $8.2σ$ and the branching fraction is measured to be $\mathcal{B}(Λ_c^+\rightarrow pK^- e^+ν_e)=(0.88\pm0.17_{\rm stat.}\pm0.07_{\rm syst.})\times 10^{-3}$. We also report evidence of $Λ_c^+\rightarrow Λ(1520)e^+ν_e$ and $Λ_c^+\rightarrow Λ(1405)e^+ν_e$ with significances of $3.3σ$ and $3.2σ$, respectively, and measure $\mathcal B(Λ^+_c\rightarrow Λ(1520)e^+ν_e)=(1.02\pm0.52_{\rm stat.}\pm0.11_{\rm syst.})\times10^{-3}$ and $\mathcal B(Λ^+_c\rightarrow Λ(1405)[\rightarrow pK^-]e^+ν_e)=(0.42\pm0.19_{\rm stat.}\pm0.04_{\rm syst.})\times10^{-3}$. Combining these with the inclusive semileptonic $Λ_c^+$ branching fraction measured by BESIII, the relative fraction is determined to be $[\mathcal{B}(Λ_c^+\rightarrow pK^-e^+ν_e)/\mathcal{B}(Λ_c^+\rightarrow X e^+ν_e)]=(2.1\pm0.4_{\rm stat.}\pm0.2_{\rm syst.})\%$, which provides a clear confirmation that semileptonic $Λ_c^+$ decays are not saturated by the $Λ\ell^+ν_{\ell}$ final state.

preprint2022arXiv

FRT-PAD: Effective Presentation Attack Detection Driven by Face Related Task

The robustness and generalization ability of Presentation Attack Detection (PAD) methods is critical to ensure the security of Face Recognition Systems (FRSs). However, in a real scenario, Presentation Attacks (PAs) are various and it is hard to predict the Presentation Attack Instrument (PAI) species that will be used by the attacker. Existing PAD methods are highly dependent on the limited training set and cannot generalize well to unknown PAI species. Unlike this specific PAD task, other face related tasks trained by huge amount of real faces (e.g. face recognition and attribute editing) can be effectively adopted into different application scenarios. Inspired by this, we propose to trade position of PAD and face related work in a face system and apply the free acquired prior knowledge from face related tasks to solve face PAD, so as to improve the generalization ability in detecting PAs. The proposed method, first introduces task specific features from other face related task, then, we design a Cross-Modal Adapter using a Graph Attention Network (GAT) to re-map such features to adapt to PAD task. Finally, face PAD is achieved by using the hierarchical features from a CNN-based PA detector and the re-mapped features. The experimental results show that the proposed method can achieve significant improvements in the complicated and hybrid datasets, when compared with the state-of-the-art methods. In particular, when training on the datasets OULU-NPU, CASIA-FASD, and Idiap Replay-Attack, we obtain HTER (Half Total Error Rate) of 5.48% for the testing dataset MSU-MFSD, outperforming the baseline by 7.39%.

preprint2022arXiv

Identifying the phase diagram structure for optimal information integration in morphogen systems

Gene regulatory networks (GRNs) perform a wide range of biological functions. It is, however, often challenging to reveal their functioning mechanism with the conventional approach focusing on the network topological structure from a bottom-up perspective. Here, we apply the top-down approach based on the optimality theory to study the information integration in morphogen systems, and show that the optimal integration strategy raises requirement on the phase diagram, rather than the topological structure, of a GRN. For the morphogen system in early fly embryos, our parameter-free model can quantitatively predict the patterning position shifts upon the dosage change of the morphogen Bicoid.

preprint2022arXiv

Incentive Mechanism Design for Emergency Frequency Control in Multi-Infeed Hybrid AC-DC System

In multi-infeed hybrid AC-DC (MIDC) systems, the emergency frequency control (EFC) with LCC-HVDC systems participating is of vital importance for system frequency stability. Nevertheless, when regional power systems are operated by different decision-makers, the LCC-HVDC systems and their connected AC systems might be unwilling to participate in the EFC due to the costs and losses. In this paper, to incentivize the LCC-HVDC systems and their connected adjacent AC systems to participate in the droop-based EFC, a novel control-parameter-based incentive mechanism is proposed, which can deal with various possible emergency frequency faults. Then, a non-cooperative-based incentive game model is formulated to implement the incentive mechanism in the MIDC system. An algorithm for seeking the Nash equilibrium is designed, and the uniqueness of Nash equilibrium is proven. Moreover, the individual rationality, incentive compatibility and social optimality of the proposed mechanism are analyzed and proven. The effectiveness of the proposed incentive mechanism is verified through a case study.

preprint2022arXiv

Instant tissue field and magnetic susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks

Quantitative susceptibility mapping (QSM) is a valuable MRI post-processing technique that quantifies the magnetic susceptibility of body tissue from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but amplify noise and errors. This study develops a large-stencil Laplacian preprocessed deep learning-based neural network for near instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MR phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the novel neural networks. The proposed iQFM and iQSM methods yielded comparable results to multi-step methods in healthy subjects while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. The reconstruction time was also substantially shortened from minutes using multi-step methods to only 30 milliseconds using the trained iQFM and iQSM neural networks.

preprint2022arXiv

Laser plasma accelerated ultra-intense electron beam for efficiently exciting nuclear isomers

Utilizing laser plasma wakefield to accelerate ultra-high charge electron beam is critical for many pioneering applications, for example to efficiently produce nuclear isomers with short lifetimes which may be widely used. However, because of the beam loading effect, electron charge in a single plasma bubble is limited in level of hundreds picocoulomb. Here, we experimentally present that a hundred kilo-ampere, twenty nanocoulomb, tens of MeV collimated electron beam is produced from a chain of wakefield acceleration, via a tightly focused intense laser pulse transversely matched in dense plasma. This ultra-intense electron beam ascribes to a novel efficient injection that the nitrogen atom inner shell electrons are ionized and continuously injected into multiple plasma bubbles. This intense electron beam has been utilized to exciting nuclear isomers with an ultra-high peak efficiency of $1.76\times10^{15}$ particles/s via photonuclear reactions. This efficient production method of isomers can be widely used for pumping isotopes with excited state lifetimes down to picosecond, which is benefit for deep understanding nuclear transition mechanisms and stimulating gamma-ray lasers.

preprint2022arXiv

Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects

The objective of this paper is to learn dense 3D shape correspondence for topology-varying generic objects in an unsupervised manner. Conventional implicit functions estimate the occupancy of a 3D point given a shape latent code. Instead, our novel implicit function produces a probabilistic embedding to represent each 3D point in a part embedding space. Assuming the corresponding points are similar in the embedding space, we implement dense correspondence through an inverse function mapping from the part embedding vector to a corresponded 3D point. Both functions are jointly learned with several effective and uncertainty-aware loss functions to realize our assumption, together with the encoder generating the shape latent code. During inference, if a user selects an arbitrary point on the source shape, our algorithm can automatically generate a confidence score indicating whether there is a correspondence on the target shape, as well as the corresponding semantic point if there is one. Such a mechanism inherently benefits man-made objects with different part constitutions. The effectiveness of our approach is demonstrated through unsupervised 3D semantic correspondence and shape segmentation.

preprint2022arXiv

Measurement of $e^{+}e^{-} \to K^{+}K^{-}π^{0}$ cross section and observation of a resonant structure

Based on $e^{+}e^{-}$ collision data collected by the BESIII detector at the BEPCII collider at center-of-mass energies from 2.000 to 3.080 GeV, a partial-wave analysis is performed for the process $e^{+}e^{-} \to K^{+}K^{-}π^{0}$. The Born cross section of the process $e^{+}e^{-} \to K^{+}K^{-}π^{0}$ and its subprocesses $e^{+}e^{-} \to ϕπ^{0}$, $K^{*}(892)K$ and $K^{*}_{2}(1430)K$ are measured. The results for $e^{+}e^{-} \to K^{+}K^{-}π^{0}$ and $ϕπ^{0}$ are consistent with the BaBar measurements and with improved precision. By analyzing the cross section, of the subprocesses $e^{+}e^{-} \to$ $K^{*}(892)K$ and $K^{*}_{2}(1430)K$, a structure with mass $M_R$ = (2208 $\pm$ 19 $\pm$ 24) MeV/$c^{2}$ and width $Γ_R$ = (168 $\pm$ 24 $\pm$ 39) MeV is observed with a combined statistical significance of 7.6$σ$. The measured resonance parameters suggest it can be identified as the $ϕ(2170)$, thus the results provide valuable input to understand the internal nature of this state.

preprint2022arXiv

Measurement of $Λ$ baryon polarization in $e^+e^-\rightarrowΛ\barΛ$ at $\sqrt{s} = 3.773$ GeV

Using a data sample of $ψ(3770)$ events collected with the BESIII detector at BEPCII corresponding to an integrated luminosity of 2.9 fb$^{-1}$, we report a measurement of $Λ$ spin polarization in $e^+e^-\rightarrowΛ\barΛ$ at $\sqrt{s} = 3.773$ GeV. The significance of polarization is found to be 2$σ$ including the systematic uncertainty, which implies a zero phase between the transition amplitudes of the $Λ\barΛ$ helicity states. This phase can be interpreted in terms of psionic form factors, and is determined to be $ΔΦ^Ψ$ = $Φ^Ψ_{E} - Φ^Ψ_{M}$ = $(71^{+66}_{-46}$ $\pm$ 5)$^{\circ}$. Similarly, the ratio between the form factors is found to be $R^ψ$ = $|G^Ψ_{E}/G^Ψ_{M}|$ = $0.48^{+0.12}_{-0.07}$ $\pm$ 0.04. The first uncertainties are statistical and the second systematic.

preprint2022arXiv

Measurement of the $D \to K^-π^+π^+π^-$ and $D \to K^-π^+π^0$ coherence factors and average strong-phase differences in quantum-correlated ${D\bar{D}}$ decays

The decays $D\to K^-π^+π^+π^-$ and $D \to K^-π^+π^0$ are studied in a sample of quantum-correlated $D\bar{D}$ pairs produced through the process $e^+e^- \to ψ(3770) \to D\bar{D}$, exploiting a data set collected by the BESIII experiment that corresponds to an integrated luminosity of 2.93 fb$^{-1}$. Here $D$ indicates a quantum superposition of a $D^0$ and a $\bar{D}^0$ meson. By reconstructing one neutral charm meson in a signal decay, and the other in the same or a different final state, observables are measured that contain information on the coherence factors and average strong-phase differences of each of the signal modes. These parameters are critical inputs in the measurement of the angle $γ$ of the Unitarity Triangle in $B^- \to DK^-$ decays at the LHCb and Belle II experiments. The coherence factors are determined to be $R_{K3π}=0.52^{+0.12}_{-0.10}$ and $R_{Kππ^0}=0.78 \pm 0.04$, with values for the average strong-phase differences that are $δ_D^{K3π}=\left(167^{+31}_{-19}\right)^\circ$ and $δ_D^{Kππ^0}=\left(196^{+14}_{-15}\right)^\circ$, where the uncertainties include both statistical and systematic contributions. The analysis is re-performed in four bins of the phase-space of the $D \to K^-π^+π^+π^-$ to yield results that will allow for a more sensitive measurement of $γ$ with this mode, to which the BESIII inputs will contribute an uncertainty of around 6$^\circ$.

preprint2022arXiv

Measurement of the branching fraction and decay asymmetry of $Λ\to nγ$

The radiative hyperon decay $Λ\to nγ$ is studied using $(10087\pm44)\times 10^6$ $J/ψ$ events collected with the BESIII detector operating at BEPCII. The absolute branching fraction of the decay $Λ\to nγ$ is determined with a significance of 5.6$σ$ to be $[0.832\pm0.038(\rm stat.)\pm0.054(\rm syst.)]\times10^{-3}$, which lies significantly below the current PDG value. By analyzing the joint angular distribution of the decay products, the first determination of the decay asymmetry $α_γ$ is reported with a value of $-0.16\pm0.10(\rm stat.)\pm0.05(\rm syst.)$.

preprint2022arXiv

Measurement of the branching fraction for $ψ(3686)\to ωK^0_SK^0_S$

Analyzing $(448.1\pm2.9)\times10^6$ $ψ(3686)$ events collected with the BESIII detector at the BEPCII collider, the $ψ(3686)\to ωK_{S}^{0}K_{S}^{0}$ decay is observed for the first time. The branching fraction for this decay is determined to be $\mathcal{B}_{ψ(3686)\to ωK_{S}^{0}K^{0}_{S}}$=$(7.04\pm0.39\pm0.36)$$\times10^{-5}$, where the first uncertainty is statistical and the second is systematic.

preprint2022arXiv

Measurement of the branching fraction of the doubly Cabibbo-suppressed decay $D^0\to K^+π^-π^0$ and search for $D^0\to K^+π^-π^0π^0$

Using $2.93\,\rm fb^{-1}$ of $e^+e^-$ collision data collected at a center-of-mass energy of 3.773\,GeV with the BESIII detector, we present a measurement of the branching fraction of the doubly Cabibbo-suppressed (DCS) decay $D^0\to K^+π^-π^0$ and a search for the DCS decay $D^0\to K^+π^-π^0π^0$. The branching fraction of $D^0\to K^+π^-π^0$ is determined to be $[3.13^{+0.60}_{-0.56}({\rm stat}) \pm 0.09({\rm syst})] \times 10^{-4}$. No signal is observed for $D^0\to K^+π^-π^0π^0$ and an upper limit of $3.6 \times 10^{-4}$ is set on the branching fraction at the 90\% C.L. We combine these results with the world-average branching fractions of their counterpart Cabibbo-favored decays to determine the ratios of the doubly Cabibbo-suppressed over the Cabibbo-favored branching fractions, ${\mathcal B}(D^0\to K^+π^-π^0)/{\mathcal B}(D^0\to K^-π^+π^0)=(0.22\pm 0.04)\%$~and ${\mathcal B}(D^0\to K^+π^-π^0π^0)/{\mathcal B}(D^0\to K^-π^+π^0π^0)<0.40\%$ at the 90\% C.L., which correspond to $(0.75\pm 0.14)\tan^{4} θ_C$~and $1.37\times \tan^{4} θ_C$, respectively, where $θ_C$ is the Cabibbo angle.

preprint2022arXiv

Measurement of the Cross Section for $e^{+}e^{-}\to$ hadrons at Energies from 2.2324 to 3.6710 GeV

Based on electron-positron collision data collected with the BESIII detector operating at the Beijing Electron Positron Collider II storage rings, the value of $R\equivσ(e^{+}e^{-}\to$hadrons)/$σ(e^{+}e^{-}\toμ^{+}μ^{-})$ is measured at 14 center-of-mass energies from 2.2324 to 3.6710 GeV. The resulting uncertainties are less than $3.0\%$, and are dominated by systematic uncertainties.

preprint2022arXiv

Measurement of the cross section of $e^{+}e^{-}\toηπ^{+}π^{-}$ at center-of-mass energies from 3.872 GeV to 4.700 GeV

Using data samples with an integrated luminosity of 19 fb$^{-1}$ at twenty-eight center-of-mass energies from 3.872 GeV to 4.700 GeV collected with the BESIII detector at the BEPCII electron--positron collider, the process $e^{+}e^{-}\toηπ^{+}π^{-}$ and the intermediate process $e^{+}e^{-}\toηρ^{0}$ are studied for the first time. The Born cross sections are measured. No significant resonance structure is observed in the cross section lineshape.

preprint2022arXiv

Measurement of the total and leptonic decay widths of the $J/ψ$ resonance with an energy scan method at BESIII

Using $e^+e^-$ annihilation data sets collected with the BESIII detector, we measure the cross sections of the processes $e^+e^- \to e^+e^-$ and $e^+e^- \to μ^+μ^-$ at fifteen center-of-mass energy points in the vicinity of the $J/ψ$ resonance. By a simultaneous fit to the measured, center-of-mass energy dependent cross sections of the two processes, the combined quantities $Γ_{ee} Γ_{ee} / Γ_{\rm tot}$ and $Γ_{ee} Γ_{μμ} / Γ_{\rm tot}$ are determined to be ($0.346 \pm 0.009$) and ($0.335 \pm 0.006$) keV, respectively, where $Γ_{ee}$, $Γ_{μμ}$, and $Γ_{\rm tot}$ are the electronic, muonic, and total decay widths of the $J/ψ$ resonance, respectively. Using the resultant $Γ_{ee} Γ_{μμ} / Γ_{\rm tot}$ and $Γ_{ee} Γ_{ee} / Γ_{\rm tot}$, the ratio $Γ_{ee} / Γ_{μμ}$ is calculated to be $1.031 \pm 0.015$, which is consistent with the expectation of lepton universality within about two standard deviations. Assuming lepton universality and using the branching fraction of the $J/ψ$ leptonic decay measured by BESIII in 2013, $Γ_{\rm tot}$ and $Γ_{ll}$ are determined to be ($93.0 \pm 2.1$) and ($5.56 \pm 0.11$) keV, respectively, where $Γ_{ll}$ is the average leptonic decay width of the $J/ψ$ resonance.

preprint2022arXiv

Measurements of Absolute Branching Fractions of $D^0\to K_L^0ϕ$, $K_L^0η$, $K_L^0ω$, and $K_L^0η^{\prime}$

We report the first measurements of the absolute branching fractions of $D^0\to K_L^0ϕ$, $D^0\to K_L^0η$, $D^0\to K_L^0ω$, and $D^0\to K_L^0η^{\prime}$, obtained by analyzing $2.93\,\rm fb^{-1}$ of $e^+e^-$ collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector. Taking the world averages of the branching fractions of $D^0\to K_S^0ϕ$, $D^0\to K_S^0η$, $D^0\to K_S^0ω$, and $D^0\to K_S^0η^{\prime}$, the $K_S^0$-$K_L^0$ asymmetry $\mathcal{R}(D^0)$ in these decay modes are obtained. The CP asymmetries in these decays are also determined. No significant $CP$ violation is observed.

preprint2022arXiv

Measurements of the absolute branching fractions of hadronic $D$-meson decays involving kaons and pions

By analyzing an electron-positron collision data sample corresponding to an integrated luminosity of $2.93\,\rm fb^{-1}$ taken at the center-of-mass energy of 3.773 GeV with the BESIII detector, we obtain for the first time the absolute branching fractions for seven $D^0$ and $D^+$ hadronic decay modes and search for the hadronic decay $D^0\to K^0_S K^0_Sπ^0$ with much improved sensitivity. The results are ${\mathcal B}(D^0\to K^0_Sπ^0π^0π^0 )=( 7.64\pm 0.30\pm 0.29)\times 10^{-3}$, ${\mathcal B}(D^0\to K^-π^+π^0π^0π^0 )=( 9.54\pm 0.30\pm 0.31)\times 10^{-3}$, ${\mathcal B}(D^0\to K^0_Sπ^+π^-π^0π^0)=(12.66\pm 0.45\pm 0.43)\times 10^{-3}$, ${\mathcal B}(D^+\to K^0_Sπ^+π^0π^0 )=(29.04\pm 0.62\pm 0.87)\times 10^{-3}$, ${\mathcal B}(D^+\to K^0_Sπ^+π^+π^-π^0)=(15.28\pm 0.57\pm 0.60)\times 10^{-3}$, ${\mathcal B}(D^+\to K^0_Sπ^+π^0π^0π^0)=( 5.54\pm 0.44\pm 0.32)\times 10^{-3}$, ${\mathcal B}(D^+\to K^-π^+π^+π^0π^0 )=( 4.95\pm 0.26\pm 0.19)\times 10^{-3}$, ${\mathcal B}({D^0\to K^0_S K^0_Sπ^0}) < 1.57 \times 10^{-4}$ at the 90\% confidence level. Here the first uncertainties are statistical and the second ones systematic. The newly studied decays greatly enrich the knowledge of the $D\to \bar Kπππ$ and $D\to \bar Kππππ$ hadronic decays, and open a bridge to access more two-body hadronic $D$ decays containing scalar, vector, axial and tensor mesons in the charm sector.

preprint2022arXiv

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data

In novel class discovery (NCD), we are given labeled data from seen classes and unlabeled data from unseen classes, and we train clustering models for the unseen classes. However, the implicit assumptions behind NCD are still unclear. In this paper, we demystify assumptions behind NCD and find that high-level semantic features should be shared among the seen and unseen classes. Based on this finding, NCD is theoretically solvable under certain assumptions and can be naturally linked to meta-learning that has exactly the same assumption as NCD. Thus, we can empirically solve the NCD problem by meta-learning algorithms after slight modifications. This meta-learning-based methodology significantly reduces the amount of unlabeled data needed for training and makes it more practical, as demonstrated in experiments. The use of very limited data is also justified by the application scenario of NCD: since it is unnatural to label only seen-class data, NCD is sampling instead of labeling in causality. Therefore, unseen-class data should be collected on the way of collecting seen-class data, which is why they are novel and first need to be clustered.

preprint2022arXiv

Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data

Modern kernel-based two-sample tests have shown great success in distinguishing complex, high-dimensional distributions with appropriate learned kernels. Previous work has demonstrated that this kernel learning procedure succeeds, assuming a considerable number of observed samples from each distribution. In realistic scenarios with very limited numbers of data samples, however, it can be challenging to identify a kernel powerful enough to distinguish complex distributions. We address this issue by introducing the problem of meta two-sample testing (M2ST), which aims to exploit (abundant) auxiliary data on related tasks to find an algorithm that can quickly identify a powerful test on new target tasks. We propose two specific algorithms for this task: a generic scheme which improves over baselines and a more tailored approach which performs even better. We provide both theoretical justification and empirical evidence that our proposed meta-testing schemes out-perform learning kernel-based tests directly from scarce observations, and identify when such schemes will be successful.

preprint2022arXiv

Multi-channel deep convolutional neural networks for multi-classifying thyroid disease

Thyroid disease instances have been continuously increasing since the 1990s, and thyroid cancer has become the most rapidly rising disease among all the malignancies in recent years. Most existing studies focused on applying deep convolutional neural networks for detecting thyroid cancer. Despite their satisfactory performance on binary classification tasks, limited studies have explored multi-class classification of thyroid disease types; much less is known of the diagnosis of co-existence situation for different types of thyroid diseases. Therefore, this study proposed a novel multi-channel convolutional neural network (CNN) architecture to address the multi-class classification task of thyroid disease. The multi-channel CNN merits from computed tomography to drive a comprehensive diagnostic decision for the overall thyroid gland, emphasizing the disease co-existence circumstance. Moreover, this study also examined alternative strategies to enhance the diagnostic accuracy of CNN models through concatenation of different scales of feature maps. Benchmarking experiments demonstrate the improved performance of the proposed multi-channel CNN architecture compared with the standard single-channel CNN architecture. More specifically, the multi-channel CNN achieved an accuracy of 0.909, precision of 0.944, recall of 0.896, specificity of 0.994, and F1 of 0.917, in contrast to the single-channel CNN, which obtained 0.902, 0.892, 0.909, 0.993, 0.898, respectively. In addition, the proposed model was evaluated in different gender groups; it reached a diagnostic accuracy of 0.908 for the female group and 0.901 for the male group. Collectively, the results highlight that the proposed multi-channel CNN has excellent generalization and has the potential to be deployed to provide computational decision support in clinical settings.

preprint2022arXiv

Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms

The theoretical analysis of multi-class classification has proved that the existing multi-class classification methods can train a classifier with high classification accuracy on the test set, when the instances are precise in the training and test sets with same distribution and enough instances can be collected in the training set. However, one limitation with multi-class classification has not been solved: how to improve the classification accuracy of multi-class classification problems when only imprecise observations are available. Hence, in this paper, we propose a novel framework to address a new realistic problem called multi-class classification with imprecise observations (MCIMO), where we need to train a classifier with fuzzy-feature observations. Firstly, we give the theoretical analysis of the MCIMO problem based on fuzzy Rademacher complexity. Then, two practical algorithms based on support vector machine and neural networks are constructed to solve the proposed new problem. Experiments on both synthetic and real-world datasets verify the rationality of our theoretical analysis and the efficacy of the proposed algorithms.

preprint2022arXiv

Nanomechanical Characterization of an Antiferromagnetic Topological Insulator

The antiferromagnetic topological insulator MnBi2Te4 (MBT) exhibits an ideal platform to study exotic topological phenomena and magnetic properties. The transport signatures of magnetic phase transitions in the MBT family materials have been well-studied. However, their mechanical properties and magneto-mechanical coupling have not been well-explored. We use nanoelectromechanical systems to study the intrinsic magnetism in MBT thin flakes via their magnetostrictive coupling. We investigate mechanical resonance signatures of magnetic phase transitions from antiferromagnetic (AFM) to canted antiferromagnetic (cAFM) to ferromagnetic (FM) phases versus magnetic field at different temperatures. The spin-flop transitions in MBT are revealed by frequency shifts of mechanical resonance. With temperatures going above TN, the transitions disappear in the resonance frequency map, consistent with transport measurements. We use a magnetostrictive model to correlate the frequency shifts with the spin-canting states. Our work demonstrates a technique to study magnetic phase transitions, magnetization and magnetoelastic properties of the magnetic topological insulator.

preprint2022arXiv

Negative Interatomic Spring Constant Manifested by Topological Phonon Flat Band

Phonons as bosons are different from electrons as fermions. Unlike interatomic electron hopping that can be either positive or negative and further tuned by spin-orbit coupling, interatomic spring constant is positive, or the structure of atomic lattices would be dynamically unstable. Surprisingly, we found that topological phonon flat bands (FBs) can manifest either a positive or negative interatomic spring constant that couples the FB-modes of opposite chirality, as exemplified by first-principles calculations of a 2D material of Kagome-BN. To reveal its physical origin, we first establish a fundamental correspondence between a collective lattice-coupling (CLC) variable of two quasi-particle states (e.g., electronic states or phonon modes) of opposite parity in a periodic lattice with band topology. Topological semimetals arise with zero CLC at special k-points protected by symmetry; while positive and negative CLC at these k-points gives rise to normal and topological insulators, respectively. Then, we show topological FB has a special form of CLC that vanishes at all k-points as characterized by its real-space wave function, and multi-atom FB phonon mode can manifest effectively a negative interatomic spring constant. Our findings shed new light on our fundamental understanding of topology and provide a practical design principle for creating artificial bosonic topological states.

preprint2022arXiv

Neighborhood Collective Estimation for Noisy Label Identification and Correction

Learning with noisy labels (LNL) aims at designing strategies to improve model performance and generalization by mitigating the effects of model overfitting to noisy labels. The key success of LNL lies in identifying as many clean samples as possible from massive noisy data, while rectifying the wrongly assigned noisy labels. Recent advances employ the predicted label distributions of individual samples to perform noise verification and noisy label correction, easily giving rise to confirmation bias. To mitigate this issue, we propose Neighborhood Collective Estimation, in which the predictive reliability of a candidate sample is re-estimated by contrasting it against its feature-space nearest neighbors. Specifically, our method is divided into two steps: 1) Neighborhood Collective Noise Verification to separate all training samples into a clean or noisy subset, 2) Neighborhood Collective Label Correction to relabel noisy samples, and then auxiliary techniques are used to assist further model optimization. Extensive experiments on four commonly used benchmark datasets, i.e., CIFAR-10, CIFAR-100, Clothing-1M and Webvision-1.0, demonstrate that our proposed method considerably outperforms state-of-the-art methods.

preprint2022arXiv

Observation of $a_0(1710)^+ \to K_S^0K^+$ in study of the $D_s^+\to K_S^0K^+π^0$ decay

Using $e^+e^-$ annihilation data corresponding to an integrated luminosity of 6.32 fb$^{-1}$ collected at center-of-mass energies between 4.178 GeV and 4.226 GeV with the BESIII detector, we perform the first amplitude analysis of the decay $D_s^+\to K_S^0K^+π^0$ and determine the relative branching fractions and phases for intermediate processes. We observe the $a_0(1710)^+$, the isovector partner of the $f_0(1710)$ and $f_0(1770)$ mesons, in its decay to $K_S^0K^+$ for the first time. In addition, we measure the ratio $\frac{\mathcal{B}(D_{s}^{+} \to \bar{K}^{*}(892)^{0}K^{+})}{\mathcal{B}(D_{s}^{+} \to \bar{K}^{0}K^{*}(892)^{+})}$ to be $2.35^{+0.42}_{-0.23\text{stat.}}\pm 0.10_{\rm syst.}$. Finally, we provide a precision measurement of the absolute branching fraction $\mathcal{B}(D_s^+\to K_S^0K^+π^0) = (1.46\pm 0.06_{\text{stat.}}\pm 0.05_{\text{syst.}})\%$.

preprint2022arXiv

Observation of $η_c(2S) \to 3(π^+π^-)$ and measurements of $χ_{cJ} \to 3(π^+π^-)$ in $ψ(3686)$ radiative transitions

The hadronic decay $η_c(2S) \to 3(π^+π^-)$ is observed with a statistical significance of 9.3 standard deviations using $(448.1\pm2.9)\times10^6$ $ψ(3686)$ events collected by the BESIII detector at the BEPCII collider. The measured mass and width of $η_c(2S)$ are $(3643.4 \pm 2.3 (\rm stat.) \pm 4.4 (\rm syst.))$ MeV/$c^2$ and $(19.8 \pm 3.9 (\rm stat.) \pm 3.1 (\rm syst.))$ MeV, respectively, which are consistent with the world average values within two standard deviations. The product branching fraction $\mathcal{B}[ψ(3686)\to γη_c(2S)]\times\mathcal{B}[η_c(2S)\to3(π^+π^-)]$ is measured to be $(9.2 \pm 1.0 (\rm stat.) \pm 0.9 (\rm syst.))\times10^{-6}$. Using $\mathcal{B}[ψ(3686)\to γη_c(2S)]=(7.0^{+3.4}_{-2.5})\times10^{-4}$, we obtain $\mathcal{B}[η_c(2S) \to 3(π^+π^-)] = (1.31 \pm 0.15 (\rm stat.) \pm 0.13 (\rm syst.)(^{+0.64}_{-0.47}) (\rm extr))\times10^{-2}$, where the third uncertainty is from $\mathcal{B}[ψ(3686) \to γη_c(2S)]$. We also measure the $χ_{cJ} \to 3(π^+π^-)$ ($J=0, 1, 2$) decays via $ψ(3686) \to γχ_{cJ}$ transitions. The branching fractions are $\mathcal{B}[χ_{c0} \to 3(π^+π^-)] = (2.080\pm0.006 (\rm stat.)\pm0.068 (\rm syst.))\times10^{-2}$, $\mathcal{B}[χ_{c1} \to 3(π^+π^-)] = (1.092\pm0.004 (\rm stat.)\pm0.035 (\rm syst.))\times10^{-2}$, and $\mathcal{B}[χ_{c2} \to 3(π^+π^-)] = (1.565\pm0.005 (\rm stat.)\pm0.048 (\rm syst.))\times10^{-2}$.

preprint2022arXiv

Observation of resonance structures in $e^+e^-\to π^+π^-ψ_2(3823)$ and mass measurement of $ψ_2(3823)$

Using a data sample corresponding to an integrated luminosity of 11.3 $\rm fb^{-1}$ collected at center-of-mass energies from $4.23$ to $4.70$ GeV with the BESIII detector, we measure the product of the $e^+e^-\to π^+π^-ψ_2(3823)$ cross section and the branching fraction $\mathcal{B}[ψ_2(3823)\to γχ_{c1}]$. For the first time, resonance structure is observed in the cross section line shape of $e^+e^-\to π^+π^-ψ_2(3823)$ with significances exceeding $5σ$. A fit to data with two coherent Breit-Wigner resonances modeling the $\sqrt{s}$-dependent cross section yields $M(R_1)=4406.9\pm 17.2\pm 4.5$ MeV/$c^2$, $Γ(R_1)=128.1\pm 37.2\pm 2.3$ MeV, and $M(R_2)=4647.9\pm 8.6\pm 0.8$ MeV/$c^2$, $Γ(R_2)=33.1\pm 18.6\pm 4.1$ MeV. Though weakly disfavored by the data, a single resonance with $M(R)=4417.5\pm26.2\pm3.5$ MeV/$c^2$, $Γ(R)=245\pm48\pm13$ MeV is also possible to interpret data. This observation deepens our understanding of the nature of the vector charmoniumlike states. The mass of the $ψ_2(3823)$ state is measured as $(3823.12\pm 0.43\pm 0.13)$ MeV/$c^2$, which is the most precise measurement to date.

preprint2022arXiv

Observation of the double Dalitz decay $η'\to e^+e^-e^+e^-$

Based on $(10087 \pm 44)\times10^6$ $J/ψ$ events collected with the BESIII detector at BEPCII, the double Dalitz decay $η'\to e^+e^-e^+e^-$ is observed for the first time via the $J/ψ\toγη'$ decay process. The significance is found to be 5.7$σ$ with systematic uncertainties taken into consideration. Its branching fraction is determined to be $\mathcal{B}(η'\to e^+ e^- e^+ e^-) =(4.5\pm1.0(\mathrm{stat.})\pm0.5(\mathrm{sys.})) \times 10^{-6}$.

preprint2022arXiv

Observation of the electromagnetic Dalitz decay $D^{\ast 0}\to D^{0}e^{+}e^{-}$

Based on 3.19 fb$^{-1}$ of $e^+e^-$ collision data accumulated at the center-of-mass energy 4.178 GeV with the BESIII detector operating at the BEPCII collider, the electromagnetic Dalitz decay $D^{\ast 0}\to D^{0}e^{+}e^{-}$ is observed for the first time with a statistical significance of $13.2σ$. The ratio of the branching fraction of $D^{\ast 0}\to D^{0}e^{+}e^{-}$ to that of $D^{\ast 0}\to D^{0} γ$ is measured to be $(11.08\pm0.76\pm0.49)\times 10^{-3}$. By using the world average value of the branching fraction of $D^{\ast 0}\to D^{0} γ$, the branching fraction of $D^{\ast 0}\to D^{0}e^{+}e^{-}$ is determined to be $(3.91\pm0.27\pm0.17\pm0.10)\times 10^{-3}$, where the first uncertainty is statistical, the second systematic and the third external branching fractions.

preprint2022arXiv

Observation of the Singly Cabibbo-Suppressed Decay $Λ_{c}^{+} \to nπ^{+}$

The singly Cabibbo-suppressed decay $Λ_{c}^{+} \to nπ^{+}$ is observed for the first time with a statistical significance of $7.3σ$ by using 3.9 $\mathrm{fb}^{-1}$ of $e^{+}e^{-}$ collision data collected at center-of-mass energies between 4.612 and 4.699 GeV with the BESIII detector at BEPCII. The branching fraction of $Λ_{c}^{+} \to nπ^{+}$ is measured to be $(6.6\pm1.2_{\rm stat}\pm0.4_{\rm syst})\times 10^{-4}$. By taking the upper limit of branching fractions of $Λ_{c}^{+} \to pπ^0$ from the Belle experiment, the ratio of branching fractions between $Λ_{c}^{+} \to nπ^{+}$ and $Λ_{c}^{+} \to pπ^0$ is calculated to be larger than 7.2 at the 90% confidence level, which disagrees with the current predictions of available phenomenological models. In addition, the branching fractions of the Cabibbo-favored decays $Λ_{c}^{+} \to Λπ^{+}$ and $Λ_{c}^{+} \to Σ^{0}π^{+}$ are measured to be $(1.31\pm0.08_{\rm stat}\pm0.05_{\rm syst})\times 10^{-2}$ and $(1.22\pm0.08_{\rm stat}\pm0.07_{\rm syst})\times 10^{-2}$, respectively, which are consistent with previous results.

preprint2022arXiv

On Nash-Stackelberg-Nash Games under Decision-Dependent Uncertainties: Model and Equilibrium

In this paper, we discuss a class of two-stage hierarchical games with multiple leaders and followers, which is called Nash-Stackelberg-Nash (N-S-N) games. Particularly, we consider N-S-N games under decision-dependent uncertainties (DDUs). DDUs refer to the uncertainties that are affected by the strategies of decision-makers and have been rarely addressed in game equilibrium analysis. In this paper, we first formulate the N-S-N games with DDUs of complete ignorance, where the interactions between the players and DDUs are characterized by uncertainty sets that depend parametrically on the players' strategies. Then, a rigorous definition for the equilibrium of the game is established by consolidating generalized Nash equilibrium and Pareto-Nash equilibrium. Afterward, we prove the existence of the equilibrium of N-S-N games under DDUs by applying Kakutani's fixed-point theorem. Finally, an illustrative example is provided to show the impact of DDUs on the equilibrium of N-S-N games.

preprint2022arXiv

Orbital Design of Flat Bands in Non-Line-Graph Lattices via Line-Graph Wavefunctions

Line-graph (LG) lattices are known for having flat bands (FBs) from the destructive interference of Bloch wavefunctions encoded in pure lattice symmetry. Here, we develop a generic atomic/molecular orbital design principle for FBs in non-LG lattices. Based on linear-combination-of-atomic-orbital (LCAO) theory, we demonstrate that the underlying wavefunction symmetry of FBs in a LG lattice can be transformed into the atomic/molecular orbital symmetry in a non-LG lattice. We illustrate such orbital-designed topological FBs in three 2D non-LG, square, trigonal, and hexagonal lattices, where the designed orbitals faithfully reproduce the corresponding lattice symmetries of checkerboard, Kagome, and diatomic-Kagome lattices, respectively. Interestingly, systematic design of FBs with a high Chern number is also achieved based on the same principle. Fundamentally our theory enriches the FB physics; practically it significantly expands the scope of FB materials, since most materials have multiple atomic/molecular orbitals at each lattice site, rather than a single s orbital mandated in graph theory and generic lattice models.

preprint2022arXiv

Partial wave analysis of $J/ψ\to γη^{\prime} η^{\prime}$

Using a sample of $(10.09~\pm~0.04)\times10^{9} ~J/ψ$ events collected with the BESIII detector, a partial wave analysis of $J/ψ\toγη^{\prime}η^{\prime}$ is performed. The masses and widths of the observed resonances and their branching fractions are reported. The main contribution is from $J/ψ\rightarrowγf_0(2020)$ with $f_0(2020)\rightarrowη^{\prime}η^{\prime}$, which is found with a significance of greater than 25$σ$. The product branching fraction ${\cal B}\left(J/ψ\rightarrowγf_0(2020)\right)\cdot{\cal B}\left(f_0(2020)\rightarrowη^{\prime}η^{\prime}\right)$ is measured to be $(2.63\pm0.06({\rm stat.})^{+0.31}_{-0.46}({\rm syst.}))\times10^{-4}$.

preprint2022arXiv

Practical considerations for the effect of finite coverage on the azimuthal dependence of global spin alignment

The global spin alignment of vector mesons is a powerful probe to study the vorticity field of the system produced in non-central relativistic heavy-ion collisions. Since the experimental observables of global spin alignment are sensitive to many factors, proper corrections are need to be taken care of when measuring the global spin alignment of vector mesons. In this paper, we propose a method to correct the effect of finite pseudo-rapidity coverage when extract the azimuthal dependence of spin alignment parameter $ρ_{00}$. The effects of the finite pseudo-rapidity coverage on the azimuthal dependence of $ϕ$ meson spin alignment and the potentially exist intrinsic spin alignment effects are taken into consideration. The method presented in this paper is verified in a Monte-Carlo simulation, it allows the measurements of azimuthal dependence of global spin alignment to be conducted properly and accurately.

preprint2022arXiv

Probabilistic Margins for Instance Reweighting in Adversarial Training

Reweighting adversarial data during training has been recently shown to improve adversarial robustness, where data closer to the current decision boundaries are regarded as more critical and given larger weights. However, existing methods measuring the closeness are not very reliable: they are discrete and can take only a few values, and they are path-dependent, i.e., they may change given the same start and end points with different attack paths. In this paper, we propose three types of probabilistic margin (PM), which are continuous and path-independent, for measuring the aforementioned closeness and reweighting adversarial data. Specifically, a PM is defined as the difference between two estimated class-posterior probabilities, e.g., such the probability of the true label minus the probability of the most confusing label given some natural data. Though different PMs capture different geometric properties, all three PMs share a negative correlation with the vulnerability of data: data with larger/smaller PMs are safer/riskier and should have smaller/larger weights. Experiments demonstrate that PMs are reliable measurements and PM-based reweighting methods outperform state-of-the-art methods.

preprint2022arXiv

Robust Representation via Dynamic Feature Aggregation

Deep convolutional neural network (CNN) based models are vulnerable to the adversarial attacks. One of the possible reasons is that the embedding space of CNN based model is sparse, resulting in a large space for the generation of adversarial samples. In this study, we propose a method, denoted as Dynamic Feature Aggregation, to compress the embedding space with a novel regularization. Particularly, the convex combination between two samples are regarded as the pivot for aggregation. In the embedding space, the selected samples are guided to be similar to the representation of the pivot. On the other side, to mitigate the trivial solution of such regularization, the last fully-connected layer of the model is replaced by an orthogonal classifier, in which the embedding codes for different classes are processed orthogonally and separately. With the regularization and orthogonal classifier, a more compact embedding space can be obtained, which accordingly improves the model robustness against adversarial attacks. An averaging accuracy of 56.91% is achieved by our method on CIFAR-10 against various attack methods, which significantly surpasses a solid baseline (Mixup) by a margin of 37.31%. More surprisingly, empirical results show that, the proposed method can also achieve the state-of-the-art performance for out-of-distribution (OOD) detection, due to the learned compact feature space. An F1 score of 0.937 is achieved by the proposed method, when adopting CIFAR-10 as in-distribution (ID) dataset and LSUN as OOD dataset. Code is available at https://github.com/HaozheLiu-ST/DynamicFeatureAggregation.

preprint2022arXiv

Search for $X(3872)\toπ^0χ_{c0}$ and $X(3872)\toππχ_{c0}$ at BESIII

Using 9.9 fb$^{-1}$ of $e^+e^-$ collision data collected by the BESIII detector at center-of-mass energies between 4.15 and 4.30 GeV, we search for the processes $e^+e^-\toγX(3872)$ with $X(3872)\rightarrowπ^0χ_{c0}$ and $X(3872)\rightarrowππχ_{c0}$. Depending on the fitting model, the statistical significance for $X(3872)\toπ^0χ_{c0}$ ranges from 1.3$σ$ to 2.8$σ$. We set upper limits (at 90\% C.L.) of $\frac{\mathcal{B}(X(3872)\rightarrowπ^0χ_{c0})}{\mathcal{B}(X(3872)\toπ^+π^-J/ψ)}<3.6$, $\frac{\mathcal{B}(X(3872)\rightarrowπ^+π^-χ_{c0})}{\mathcal{B}(X(3872)\toπ^+π^-J/ψ)}<0.68$, and $\frac{\mathcal{B}(X(3872)\rightarrowπ^0π^0χ_{c0})}{\mathcal{B}(X(3872)\toπ^+π^-J/ψ)}<1.7$. Combined with the BESIII measurement of $X(3872)\toπ^0χ_{c1}$, we also set an upper limit of $\frac{\mathcal{B}(X(3872)\rightarrowπ^0χ_{c0})}{\mathcal{B}(X(3872)\toπ^0χ_{c1})}<4.4$.

preprint2022arXiv

Search for baryon and lepton number violating decays $D^{0}\to \bar{p}e^{+}$ and $D^{0}\to pe^{-}$

Using an electron-positron collision data sample corresponding to an integrated luminosity of 2.93~fb$^{-1}$ collected with the BESIII detector at a center-of-mass energy of 3.773 GeV, we search for the baryon and lepton number violating decays $D^{0}\to \bar{p}e^{+}$ and $D^{0}\to pe^{-}$. No obvious signals are found with the current statistics. The upper limits on the branching fractions for $D^{0}\to \bar{p}e^{+}$ and $D^{0}\to pe^{-}$ are set to be $1.2\times 10^{-6}$ and $2.2\times 10^{-6}$ at 90\% confidence level, respectively.

preprint2022arXiv

Search for baryon and lepton number violation decay $D^{\pm}\to n(\bar{n})e^{\pm}$

Using a data set of electron-positron collisions corresponding to an integrated luminosity of ${\rm 2.93~fb^{-1}}$ taken with the BESIII detector at a center-of-mass energy of 3.773 GeV, a search for the baryon ($B$) and lepton ($L$) number violating decays $D^{\pm}\to n(\bar{n})e^{\pm}$ is performed. No signal is observed and the upper limits on the branching fractions at the $90\%$ confidence level are set to be $1.43\times10^{-5}$ for the decays $D^{+(-)}\to \bar{n}(n)e^{+(-)}$ with $Δ|B-L|=0$, and $2.91\times10^{-5}$ for the decays $D^{+(-)}\to n(\bar{n})e^{+(-)}$ with $Δ|B-L|=2$ , where $Δ|B-L|$ denotes the change in the difference between baryon and lepton numbers.

preprint2022arXiv

Search for invisible decays of the $Λ$ baryon

A search for invisible decays of the $Λ$ baryon is carried out in the process $J/ψ\toΛ\barΛ$ based on $(1.0087\pm0.0044)\times10^{10}$ $J/ψ$ events collected with the BESIII detector located at the BEPCII storage ring. No signals are found for the invisible decays of $Λ$ baryon, and the upper limit of the branching fraction is determined to be $7.4 \times 10^{-5}$ at the 90% confidence level. This is the first search for invisible decays of baryons; such searches will play an important role in constraining dark sector models related to the baryon asymmetry.

preprint2022arXiv

Search for new hadronic decays of $h_{c}$ and observation of $h_{c}\to p\bar{p}η$

A search for the hadronic decays of the $h_{c}$ meson to the final states $p\bar{p}π^{+}π^{-}π^{0}$, $p\bar{p}η$, and $p\bar{p}π^0$ via the process $ψ(3686) \to π^{0}{h_c}$ is performed using $(4.48\pm0.03)\times10^{8}$ $ψ(3686)$ events collected with the BESIII detector. The decay channel $h_{c}\to p\bar{p}η$ is observed for the first time with a significance greater than $5σ$ and a branching fraction of $\left( {6.41 \pm 1.74 \pm 0.53 \pm 1.00} \right) \times {10^{ -4}}$, where the uncertainties are statistical, systematic, and that from the branching fraction of $ψ(3686)\toπ^{0}h_{c}$. Strong evidence for the decay ${h_c} \to p\bar{p}{π^+}{π^-}{π^0}$ is found with a significance of $4.9σ$ and a branching fraction of $\left( {3.84 \pm 0.83 \pm0.69} \pm 0.58 \right) \times {10^{ - 3}}$. The significances include systematic uncertainties. No clear signal of the decay $h_c\to p\bar{p}π^{0}$ is found, and an upper limit of $6.59\times 10^{-4}$ on its branching fraction is set at the 90% confidence level.

preprint2022arXiv

Search for the decay $D^{0} \to π^{0} ν\barν$

We present the first experimental search for the rare charm decay $D^{0} \to π^{0} ν\barν$. It is based on an $e^+e^-$ collision sample consisting of $10.6\times10^{6}$ pairs of $D^0\bar{D}^0$ mesons collected by the BESIII detector at $\sqrt{s}$=3.773 GeV, corresponding to an integrated luminosity of 2.93~fb$^{-1}$. A data-driven method is used to ensure the reliability of the background modeling. No significant $D^{0} \to π^{0} ν\barν$ signal is observed in data and an upper limit of the branching fraction is set to be $2.1\times 10^{-4}$ at the 90$\%$ confidence level. This is the first experimental constraint on charmed-hadron decays into dineutrino final states.

preprint2022arXiv

Search for the decay $h_c\rightarrowπ^0J/ψ$

A search for the decay $h_c\rightarrowπ^0J/ψ$ is performed using a sample of $h_c$ produced in the reaction $e^+e^-\rightarrowπ^+π^-h_c$. The data samples were collected with the BESIII detector at center-of-mass energies between 4.189 and 4.437 GeV, corresponding to a total integrated luminosity of 11 fb$^{-1}$. No significant signal is observed. Upper limits on the branching ratio $\mathcal{B}(h_c\rightarrowπ^0J/ψ)/\mathcal{B}(h_c\rightarrowγη_c\rightarrowγK^+K^-π^0)$ and on the branching fraction $\mathcal{B}(h_c\rightarrowπ^0J/ψ)$ are determined to be $7.5\times10^{-2}$ and $4.7\times10^{-4}$ at $90\%$ confidence level, respectively. The latter is derived from the former using the measured branching fraction of the normalization channel. This is the first determination of the upper limit of the decay $h_c\rightarrowπ^0J/ψ$.

preprint2022arXiv

Shift-tolerant Perceptual Similarity Metric

Existing perceptual similarity metrics assume an image and its reference are well aligned. As a result, these metrics are often sensitive to a small alignment error that is imperceptible to the human eyes. This paper studies the effect of small misalignment, specifically a small shift between the input and reference image, on existing metrics, and accordingly develops a shift-tolerant similarity metric. This paper builds upon LPIPS, a widely used learned perceptual similarity metric, and explores architectural design considerations to make it robust against imperceptible misalignment. Specifically, we study a wide spectrum of neural network elements, such as anti-aliasing filtering, pooling, striding, padding, and skip connection, and discuss their roles in making a robust metric. Based on our studies, we develop a new deep neural network-based perceptual similarity metric. Our experiments show that our metric is tolerant to imperceptible shifts while being consistent with the human similarity judgment.

preprint2022arXiv

SNeRF: Stylized Neural Implicit Representations for 3D Scenes

This paper presents a stylized novel view synthesis method. Applying state-of-the-art stylization methods to novel views frame by frame often causes jittering artifacts due to the lack of cross-view consistency. Therefore, this paper investigates 3D scene stylization that provides a strong inductive bias for consistent novel view synthesis. Specifically, we adopt the emerging neural radiance fields (NeRF) as our choice of 3D scene representation for their capability to render high-quality novel views for a variety of scenes. However, as rendering a novel view from a NeRF requires a large number of samples, training a stylized NeRF requires a large amount of GPU memory that goes beyond an off-the-shelf GPU capacity. We introduce a new training method to address this problem by alternating the NeRF and stylization optimization steps. Such a method enables us to make full use of our hardware memory capacity to both generate images at higher resolution and adopt more expressive image style transfer methods. Our experiments show that our method produces stylized NeRFs for a wide range of content, including indoor, outdoor and dynamic scenes, and synthesizes high-quality novel views with cross-view consistency.

preprint2022arXiv

The State of Aerial Surveillance: A Survey

The rapid emergence of airborne platforms and imaging sensors are enabling new forms of aerial surveillance due to their unprecedented advantages in scale, mobility, deployment and covert observation capabilities. This paper provides a comprehensive overview of human-centric aerial surveillance tasks from a computer vision and pattern recognition perspective. It aims to provide readers with an in-depth systematic review and technical analysis of the current state of aerial surveillance tasks using drones, UAVs and other airborne platforms. The main object of interest is humans, where single or multiple subjects are to be detected, identified, tracked, re-identified and have their behavior analyzed. More specifically, for each of these four tasks, we first discuss unique challenges in performing these tasks in an aerial setting compared to a ground-based setting. We then review and analyze the aerial datasets publicly available for each task, and delve deep into the approaches in the aerial literature and investigate how they presently address the aerial challenges. We conclude the paper with discussion on the missing gaps and open research questions to inform future research avenues.

preprint2022arXiv

TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation

In few-shot domain adaptation (FDA), classifiers for the target domain are trained with accessible labeled data in the source domain (SD) and few labeled data in the target domain (TD). However, data usually contain private information in the current era, e.g., data distributed on personal phones. Thus, the private information will be leaked if we directly access data in SD to train a target-domain classifier (required by FDA methods). In this paper, to thoroughly prevent the privacy leakage in SD, we consider a very challenging problem setting, where the classifier for the TD has to be trained using few labeled target data and a well-trained SD classifier, named few-shot hypothesis adaptation (FHA). In FHA, we cannot access data in SD, as a result, the private information in SD will be protected well. To this end, we propose a target orientated hypothesis adaptation network (TOHAN) to solve the FHA problem, where we generate highly-compatible unlabeled data (i.e., an intermediate domain) to help train a target-domain classifier. TOHAN maintains two deep networks simultaneously, where one focuses on learning an intermediate domain and the other takes care of the intermediate-to-target distributional adaptation and the target-risk minimization. Experimental results show that TOHAN outperforms competitive baselines significantly.

preprint2022arXiv

Undersampled MRI Reconstruction with Side Information-Guided Normalisation

Magnetic resonance (MR) images exhibit various contrasts and appearances based on factors such as different acquisition protocols, views, manufacturers, scanning parameters, etc. This generally accessible appearance-related side information affects deep learning-based undersampled magnetic resonance imaging (MRI) reconstruction frameworks, but has been overlooked in the majority of current works. In this paper, we investigate the use of such side information as normalisation parameters in a convolutional neural network (CNN) to improve undersampled MRI reconstruction. Specifically, a Side Information-Guided Normalisation (SIGN) module, containing only few layers, is proposed to efficiently encode the side information and output the normalisation parameters. We examine the effectiveness of such a module on two popular reconstruction architectures, D5C5 and OUCR. The experimental results on both brain and knee images under various acceleration rates demonstrate that the proposed method improves on its corresponding baseline architectures with a significant margin.

preprint2021arXiv

Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation

In unsupervised domain adaptation (UDA), classifiers for the target domain (TD) are trained with clean labeled data from the source domain (SD) and unlabeled data from TD. However, in the wild, it is difficult to acquire a large amount of perfectly clean labeled data in SD given limited budget. Hence, we consider a new, more realistic and more challenging problem setting, where classifiers have to be trained with noisy labeled data from SD and unlabeled data from TD -- we name it wildly UDA (WUDA). We show that WUDA ruins all UDA methods if taking no care of label noise in SD, and to this end, we propose a Butterfly framework, a powerful and efficient solution to WUDA. Butterfly maintains four deep networks simultaneously, where two take care of all adaptations (i.e., noisy-to-clean, labeled-to-unlabeled, and SD-to-TD-distributional) and then the other two can focus on classification in TD. As a consequence, Butterfly possesses all the conceptually necessary components for solving WUDA. Experiments demonstrate that, under WUDA, Butterfly significantly outperforms existing baseline methods.

preprint2021arXiv

Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation

In unsupervised domain adaptation (UDA), classifiers for the target domain are trained with massive true-label data from the source domain and unlabeled data from the target domain. However, it may be difficult to collect fully-true-label data in a source domain given a limited budget. To mitigate this problem, we consider a novel problem setting where the classifier for the target domain has to be trained with complementary-label data from the source domain and unlabeled data from the target domain named budget-friendly UDA (BFUDA). The key benefit is that it is much less costly to collect complementary-label source data (required by BFUDA) than collecting the true-label source data (required by ordinary UDA). To this end, the complementary label adversarial network (CLARINET) is proposed to solve the BFUDA problem. CLARINET maintains two deep networks simultaneously, where one focuses on classifying complementary-label source data and the other takes care of the source-to-target distributional adaptation. Experiments show that CLARINET significantly outperforms a series of competent baselines.

preprint2021arXiv

Convergence Analysis of Dual Decomposition Algorithm in Distributed Optimization: Asynchrony and Inexactness

Dual decomposition is widely utilized in distributed optimization of multi-agent systems. In practice, the dual decomposition algorithm is desired to admit an asynchronous implementation due to imperfect communication, such as time delay and packet drop. In addition, computational errors also exist when individual agents solve their own subproblems. In this paper, we analyze the convergence of the dual decomposition algorithm in distributed optimization when both the asynchrony in communication and the inexactness in solving subproblems exist. We find that the interaction between asynchrony and inexactness slows down the convergence rate from $\mathcal{O} ( 1 / k )$ to $\mathcal{O} ( 1 / \sqrt{k} )$. Specifically, with a constant step size, the value of objective function converges to a neighborhood of the optimal value, and the solution converges to a neighborhood of the exact optimal solution. Moreover, the violation of the constraints diminishes in $\mathcal{O} ( 1 / \sqrt{k} )$. Our result generalizes and unifies the existing ones that only consider either asynchrony or inexactness. Finally, numerical simulations validate the theoretical results.

preprint2021arXiv

Cross section measurements of the $e^+e^-\to D^{+}D^{-}$ and $e^+e^-\to D^{*+}D^{-}$ processes at center-of-mass energies from 4.085 to 4.600 GeV

The Born cross sections of the $e^+e^-\to D^{*+}D^{*-}$ and $e^+e^-\to D^{*+}D^{-}$ processes are measured using $e^+e^-$ collision data collected with the BESIII experiment at center-of-mass energies from 4.085 to 4.600 GeV, corresponding to an integrated luminosity of $15.7~{\rm fb}^{-1}$. The results are consistent with and more precise than the previous measurements by the Belle, Babar and CLEO collaborations. The measurements are essential for understanding the nature of vector charmonium and charmonium-like states.

preprint2021arXiv

Cross sections for the reactions $e^+e^-\rightarrow K^+K^-π^+π^-(π^0)$, $K^+K^-K^+K^-(π^0)$, $π^+π^-π^+π^-(π^0)$, $p\bar{p}π^+π^-(π^0)$ in the energy region between 3.773 and 4.600 GeV

Using the data samples collected in the energy range from 3.773 to 4.600 GeV with the BESIII detector at the BEPCII collider, we measure the dressed cross sections as a function of center-of-mass energy for $e^+e^-\rightarrow K^+K^-π^+π^-(π^0)$, $K^+K^-K^+K^-(π^0)$, $π^+π^-π^+π^-(π^0)$, and $p\bar{p}π^+π^-(π^0)$. The cross sections for $e^+e^-\rightarrow K^+K^-K^+K^-π^0$, $p\bar{p}π^+π^-(π^0)$ are the first measurements. Cross sections for the other five channels are much more precise than previous results in this energy region. We also search for charmonium and charmonium-like resonances, such as the $Y(4230)$, decaying into the same final states. We find evidence of the $ψ(4040)$ decaying to $π^+π^-π^+π^-π^0$ with a statistical significance of $3.6σ$. Upper limits are provided for other decays since no clear signals are observed.

preprint2021arXiv

Evidence for $Z_{c}^{\pm}$ decays into the $ρ^{\pm} η_{c}$ final state

We study $e^{+}e^{-}$ collisions with a $π^{+}π^{-}π^{0}η_{c}$ final state using data samples collected with the BESIII detector at center-of-mass energies $\sqrt{s}=4.226$, $4.258$, $4.358$, $4.416$, and $4.600$ GeV. Evidence for the decay $\zcpm\to\rhopm\etac$ is reported with a statistical significance of $3.9σ$ with various systematic uncertainties taken into account at $\sqrt{s} = 4.226$ GeV, and the Born cross section times branching fraction $σ^{B}(\EE\to \pimp\zcpm)\times \BR(\zcpm\to\rhopm\etac)$ is measured to be $(48 \pm 11 \pm 11)\,\rm{pb}$. The $\zcpm\to \rhopm\etac$ signal is not significant at the other center-of-mass energies and the corresponding upper limits are determined. In addition, no significant signal is observed in a search for $\zcppm\to ρ^{\pm}\etac$ with the same data samples. The ratios $R_{\zc}=\BR(\zcpm\to ρ^{\pm} \etac)/\BR(\zcpm\to π^{\pm} \jpsi)$ and $R_{\zcp}=\BR(\zcppm\to ρ^{\pm} \etac)/\BR(\zcppm\to π^{\pm} \hc)$ are obtained and used to discriminate between different theoretical interpretations of the $\zcpm$ and $\zcppm$.

preprint2021arXiv

Learning Deep Kernels for Non-Parametric Two-Sample Tests

We propose a class of kernel-based two-sample tests, which aim to determine whether two sets of samples are drawn from the same distribution. Our tests are constructed from kernels parameterized by deep neural nets, trained to maximize test power. These tests adapt to variations in distribution smoothness and shape over space, and are especially suited to high dimensions and complex data. By contrast, the simpler kernels used in prior kernel testing work are spatially homogeneous, and adaptive only in lengthscale. We explain how this scheme includes popular classifier-based two-sample tests as a special case, but improves on them in general. We provide the first proof of consistency for the proposed adaptation method, which applies both to kernels on deep features and to simpler radial basis kernels or multiple kernel learning. In experiments, we establish the superior performance of our deep kernels in hypothesis testing on benchmark and real-world data. The code of our deep-kernel-based two sample tests is available at https://github.com/fengliu90/DK-for-TST.

preprint2021arXiv

Measurement of Branching Fractions of $J/ψ$ and $ψ(3686)$ decays to $Σ^{+}$ and $\overlineΣ^-$

Using $1310.6\times10^{6}$ $J/ψ$ and $448.1\times10^{6}$ $ψ(3686)$ events collected with the BESIII detector, the branching fractions of $J/ψ$ and $ψ(3686)$ decays to $Σ^{+}\overlineΣ^{-}$ are measured to be $(10.61 \pm 0.04 \pm 0.36) \times 10^{-4}$ and $(2.52 \pm 0.04 \pm 0.09) \times 10^{-4}$, respectively. In addition, the ratio of $\mathcal{B}(ψ(3686) \rightarrow Σ^{+}\overlineΣ^{-})/\mathcal{B}(J/ψ\rightarrow Σ^{+}\overlineΣ^{-})$ is determined to be $(23.8 \pm 1.1)\%$ which violates the "$12\%$ rule".

preprint2021arXiv

Measurement of cross-section for $e^+e^-\toΞ^-\barΞ^+$ near threshold at BESIII

The Born cross-sections and effective form factors for process $e^+e^-\toΞ^-\barΞ^+$ are measured at eight center-of-mass energies between 2.644 and 3.080 GeV, using a total integrated luminosity of 363.9 pb$^{-1}$ $e^+e^-$ collision data collected with the BESIII detector at BEPCII. After performing a fit to the Born cross-section of $e^+e^-\toΞ^-\barΞ^+$, no significant threshold effect is observed.

preprint2021arXiv

Measurement of the $e^{+}e^{-}\toΣ^{0}\barΣ^{0}$ cross sections at center-of-mass energies from $2.3864$ to $3.0200$ GeV

The Born cross sections of $e^{+}e^{-}\to Σ^{0}\barΣ^{0}$ are measured at center-of-mass energies from $2.3864$ to $3.0200$ GeV using data samples with an integrated luminosity of $328.5$ pb$^{-1}$ collected with the BESIII detector operating at the BEPCII collider. The analysis makes use of a novel reconstruction method for energies near production threshold, while a single-tag method is employed at other center-of-mass energies. The measured cross sections are consistent with earlier results from BaBar, with a substantially improved precision. The cross-section lineshape can be well described by a perturbative QCD-driven energy function. In addition, the effective form factors of the $Σ^{0}$ baryon are determined. The results provide precise experimental input for testing various theoretical predictions.

preprint2021arXiv

Measurements of $e^+e^-\rightarrow η_{\rm c}π^+ π^-π^0$, $η_{\rm c}π^+ π^-$ and $η_{\rm c}π^0γ$ at $\sqrt{s}$ from 4.18 to 4.60\,GeV, and search for a $Z_{\rm c}$ state close to the $D\bar{D}$ threshold decaying to $η_{\rm c}π$ at $\sqrt{s}$ = 4.23 GeV

We study $η_{\rm c}$ production at center-of-mass energies $\sqrt{s}$ from 4.18 to 4.60 GeV in $e^+e^-$ annihilation data collected with the BESIII detector operating at the BEPCII storage ring, corresponding to 7.3 fb$^{-1}$ of integrated luminosity. We measure the cross sections of the three different exclusive reactions $e^+e^-\rightarrow η_{\rm c}π^+ π^-π^0$, $e^+e^- \rightarrow η_{\rm c}π^+ π^-$, and $e^+e^- \rightarrow η_{\rm c}π^0γ$. We find significant $η_{\rm c}$ production in $e^+e^-\rightarrow η_{\rm c}π^+ π^-π^0$ at $\sqrt{s}$ of 4.23 GeV and 4.26 GeV and observe a significant energy-dependent Born cross section that we measure to be consistent with the production via the intermediate $Y(4260)$ resonance. In addition, we perform a search for a charmonium-like $Z_{\rm c}$ state close to the $D\bar{D}$ threshold that decays to $η_{\rm c}π$, involving ground state charmonium, and observe no signal. Corresponding upper limits on the cross section of $η_{\rm c}$ and $Z_{\rm c}$ production are provided, where the yields are not found to be significant.

preprint2021arXiv

Model independent determination of the spin of the $Ω^{-}$ and its polarization alignment in $ψ(3686)\rightarrowΩ^{-}\barΩ^{+}$

We present an analysis of the process $ψ(3686) \to Ω^- \barΩ^+$ ($Ω^-\to K^-Λ$, $\barΩ^+\to K^+\barΛ$, $Λ\to pπ^-$, $\barΛ\to \bar{p}π^+$) based on a data set of $448\times 10^6$ $ψ(3686)$ decays collected with the BESIII detector at the BEPCII electron-positron collider. The helicity amplitudes for the process $ψ(3686) \to Ω^- \barΩ^+$ and the decay parameters of the subsequent decay $Ω^-\to K^-Λ$ $(\barΩ^+\to K^+\barΛ)$ are measured for the first time by a fit to the angular distribution of the complete decay chain. The branching fraction of $ψ(3686) \to Ω^- \barΩ^+$ is measured to be $(5.82\pm 0.12\pm 0.24)\times 10^{-5}$, with an improved precision compared to previous measurements.

preprint2021arXiv

Observation of $D^{0(+)}\to K^0_Sπ^{0(+)}ω$ and improved measurement of $D^0\to K^-π^+ω$

By analyzing an $e^+e^-$ annihilation data sample with an integrated luminosity of $2.93\ \rm fb^{-1}$ taken at the center-of-mass energy of 3.773 GeV with the BESIII detector, we determine the absolute branching fractions of the hadronic decays $D^0\to K^-π^+ω$, $D^0\to K^0_Sπ^0ω$, and $D^+\to K^0_Sπ^+ω$ to be $(3.392 \pm 0.044_{\rm stat} \pm 0.085_{\rm syst})\%$, $(0.848 \pm 0.046_{\rm stat} \pm 0.031_{\rm syst})\%$, and $(0.707 \pm 0.041_{\rm stat} \pm 0.029_{\rm syst})\%$, respectively. The accuracy of the branching fraction measurement of the decay $D^0\to K^-π^+ω$ is improved by a factor of seven compared to the world average value. The $D^{0}\to K^0_Sπ^{0}ω$ and $D^{+}\to K^0_Sπ^{+}ω$ decays are observed for the first time.

preprint2021arXiv

Observation of $e^{+}e^{-}\rightarrowηψ(2S)$ at center-of-mass energies from 4.236 to 4.600 GeV

Using a total of $5.25~{\rm fb}^{-1}$ of $e^{+}e^{-}$ collision data with center-of-mass energies from 4.236 to 4.600 GeV, we report the first observation of the process $e^{+}e^{-}\to ηψ(2S)$ with a statistical significance of $5σ$. The data sets were collected by the BESIII detector operating at the BEPCII storage ring. We measure the yield of events integrated over center-of-mass energies and also present the energy dependence of the measured cross section.

preprint2021arXiv

Robust Scheduling of Virtual Power Plant under Exogenous and Endogenous Uncertainties

Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional power plants, energy storages, and flexible demands. This paper proposes a novel model for determining the optimal offering strategy in the day-ahead energy-reserve market and the optimal self-scheduling plan. It considers exogenous uncertainties (or called decision-independent uncertainties, DIUs) associated with market clearing prices and available wind power generation, as well as the endogenous uncertainties (or called decision-dependent uncertainties, DDUs) pertaining to real-time reserve deployment requests. A tractable solution method based on strong duality theory, McCormick relaxation, and the Benders' decomposition to solve the proposed stochastic adaptive robust optimization with DDUs formulation is developed. Simulation results demonstrate the applicability of the proposed approach.

preprint2021arXiv

Search for the $X(2370)$ and observation of $η_{c}\toηηη^\prime$ in $J/ψ\toγηηη^{\prime}$

Using a sample of $1.31\times10^{9} ~J/ψ$ events collected with the BESIII detector, we perform a study of $J/ψ\toγηηη^{\prime}$ to search for the $X(2370)$ and $η_{c}$ in the $ηηη^{\prime}$ invariant mass distribution. No significant signal for the $X(2370)$ is observed, and we set an upper limit for the product branching fraction of ${\cal B}(J/ψ\toγX(2370)\cdot{\cal B}(X(2370)\toηηη^{\prime}) < 9.2\times10^{-6}$ at the 90% confidence level. A clear $η_{c}$ signal is observed for the first time, yielding a product branching fraction of ${\cal B}(J/ψ\to γη_{c})\cdot{\cal B}(η_{c}\to ηηη^{\prime}) = (4.86\pm0.62~({\rm stat.})\pm0.45~({\rm sys.}))\times10^{-5}$.

preprint2021arXiv

Technoeconomic Supplement of P2G Clusters with Hydrogen Pipeline for Coordinated Renewable Energy and HVDC Systems

Under the downward tendency of prices of renewable energy generators and upward trend of hydrogen demand, this paper studies the technoeconomic supplement of P2G clusters with hydrogen pipeline for HVDC to jointly consume renewable energy. First, the planning and operation constraints of large-capacity P2G clusters is established. On this basis, the multistage coordinated planning model of renewable energy, HVDCs, P2Gs and hydrogen pipelines is proposed considering both variability and uncertainty, rendering a distributionally robust chance-constrained (DRCC) program. Then this model is applied in the case study based on the real Inner Mongolia-Shandong system. Compared with energy transmission via HVDC only, P2G can provide operation supplement with its operational flexibility and long term economic supplement with increasing demand in high-valued transportation sector, which stimulates an extra 24 GW renewable energy exploration. Sensitivity analysis for both technical and economic factors further verifies the advantages of P2G in the presence of high variability due to renewable energy and downward tendency of prices of renewable energy generators. However, since the additional levelized cost of the P2G (0.04 RMB/kWh) is approximately twice the HVDC (0.02 RMB/kWh), P2G is more sensitive to uncertainty from both renewable energy and hydrogen demand.

preprint2021arXiv

Universal Undersampled MRI Reconstruction

Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for one anatomy with limited generalization ability to another anatomy. Rather than building multiple models, a universal model that reconstructs images across different anatomies is highly desirable for efficient deployment and better generalization. Simply mixing images from multiple anatomies for training a single network does not lead to an ideal universal model due to the statistical shift among datasets of various anatomies, the need to retrain from scratch on all datasets with the addition of a new dataset, and the difficulty in dealing with imbalanced sampling when the new dataset is further of a smaller size. In this paper, for the first time, we propose a framework to learn a universal deep neural network for undersampled MRI reconstruction. Specifically, anatomy-specific instance normalization is proposed to compensate for statistical shift and allow easy generalization to new datasets. Moreover, the universal model is trained by distilling knowledge from available independent models to further exploit representations across anatomies. Experimental results show the proposed universal model can reconstruct both brain and knee images with high image quality. Also, it is easy to adapt the trained model to new datasets of smaller size, i.e., abdomen, cardiac and prostate, with little effort and superior performance.

preprint2021arXiv

Weak phases and CP-symmetry tests in sequential decays of entangled double-strange baryons

Using a sample of $1.31\times10^9$ $J/ψ$ events collected with the BESIII detector at the electron-positron collider BEPCII, we analyse the full $J/ψ\to$ $Ξ^-\overlineΞ^+$, $Ξ^-\to Λπ^-$, $Λ\to pπ^-$, $\overlineΞ^+\to\overlineΛπ^+$, $\overlineΛ\to\overline{p}π^+$ decay chain. A new method, exploiting the fact that the $Ξ^-\overlineΞ^+$ pair is entangled and sequentially decaying, and where the complete decay chains are reconstructed, is applied for the first time. This enables precision measurements of the decay parameters for the $Ξ^-\toΛπ^-$ decay ($α_Ξ$, $ϕ_Ξ$) as well as the $\overlineΞ^+\to\overlineΛπ^+$ decay ($\overlineα_Ξ$, $\overlineϕ_Ξ$). From the decay parameters, two independent CP tests were performed, quantified by the observables $A_{\rm CP}^Ξ$ and $Δϕ_Ξ$. Our results, $A_{\rm CP}^Ξ$ = $(6.0\pm13.4\pm5.6)\times10^{-3}$ and $Δϕ_Ξ= (-4.8\pm13.7\pm2.9)\times10^{-3}~{\rm rad}$, are consistent with CP symmetry. Furthermore, our method enables a separation of strong and weak $Ξ\toΛπ$ decay amplitudes. This results in the first direct measurement of the weak phase difference for any baryon decay. The result is found to be $(ξ_{P} - ξ_{S}) = (1.2\pm3.4\pm0.8)\times10^{-2}$ rad and is one of the most precise tests of CP symmetry for strange baryons. The strong phase difference is measured to be $(δ_P - δ_S) = (-4.0\pm3.3\pm1.7)\times10^{-2}$ rad. In addition, we provide an independent measurement of the recently debated $Λ$ decay parameter, $α_Λ = 0.757 \pm 0.011 \pm 0.008 $. The $Λ\overlineΛ$ asymmetry is measured to be $A_{\rm CP}^Λ = (-3.7\pm11.7\pm9.0)\times10^{-3}$.

preprint2021arXiv

Weyl nodal line induced pairing in Ising superconductor and high critical field

Superconducting and topological states are two quantum phenomena attracting much interest. Their coexistence may lead to topological superconductivity sought-after for Majorana-based quantum computing. However, there is no causal relationship between the two, since superconductivity is a many-body effect due to electron-electron interaction while topology is a single-particle manifestation of electron band structure. Here, we demonstrate a novel form of Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) pairing, induced by topological Weyl nodal lines in Ising Bardeen-Cooper-Schrieffer (IBCS) superconductors. Based on first-principles calculations and analyses, we predict that the nonmagnetic metals of MA$_2$Z$_4$ family, including $α_1$-TaSi$_2$P$_4$, $α_1$-TaSi$_2$N$_4$, $α_1$-NbSi$_2$P$_4$, $α_2$-TaGe$_2$P$_4$, and $α_2$-NbGe$_2$P$_4$ monolayers, are all superconductors. While the intrinsic IBCS paring arises in these non-centrosymmetric systems, the extrinsic FFLO pairing is revealed to be evoked by the Weyl nodal lines under magnetic field, facilitating the formation of Cooper pairs with nonzero momentum in their vicinity. Moreover, we show that the IBCS pairing alone will enhance the in-plane critical field $B_c$ to ~10-50 times of Pauli paramagnetic limit $B_p$, and additional FFLO pairing can further triple the $B_c/B_p$ ratio. It therefore affords an effective approach to enhance the robustness of superconductivity. Also, the topology induced superconductivity renders naturally the possible existence of topological superconducting state.

preprint2020arXiv

$Σ^{+}$ and $\barΣ^-$ polarization in the $J/ψ$ and $ψ(3686)$ decays

From $1310.6\times10^{6}$ $J/ψ$ and $448.1\times10^{6}$ $ψ(3686)$ events collected with the BESIII experiment, we report the first observation of $Σ^{+}$ and $\barΣ^{-}$ spin polarization in $e^+e^-\rightarrow J/ψ(ψ(3686)) \rightarrow Σ^{+} \barΣ^{-}$ decays. The relative phases of the form factors $ΔΦ$ have been measured to be $(-15.5\pm0.7\pm0.5)^{\circ}$ and $(21.7\pm4.0\pm0.8)^{\circ}$ with $J/ψ$ and $ψ(3686)$ data, respectively. The non-zero value of $ΔΦ$ allows for a direct and simultaneous measurement of the decay asymmetry parameters of $Σ^{+}\rightarrow p π^{0}~(α_0 = -0.998\pm0.037\pm0.009)$ and $\barΣ^{-}\rightarrow \bar{p} π^{0}~(\barα_0 = 0.990\pm0.037\pm0.011)$, the latter value being determined for the first time. The average decay asymmetry, $(α_{0} - \barα_{0})/2$, is calculated to be $-0.994\pm0.004\pm0.002$. The CP asymmetry $A_{\rm CP,Σ} = (α_0 + \barα_0)/(α_0 - \barα_0) = -0.004\pm0.037\pm0.010$ is extracted for the first time, and is found to be consistent with CP conservation.

preprint2020arXiv

A Unified View of Topological Phase Transition in Band Theory

We develop a unified view of topological phase transitions (TPTs) in solids by revising the classical band theory with the inclusion of topology. Re-evaluating the band evolution from an "atomic crystal" [a normal insulator (NI)] to a solid crystal, such as a semiconductor, we demonstrate that there exists ubiquitously an intermediate phase of topological insulator (TI), whose critical transition point displays a linear scaling between electron hopping potential and average bond length, underlined by deformation-potential theory. The validity of the scaling relation is verified in various two-dimensional (2D) lattices regardless of lattice symmetry, periodicity, and form of electron hoppings, based on a generic tight-binding model. Significantly, this linear scaling is shown to set an upper bound for the degree of structural disorder to destroy the topological order in a crystalline solid, as exemplified by formation of vacancies and thermal disorder. Our work formulates a simple framework for understanding the physical nature of TPTs with significant implications in practical applications of topological materials.

preprint2020arXiv

A Zero-Shot based Fingerprint Presentation Attack Detection System

With the development of presentation attacks, Automated Fingerprint Recognition Systems(AFRSs) are vulnerable to presentation attack. Thus, numerous methods of presentation attack detection(PAD) have been proposed to ensure the normal utilization of AFRS. However, the demand of large-scale presentation attack images and the low-level generalization ability always astrict existing PAD methods' actual performances. Therefore, we propose a novel Zero-Shot Presentation Attack Detection Model to guarantee the generalization of the PAD model. The proposed ZSPAD-Model based on generative model does not utilize any negative samples in the process of establishment, which ensures the robustness for various types or materials based presentation attack. Different from other auto-encoder based model, the Fine-grained Map architecture is proposed to refine the reconstruction error of the auto-encoder networks and a task-specific gaussian model is utilized to improve the quality of clustering. Meanwhile, in order to improve the performance of the proposed model, 9 confidence scores are discussed in this article. Experimental results showed that the ZSPAD-Model is the state of the art for ZSPAD, and the MS-Score is the best confidence score. Compared with existing methods, the proposed ZSPAD-Model performs better than the feature-based method and under the multi-shot setting, the proposed method overperforms the learning based method with little training data. When large training data is available, their results are similar.

preprint2020arXiv

Analysis of the decay $D^0\rightarrow K_{S}^{0} K^{+} K^{-}$

Using a data sample of $2.93~fb^{-1}$ of $e^+e^-$ collisions collected at $\sqrt{s}=3.773 GeV$ in the BESIII experiment, we perform an analysis of the decay $D^0\rightarrow K_{S}^{0} K^{+} K^{-}$. The Dalitz plot is analyzed using $1856\pm 45$ flavor-tagged signal decays. We find that the Dalitz plot is well described by a set of six resonances: $a_0(980)^0$, $a_0(980)^+$, $ϕ(1020)$, $a_2(1320)^+$, $a_2(1320)^-$ and $a_0(1450)^-$. Their magnitudes, phases and fit fractions are determined as well as the coupling of $a_0(980)$ to $K\bar{K}$, $g_{K\bar{K}}=3.77\pm 0.24\text{(stat.)}\pm0.35\text{(sys.)} GeV$. The branching fraction of the decay $D^0\rightarrow K_{S}^{0} K^{+} K^{-}$ is measured using $11660\pm 118$ untagged signal decays to be $(4.51\pm 0.05\text{(stat.)}\pm 0.16\text{(sys.)})10^{-3}$. Both measurements are limited by their systematic uncertainties.

preprint2020arXiv

Asynchrony-Resilient and Privacy-Preserving Charging Protocol for Plug-in Electric Vehicles

The proliferation of plug-in electric vehicles (PEVs) advocates a distributed paradigm for the coordination of PEV charging. Distinct from existing primal-dual decomposition or consensus methods, this paper proposes a cutting-plane based distributed algorithm, which enables an asynchronous coordination while well preserving individual's private information. To this end, an equivalent surrogate model is first constructed by exploiting the duality of the original optimization problem, which masks the private information of individual users by a transformation. Then, a cutting-plane based algorithm is derived to solve the surrogate problem in a distributed manner with intrinsic superiority to cope with various asynchrony. Critical implementation issues, such as the distributed initialization, cutting-plane generation and localized stopping criteria, are discussed in detail. Numerical tests on IEEE 37- and 123-node feeders with real data show that the proposed method is resilient to a variety of asynchrony and admits the plug-and-play operation mode. It is expected the proposed methodology provides an alternative path toward a more practical protocol for PEV charging.

preprint2020arXiv

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation

In the unsupervised open set domain adaptation (UOSDA), the target domain contains unknown classes that are not observed in the source domain. Researchers in this area aim to train a classifier to accurately: 1) recognize unknown target data (data with unknown classes) and, 2) classify other target data. To achieve this aim, a previous study has proven an upper bound of the target-domain risk, and the open set difference, as an important term in the upper bound, is used to measure the risk on unknown target data. By minimizing the upper bound, a shallow classifier can be trained to achieve the aim. However, if the classifier is very flexible (e.g., deep neural networks (DNNs)), the open set difference will converge to a negative value when minimizing the upper bound, which causes an issue where most target data are recognized as unknown data. To address this issue, we propose a new upper bound of target-domain risk for UOSDA, which includes four terms: source-domain risk, $ε$-open set difference ($Δ_ε$), a distributional discrepancy between domains, and a constant. Compared to the open set difference, $Δ_ε$ is more robust against the issue when it is being minimized, and thus we are able to use very flexible classifiers (i.e., DNNs). Then, we propose a new principle-guided deep UOSDA method that trains DNNs via minimizing the new upper bound. Specifically, source-domain risk and $Δ_ε$ are minimized by gradient descent, and the distributional discrepancy is minimized via a novel open-set conditional adversarial training strategy. Finally, compared to existing shallow and deep UOSDA methods, our method shows the state-of-the-art performance on several benchmark datasets, including digit recognition (MNIST, SVHN, USPS), object recognition (Office-31, Office-Home), and face recognition (PIE).

preprint2020arXiv

Cross section measurement of $e^+e^- \rightarrow η'J/ψ$ from $\sqrt{s} = 4.178$ to $4.600$ GeV

The cross section of the process $e^+e^- \rightarrow η'J/ψ$ is measured at center-of-mass energies from $\sqrt{s} =$ 4.178 to 4.600 GeV using data samples corresponding to a total integrated luminosity of 11 fb$^{-1}$ collected with the BESIII detector operating at the BEPCII storage ring. The dependence of the cross section on $\sqrt{s}$ shows an enhancement around $4.2$ GeV. While the shape of the cross section cannot be fully explained with a single $ψ(4160)$ or $ψ(4260)$ state, a coherent sum of the two states does provide a reasonable description of the data.

preprint2020arXiv

Deciphering gene regulation from gene expression dynamics using deep neural network

Complex biological functions are carried out by the interaction of genes and proteins. Uncovering the gene regulation network behind a function is one of the central themes in biology. Typically, it involves extensive experiments of genetics, biochemistry and molecular biology. In this paper, we show that much of the inference task can be accomplished by a deep neural network (DNN), a form of machine learning or artificial intelligence. Specifically, the DNN learns from the dynamics of the gene expression. The learnt DNN behaves like an accurate simulator of the system, on which one can perform in-silico experiments to reveal the underlying gene network. We demonstrate the method with two examples: biochemical adaptation and the gap-gene patterning in fruit fly embryogenesis. In the first example, the DNN can successfully find the two basic network motifs for adaptation - the negative feedback and the incoherent feed-forward. In the second and much more complex example, the DNN can accurately predict behaviors of essentially all the mutants. Furthermore, the regulation network it uncovers is strikingly similar to the one inferred from experiments. In doing so, we develop methods for deciphering the gene regulation network hidden in the DNN "black box". Our interpretable DNN approach should have broad applications in genotype-phenotype mapping.

preprint2020arXiv

Deep Homography Estimation for Dynamic Scenes

Homography estimation is an important step in many computer vision problems. Recently, deep neural network methods have shown to be favorable for this problem when compared to traditional methods. However, these new methods do not consider dynamic content in input images. They train neural networks with only image pairs that can be perfectly aligned using homographies. This paper investigates and discusses how to design and train a deep neural network that handles dynamic scenes. We first collect a large video dataset with dynamic content. We then develop a multi-scale neural network and show that when properly trained using our new dataset, this neural network can already handle dynamic scenes to some extent. To estimate a homography of a dynamic scene in a more principled way, we need to identify the dynamic content. Since dynamic content detection and homography estimation are two tightly coupled tasks, we follow the multi-task learning principles and augment our multi-scale network such that it jointly estimates the dynamics masks and homographies. Our experiments show that our method can robustly estimate homography for challenging scenarios with dynamic scenes, blur artifacts, or lack of textures.

preprint2020arXiv

Determination of strong-phase parameters in $D\rightarrow K^0_{S,L}π^+π^-$

We report the most precise measurements to date of the strong-phase parameters between $D^0$ and $\bar{D}^0$ decays to $K^0_{S,L}π^+π^-$ using a sample of 2.93 fb$^{-1}$ of $e^+e^-$ annihilation data collected at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider. Our results provide the key inputs for a binned model-independent determination of the Cabibbo-Kobayashi-Maskawa angle $γ/ϕ_3$ with $B$ decays. Using our results, the decay model sensitivity to the $γ/ϕ_3$ measurement is expected to be between 0.7$^{\circ}$ and 1.2$^{\circ}$, approximately a factor of three smaller than that achievable with previous measurements. The improved precision of this work ensures that measurements of $γ/ϕ_3$ will not be limited by knowledge of strong phases for the next decade. Furthermore, our results provide critical input for other flavor-physics investigations, including charm mixing, other measurements of $CP$ violation, and the measurement of strong-phase parameters for other $D$-decay modes.

preprint2020arXiv

Distributed Generalized Nash Equilibrium Seeking for Energy Sharing Games

With the proliferation of distributed generators and energy storage systems, traditional passive consumers in power systems have been gradually evolving into the so-called "prosumers", i.e., proactive consumers, which can both produce and consume power. To encourage energy exchange among prosumers, energy sharing is increasingly adopted, which is usually formulated as a generalized Nash game (GNG). In this paper, a distributed approach is proposed to seek the Generalized Nash equilibrium (GNE) of the energy sharing game. To this end, we convert the GNG into an equivalent optimization problem. A Krasnosel'ski{ǐ}-Mann iteration type algorithm is thereby devised to solve the problem and consequently find the GNE in a distributed manner. The convergence of the proposed algorithm is proved rigorously based on the nonexpansive operator theory. The performance of the algorithm is validated by experiments with three prosumers, and the scalability is tested by simulations using 123 prosumers.

preprint2020arXiv

Domain Contrast for Domain Adaptive Object Detection

We present Domain Contrast (DC), a simple yet effective approach inspired by contrastive learning for training domain adaptive detectors. DC is deduced from the error bound minimization perspective of a transferred model, and is implemented with cross-domain contrast loss which is plug-and-play. By minimizing cross-domain contrast loss, DC guarantees the transferability of detectors while naturally alleviating the class imbalance issue in the target domain. DC can be applied at either image level or region level, consistently improving detectors' transferability and discriminability. Extensive experiments on commonly used benchmarks show that DC improves the baseline and state-of-the-art by significant margins, while demonstrating great potential for large domain divergence.

preprint2020arXiv

Erratum to "Measurement of the $e^+e^-\toπ^+π^-$ cross section between 600 and 900 MeV using initial state radiation"

In Phys. Lett. B 753, 629-638 (2016) [arXiv:1507.08188] the BESIII collaboration published a cross section measurement of the process $e^+e^-\to π^+ π^-$ in the energy range between 600 and 900 MeV. In this erratum we report a corrected evaluation of the statistical errors in terms of a fully propagated covariance matrix. The correction also yields a reduced statistical uncertainty for the hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, which now reads as $a_μ^{ππ\mathrm{, LO}}(600 - 900\,\mathrm{MeV}) = (368.2 \pm 1.5_{\rm stat} \pm 3.3_{\rm syst})\times 10^{-10}$. The central values of the cross section measurement and of $a_μ^{ππ\mathrm{, LO}}$, as well as the systematic uncertainties remain unchanged.

preprint2020arXiv

Event Arguments Extraction via Dilate Gated Convolutional Neural Network with Enhanced Local Features

Event Extraction plays an important role in information-extraction to understand the world. Event extraction could be split into two subtasks: one is event trigger extraction, the other is event arguments extraction. However, the F-Score of event arguments extraction is much lower than that of event trigger extraction, i.e. in the most recent work, event trigger extraction achieves 80.7%, while event arguments extraction achieves only 58%. In pipelined structures, the difficulty of event arguments extraction lies in its lack of classification feature, and the much higher computation consumption. In this work, we proposed a novel Event Extraction approach based on multi-layer Dilate Gated Convolutional Neural Network (EE-DGCNN) which has fewer parameters. In addition, enhanced local information is incorporated into word features, to assign event arguments roles for triggers predicted by the first subtask. The numerical experiments demonstrated significant performance improvement beyond state-of-art event extraction approaches on real-world datasets. Further analysis of extraction procedure is presented, as well as experiments are conducted to analyze impact factors related to the performance improvement.

preprint2020arXiv

Exponential Stability of Partial Primal-Dual Gradient Dynamics with Nonsmooth Objective Functions

In this paper, we investigate the continuous time partial primal-dual gradient dynamics (P-PDGD) for solving convex optimization problems with the form $ \min\limits_{x\in X,y\inΩ}\ f({x})+h(y),\ \textit{s.t.}\ A{x}+By=C $, where $ f({x}) $ is strongly convex and smooth, but $ h(y) $ is strongly convex and non-smooth. Affine equality and set constraints are included. We prove the exponential stability of P-PDGD, and bounds on decaying rates are provided. Moreover, it is also shown that the decaying rates can be regulated by setting the stepsize.

preprint2020arXiv

Fast Monte Carlo Simulation of Dynamic Power Systems Under Continuous Random Disturbances

Continuous-time random disturbances from the renewable generation pose a significant impact on power system dynamic behavior. In evaluating this impact, the disturbances must be considered as continuous-time random processes instead of random variables that do not vary with time to ensure accuracy. Monte Carlo simulation (MCs) is a nonintrusive method to evaluate such impact that can be performed on commercial power system simulation software and is easy for power utilities to use, but is computationally cumbersome. Fast samplings methods such as Latin hypercube sampling (LHS) have been introduced to speed up sampling random variables, but yet cannot be applied to sample continuous disturbances. To overcome this limitation, this paper proposes a fast MCs method that enables the LHS to speed up sampling continuous disturbances, which is based on the Itô process model of the disturbances and the approximation of the Itô process by functions of independent normal random variables. A case study of the IEEE 39-Bus System shows that the proposed method is 47.6 and 6.7 times faster to converge compared to the traditional MCs in evaluating the expectation and variance of the system dynamic response.

preprint2020arXiv

First Measurements of $χ_{cJ}\rightarrow Σ^{-} \barΣ^{+} (J = 0, 1, 2)$ Decays

We measured the branching fractions of the decays $χ_{cJ}\toΣ^{-}\barΣ^{+}$ for the first time using the final states $n\bar{n}π^{+}π^{-}$. The data sample exploited here is $448.1\times10^{6}$ $ψ(3686)$ events collected with BESIII. We find $\mathcal{B}(χ_{cJ}\rightarrowΣ^{-}\barΣ^{+}) = (51.3\pm2.4\pm4.1)\times10^{-5},\, (5.7\pm1.4\pm0.6)\times10^{-5},\, \rm{and}~ (4.4\pm1.7\pm0.5)\times10^{-5}$, for $J=0,1,2$, respectively, where the first uncertainties are statistical and the second systematic.

preprint2020arXiv

Frosting Weights for Better Continual Training

Training a neural network model can be a lifelong learning process and is a computationally intensive one. A severe adverse effect that may occur in deep neural network models is that they can suffer from catastrophic forgetting during retraining on new data. To avoid such disruptions in the continuous learning, one appealing property is the additive nature of ensemble models. In this paper, we propose two generic ensemble approaches, gradient boosting and meta-learning, to solve the catastrophic forgetting problem in tuning pre-trained neural network models.

preprint2020arXiv

Future Physics Programme of BESIII

There has recently been a dramatic renewal of interest in the subjects of hadron spectroscopy and charm physics. This renaissance has been driven in part by the discovery of a plethora of charmonium-like $XYZ$ states at BESIII and $B$ factories, and the observation of an intriguing proton-antiproton threshold enhancement and the possibly related $X(1835)$ meson state at BESIII, as well as the threshold measurements of charm mesons and charm baryons. We present a detailed survey of the important topics in tau-charm physics and hadron physics that can be further explored at BESIII over the remaining lifetime of BEPCII operation. This survey will help in the optimization of the data-taking plan over the coming years, and provides physics motivation for the possible upgrade of BEPCII to higher luminosity.

preprint2020arXiv

Global mild solutions to three-dimensional magnetohydrodynamic system in Morrey spaces

In this article, the Cauchy problem of three-dimensional (3-D) incompressible magnetohydrodynamic system was investigated. If the initial $\mathcal{M}^{1,1}$ norms of the vorticity $ω$ and the current density $j$ are both sufficiently small, then some uniform estimates with respect to time for the coupling terms between the fluid and the magnetic field can be established, which lead to a global-in-time well-posedness of mild solutions in Morrey spaces via some effective arguments.

preprint2020arXiv

Global optimization using mixed integer quadratic programming on non-convex two-way interaction truncated linear multivariate adaptive regression splines

Multivariate adaptive regression splines (MARS) is a flexible statistical modeling method that has been popular for data mining applications. MARS has also been employed to approxmiate unknown relationships in optimzation for complex systems, including surrogate optimization, dynamic programming, and two-stage stochastic programming. Given the increasing desire to optimize real world systems, this paper presents an approach to globally optimize a MARS model that allows up to two-way interaction terms that are products of truncated linear univariate functions (TITL-MARS). Specifally, such a MARS model consists of linear and quadratic structure. This structure is exploited to formulate a mixed integer quadratic programming problem (TITL-MARS-OPT). To appreciate the contribution of TITL-MARS-OPT, one must recognize that popular heurstic optimization approaches, such as evolutionary algorithms, do not guarantee global optimality and can be computationally slow. The use of MARS maintains the flexibility of modeling within TITL-MARS-OPT while also taking advantage of the linear modeling structure of MARS to enable global optimality. Computational results compare TITL-MARS-OPT with a genetic algorithm for two types of cases. First, a wind farm power distribution case study is described and then other TITL-MARS forms are tested. The results show the superiority of TITL-MARS-OPT over the genetic algorithm in both accuracy and computational time.

preprint2020arXiv

Heterogeneous domain adaptation: An unsupervised approach

Domain adaptation leverages the knowledge in one domain - the source domain - to improve learning efficiency in another domain - the target domain. Existing heterogeneous domain adaptation research is relatively well-progressed, but only in situations where the target domain contains at least a few labeled instances. In contrast, heterogeneous domain adaptation with an unlabeled target domain has not been well-studied. To contribute to the research in this emerging field, this paper presents: (1) an unsupervised knowledge transfer theorem that guarantees the correctness of transferring knowledge; and (2) a principal angle-based metric to measure the distance between two pairs of domains: one pair comprises the original source and target domains and the other pair comprises two homogeneous representations of two domains. The theorem and the metric have been implemented in an innovative transfer model, called a Grassmann-Linear monotonic maps-geodesic flow kernel (GLG), that is specifically designed for heterogeneous unsupervised domain adaptation (HeUDA). The linear monotonic maps meet the conditions of the theorem and are used to construct homogeneous representations of the heterogeneous domains. The metric shows the extent to which the homogeneous representations have preserved the information in the original source and target domains. By minimizing the proposed metric, the GLG model learns the homogeneous representations of heterogeneous domains and transfers knowledge through these learned representations via a geodesic flow kernel. To evaluate the model, five public datasets were reorganized into ten HeUDA tasks across three applications: cancer detection, credit assessment, and text classification. The experiments demonstrate that the proposed model delivers superior performance over the existing baselines.

preprint2020arXiv

Higher-order Quantum Spin Hall Effect of Light

Band topology and related spin (or pseudo-spin) physics of photons provide us with a new dimension for manipulating light, which is potentially useful for information communication and data storage. Especially, the quantum spin Hall effect of light, where electromagnetic waves propagate along surfaces of samples with strong spin-momentum locking, paves the way for achieving topologically protected photonic spin transport. Recently, the conventional bulk-edge correspondence of the band topology has been extended to higher-order cases that enables the explorations of topological states with codimensions larger than 1 such as hinge and corner states. Here, for the first time, we demonstrate a higherorder quantum spin Hall effect of light by utilizing an all-dielectric C6v-symmetric photonic crystal. We observe corner states with opposite pseudospin polarizations at different corners owing to nontrivial higher-order topology and finite spin-spin coupling. By applying the spin-polarized excitation sources, we can selectively excite the corner states at different spatial positions through spin-momentum-locked decaying edge states, resembling the quantum spin Hall effect in a higher-order manner. Our work which breaks the barriers between the spin photonics and higher-order topology opens the frontiers for studying lower-dimensional spinful classical surface waves and supports explorations in robust communications.

preprint2020arXiv

Honeycomb-Lattice Mott insulator on Tantalum Disulphide

Effects of electron many-body interactions amplify in an electronic system with a narrow bandwidth opening a way to exotic physics. A narrow band in a two-dimensional (2D) honeycomb lattice is particularly intriguing as combined with Dirac bands and topological properties but the material realization of a strongly interacting honeycomb lattice described by the Kane-Mele-Hubbard model has not been identified. Here we report a novel approach to realize a 2D honeycomb-lattice narrow-band system with strongly interacting 5$d$ electrons. We engineer a well-known triangular lattice 2D Mott insulator 1T-TaS$_2$ into a honeycomb lattice utilizing an adsorbate superstructure. Potassium (K) adatoms at an optimum coverage deplete one-third of the unpaired $d$ electrons and the remaining electrons form a honeycomb lattice with a very small hopping. Ab initio calculations show extremely narrow Z$_2$ topological bands mimicking the Kane-Mele model. Electron spectroscopy detects an order of magnitude bigger charge gap confirming the substantial electron correlation as confirmed by dynamical mean field theory. It could be the first artificial Mott insulator with a finite spin Chern number.

preprint2020arXiv

How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?

Unsupervised domain adaptation (UDA) aims to train a target classifier with labeled samples from the source domain and unlabeled samples from the target domain. Classical UDA learning bounds show that target risk is upper bounded by three terms: source risk, distribution discrepancy, and combined risk. Based on the assumption that the combined risk is a small fixed value, methods based on this bound train a target classifier by only minimizing estimators of the source risk and the distribution discrepancy. However, the combined risk may increase when minimizing both estimators, which makes the target risk uncontrollable. Hence the target classifier cannot achieve ideal performance if we fail to control the combined risk. To control the combined risk, the key challenge takes root in the unavailability of the labeled samples in the target domain. To address this key challenge, we propose a method named E-MixNet. E-MixNet employs enhanced mixup, a generic vicinal distribution, on the labeled source samples and pseudo-labeled target samples to calculate a proxy of the combined risk. Experiments show that the proxy can effectively curb the increase of the combined risk when minimizing the source risk and distribution discrepancy. Furthermore, we show that if the proxy of the combined risk is added into loss functions of four representative UDA methods, their performance is also improved.

preprint2020arXiv

Identification of New Assembly Mode in the Heliconical Nematic Phase via Tender Resonant X-ray Scattering

Helical structures are exciting and are utilized in numerous applications ranging from biotechnology to displays to medicine. Accurate description and understanding of resonance effects in helical structures provides crucial knowledge on molecular packing beyond positional ordering. We exam-ined the manifestation of resonance effects in a nematic phase with heliconical structure, the so called twist bend nematic (NTB) via tender resonant X-ray scattering (TReXS) at the sulfur K-edge. We demonstrate for the first time quantitatively that the energy dependence of the scattering peak in the NTB phase follows the energy dependence of the complex refractive indices measured by X-ray absorption. This allows us to identify a new self-assembly mode for specific sets of liquid crystal dimers in the NTB phase. We anticipate that new avenues in the exploration of complex orientational structures both in static as well as in dynamic modes induced by external stimuli will be pursued.

preprint2020arXiv

Inclusive charged and neutral particle multiplicity distributions in $χ_{cJ}$ and $J/ψ$ decays

Using a sample of 106 million $ψ(3686)$ decays, $ψ(3686) \to γχ_{cJ} (J = 0, 1, 2)$ and $ψ(3686) \to γχ_{cJ}, χ_{cJ} \to γJ/ψ$ $(J = 1, 2)$ events are utilized to study inclusive $χ_{cJ} \to$ anything, $χ_{cJ} \to$ hadrons, and $J/ψ\to$ anything distributions, including distributions of the number of charged tracks, electromagnetic calorimeter showers, and $π^0$s, and to compare them with distributions obtained from the BESIII Monte Carlo simulation. Information from each Monte Carlo simulated decay event is used to construct matrices connecting the detected distributions to the input predetection "produced" distributions. Assuming these matrices also apply to data, they are used to predict the analogous produced distributions of the decay events. Using these, the charged particle multiplicities are compared with results from MARK I. Further, comparison of the distributions of the number of photons in data with those in Monte Carlo simulation indicates that G-parity conservation should be taken into consideration in the simulation.

preprint2020arXiv

Inter-sequence Enhanced Framework for Personalized Sequential Recommendation

Modeling the sequential correlation of users' historical interactions is essential in sequential recommendation. However, the majority of the approaches mainly focus on modeling the \emph{intra-sequence} item correlation within each individual sequence but neglect the \emph{inter-sequence} item correlation across different user interaction sequences. Though several studies have been aware of this issue, their method is either simple or implicit. To make better use of such information, we propose an inter-sequence enhanced framework for the Sequential Recommendation (ISSR). In ISSR, both inter-sequence and intra-sequence item correlation are considered. Firstly, we equip graph neural networks in the inter-sequence correlation encoder to capture the high-order item correlation from the user-item bipartite graph and the item-item graph. Then, based on the inter-sequence correlation encoder, we build GRU network and attention network in the intra-sequence correlation encoder to model the item sequential correlation within each individual sequence and temporal dynamics for predicting users' preferences over candidate items. Additionally, we conduct extensive experiments on three real-world datasets. The experimental results demonstrate the superiority of ISSR over many state-of-the-art methods and the effectiveness of the inter-sequence correlation encoder.

preprint2020arXiv

Learning from a Complementary-label Source Domain: Theory and Algorithms

In unsupervised domain adaptation (UDA), a classifier for the target domain is trained with massive true-label data from the source domain and unlabeled data from the target domain. However, collecting fully-true-label data in the source domain is high-cost and sometimes impossible. Compared to the true labels, a complementary label specifies a class that a pattern does not belong to, hence collecting complementary labels would be less laborious than collecting true labels. Thus, in this paper, we propose a novel setting that the source domain is composed of complementary-label data, and a theoretical bound for it is first proved. We consider two cases of this setting, one is that the source domain only contains complementary-label data (completely complementary unsupervised domain adaptation, CC-UDA), and the other is that the source domain has plenty of complementary-label data and a small amount of true-label data (partly complementary unsupervised domain adaptation, PC-UDA). To this end, a complementary label adversarial network} (CLARINET) is proposed to solve CC-UDA and PC-UDA problems. CLARINET maintains two deep networks simultaneously, where one focuses on classifying complementary-label source data and the other takes care of source-to-target distributional adaptation. Experiments show that CLARINET significantly outperforms a series of competent baselines on handwritten-digits-recognition and objects-recognition tasks.

preprint2020arXiv

Local Facial Makeup Transfer via Disentangled Representation

Facial makeup transfer aims to render a non-makeup face image in an arbitrary given makeup one while preserving face identity. The most advanced method separates makeup style information from face images to realize makeup transfer. However, makeup style includes several semantic clear local styles which are still entangled together. In this paper, we propose a novel unified adversarial disentangling network to further decompose face images into four independent components, i.e., personal identity, lips makeup style, eyes makeup style and face makeup style. Owing to the further disentangling of makeup style, our method can not only control the degree of global makeup style, but also flexibly regulate the degree of local makeup styles which any other approaches can't do. For makeup removal, different from other methods which regard makeup removal as the reverse process of makeup, we integrate the makeup transfer with the makeup removal into one uniform framework and obtain multiple makeup removal results. Extensive experiments have demonstrated that our approach can produce more realistic and accurate makeup transfer results compared to the state-of-the-art methods.

preprint2020arXiv

Measurement of {\boldmath $J/ψ\toΞ(1530)^{-}\barΞ^{+}$} and evidence for the radiative decay {\boldmath $Ξ(1530)^{-}\toγΞ^-$}

The SU(3)-flavor violating decay $J/ψ\toΞ(1530)^{-}\barΞ^{+}+c.c.$ is studied using $(1310.6\pm7.0)\times 10^{6} ~J/ψ$ events collected with the BESIII detector at BEPCII and the branching fraction is measured to be ${\cal{B}}(J/ψ\toΞ(1530)^{-}\barΞ^{+}+c.c.)=(3.17\pm0.02_{\rm stat.}\pm0.08_{\rm syst.})\times10^{-4}$. This is consistent with previous measurements with an improved precision. The angular parameter for this decay is measured for the first time and is found to be $α=-0.21\pm0.04_{\rm stat.}\pm0.06_{\rm syst.}$. In addition, we report evidence for the radiative decay $Ξ(1530)^{-}\toγΞ^- $ with a significance of 3.9$σ$, including the systematic uncertainties. The 90\% confidence level upper limit on the branching fraction is determined to be $\mathcal{B}(Ξ(1530)^{-}\toγΞ^- )\leq3.7$\%.

preprint2020arXiv

Measurement of proton electromagnetic form factors in $e^+e^- \to p\bar{p}$ in the energy region 2.00-3.08 GeV

The process of $e^+e^- \rightarrow p\bar{p}$ is studied at 22 center-of-mass energy points ($\sqrt{s}$) from 2.00 to 3.08 GeV, exploiting 688.5~pb$^{-1}$ of data collected with the BESIII detector operating at the BEPCII collider. The Born cross section~($σ_{p\bar{p}}$) of $e^+e^- \rightarrow p\bar{p}$ is measured with the energy-scan technique and it is found to be consistent with previously published data, but with much improved accuracy. In addition, the electromagnetic form-factor ratio ($|G_{E}/G_{M}|$) and the value of the effective ($|G_{\rm{eff}}|$), electric ($|G_E|$) and magnetic ($|G_M|$) form factors are measured by studying the helicity angle of the proton at 16 center-of-mass energy points. $|G_{E}/G_{M}|$ and $|G_M|$ are determined with high accuracy, providing uncertainties comparable to data in the space-like region, and $|G_E|$ is measured for the first time. We reach unprecedented accuracy, and precision results in the time-like region provide information to improve our understanding of the proton inner structure and to test theoretical models which depend on non-perturbative Quantum Chromodynamics.

preprint2020arXiv

Measurement of Singly Cabibbo-Suppressed Decays $D \to ωππ$

Using 2.93 fb$^{-1}$ of $e^{+}e^{-}$ collision data taken at a center-of-mass energy of 3.773 GeV by the BESIII detector at the BEPCII, we measure the branching fractions of the singly Cabibbo-suppressed decays $D \to ωππ$ to be $\mathcal{B}(D^0 \to ωπ^+π^-) = (1.33 \pm 0.16 \pm 0.12)\times 10^{-3}$ and $\mathcal{B}(D^+ \to ωπ^+π^0) =(3.87 \pm 0.83 \pm 0.25)\times 10^{-3}$, where the first uncertainties are statistical and the second ones systematic. The statistical significances are $12.9σ$ and $7.7 σ$, respectively. The precision of $\mathcal{B}(D^0 \to ωπ^+π^-)$ is improved by a factor of 2.1 over the CLEO measurement, and $\mathcal{B}(D^+ \to ωπ^+π^0)$ is measured for the first time. No significant signal of $\mathcal{B}(D^0 \to ωπ^0π^0)$ is observed, and the upper limit on the branching fraction is $\mathcal{B}(D^0 \to ωπ^0π^0) < 1.10 \times 10^{-3}$ at the $90\%$ confidence level. The branching fractions of $D\to ηππ$ are also measured and consistent with existing results.

preprint2020arXiv

Measurement of the Born Cross Sections for $e^+e^-\to D_s^+ D_{s1}(2460)^- +c.c.$ and $e^+e^-\to D_s^{\ast +} D_{s1}(2460)^- +c.c.$

The processes $e^+e^-\to D_s^+ D_{s1}(2460)^- +c.c.$ and $e^+e^-\to D_s^{\ast +} D_{s1}(2460)^- +c.c.$ are studied for the first time using data samples collected with the BESIII detector at the BEPCII collider. The Born cross sections of $e^+e^-\to D_s^+ D_{s1}(2460)^- +c.c.$ at nine center-of-mass energies between 4.467\,GeV and 4.600\,GeV and those of $e^+e^-\to D_s^{\ast +} D_{s1}(2460)^- +c.c.$ at ${\sqrt s}=$ 4.590\,GeV and 4.600\,GeV are measured. No obvious charmonium or charmonium-like structure is seen in the measured cross sections.

preprint2020arXiv

Measurement of the cross section for $e^{+}e^{-}\rightarrowΞ^{-}\barΞ^{+}$ and observation of an excited $Ξ$ baryon

Using a total of 11.0 fb$^{-1}$ of $e^{+}e^{-}$ collision data with center-of-mass energies between 4.009 GeV and 4.6 GeV and collected with the BESIII detector at BEPCII, we measure fifteen exclusive cross sections and effective form factors for the process $e^{+}e^{-}\rightarrowΞ^{-}\barΞ^{+}$ by means of a single baryon-tag method. After performing a fit to the dressed cross section of $e^{+}e^{-}\rightarrowΞ^{-}\barΞ^{+}$, no significant $ψ(4230)$ or $ψ(4260)$ resonance is observed in the $Ξ^{-}\barΞ^{+}$ final states, and upper limits at the 90\% confidence level on $Γ_{ee}\mathcal{B}$ for the processes $ψ(4230)$/$ψ(4260)\rightarrowΞ^{-}\barΞ^{+}$ are determined. In addition, an excited $Ξ$ baryon at 1820 MeV/$c^{2}$ is observed with a statistical significance of 6.2 $\sim$ 6.5$σ$ by including the systematic uncertainty, and the mass and width are measured to be $M = (1825.5 \pm 4.7 \pm 4.7)$~MeV/$c^{2}$ and $Γ= (17.0 \pm 15.0 \pm 7.9)$~MeV, which confirms the existence of the $J^{P}=\frac{3}{2}^{-}$ state $Ξ(1820)$.

preprint2020arXiv

Model-independent determination of the relative strong-phase difference between $D^0$ and $\bar{D}^0\rightarrow K^0_{S,L}π^+π^-$ and its impact on the measurement of the CKM angle $γ/ϕ_3$

Crucial inputs for a variety of $CP$-violation studies can be determined through the analysis of pairs of quantum-entangled neutral $D$ mesons, which are produced in the decay of the $ψ(3770)$ resonance. The relative strong-phase parameters between $D^0$ and $\bar{D}^0$ in the decays $D^0\rightarrow K^0_{S,L}π^+π^-$ are studied using 2.93~${\rm fb}^{-1}$ of $e^+e^-$ annihilation data delivered by the BEPCII collider and collected by the BESIII detector at a center-of-mass energy of 3.773 GeV. Results are presented in regions of the phase space of the decay. These are the most precise measurements to date of the strong-phase parameters in $D \to K_{S,L}^0π^+π^-$ decays. Using these parameters, the associated uncertainty on the Cabibbo-Kobayashi-Maskawa angle $γ/ϕ_3$ is expected to be between $0.7^\circ$ and $1.2^\circ$, for an analysis using the decay $B^{\pm}\rightarrow DK^{\pm}$, $D\rightarrow K^0_Sπ^+π^-$, where $D$ represents a superposition of $D^0$ and $\bar{D^0}$ states. This is a factor of three smaller than that achievable with previous measurements. Furthermore, these results provide valuable input for charm-mixing studies, other measurements of $CP$ violation, and the measurement of strong-phase parameters for other $D$-decay modes.

preprint2020arXiv

Nonintrusive Uncertainty Quantification of Dynamic Power Systems Subject to Stochastic Excitations

Continuous-time random disturbances (also called stochastic excitations) due to increasing renewable generation have an increasing impact on power system dynamics; However, except from the Monte Carlo simulation, most existing methods for quantifying this impact are intrusive, meaning they are not based on commercial simulation software and hence are difficult to use for power utility companies. To fill this gap, this paper proposes an efficient and nonintrusive method for quantifying uncertainty in dynamic power systems subject to stochastic excitations. First, the Gaussian or non-Gaussian stochastic excitations are modeled with an Itô process as stochastic differential equations. Then, the Itô process is spectrally represented by independent Gaussian random parameters, which enables the polynomial chaos expansion (PCE) of the system dynamic response to be calculated via an adaptive sparse probabilistic collocation method. Finally, the probability distribution and the high-order moments of the system dynamic response and performance index are accurately and efficiently quantified. The proposed nonintrusive method is based on commercial simulation software such as PSS/E with carefully designed input signals, which ensures ease of use for power utility companies. The proposed method is validated via case studies of IEEE 39-bus and 118-bus test systems.

preprint2020arXiv

Observation of a cross-section enhancement near mass threshold in $e^{+}e^{-}\rightarrowΛ\barΛ$

The process $e^{+}e^{-}\rightarrowΛ\barΛ$ is studied using data samples at $\sqrt{s}=2.2324$, 2.400, 2.800 and 3.080 GeV collected with the BESIII detector operating at the BEPCII collider. The Born cross section is measured at $\sqrt{s}$=2.2324 GeV, which is 1.0 MeV above the $Λ\barΛ$ mass threshold, to be $305\pm45^{+66}_{-36}$ pb, where the first uncertainty is statistical and the second systematic. The substantial cross section near threshold is significantly larger than that expected from theory, which predicts the cross section to vanish at threshold. The Born cross sections at $\sqrt{s}$=2.400, 2.800 and 3.080 GeV are measured and found to be consistent with previous experimental results, but with improved precision. Finally, the corresponding effective electromagnetic form factors of $Λ$ are deduced.

preprint2020arXiv

Observation of a resonant structure in $e^{+}e^{-} \to ωη$ and another in $e^{+}e^{-} \to ωπ^{0}$ at center-of-mass energies between 2.00 and 3.08 GeV

Born cross sections for the processes $e^+e^- \to ωη$ and $e^+e^- \to ωπ^{0}$ have been determined for center-of-mass energies between 2.00 and 3.08 GeV with the BESIII detector at the BEPCII collider. The results obtained in this work are consistent with previous measurements but with improved precision. Two resonant structures are observed. In the $e^{+}e^{-} \to ωη$ cross sections, a resonance with a mass of $(2179 \pm 21 \pm 3)\text{MeV}/c^2$ and a width of $(89 \pm 28 \pm 5)\text{MeV}$ is observed with a significance of 6.1$σ$. Its properties are consistent with the $ϕ(2170)$. In the $e^{+}e^{-} \toωπ^{0}$ cross sections, a resonance denoted $Y(2040)$ is observed with a significance of more than 10$σ$. Its mass and width are determined to be $(2034 \pm 13 \pm 9)\text{MeV}/c^2$ and $(234 \pm 30 \pm 25)\text{MeV}$, respectively, where the first uncertainties are statistical and the second ones are systematic.

preprint2020arXiv

Observation of a structure in $e^+e^- \to ϕη^{\prime}$ at $\sqrt{s}$ from 2.05 to 3.08 GeV

The process $e^{+}e^{-} \to ϕη^{\prime}$ has been studied for the first time in detail using data sample collected with the BESIII detector at the BEPCII collider at center of mass energies from 2.05 to 3.08 GeV. A resonance with quantum numbers $J^{PC}=1^{--}$ is observed with mass $M$ = (2177.5 $\pm$ 4.8 (stat) $\pm$ 19.5 (syst)) MeV/${ \it{c}^{\mathrm{2}}}$ and width $Γ$ = (149.0 $\pm$ 15.6 (stat) $\pm$ 8.9 (syst)) MeV with a statistical significance larger than 10$σ$. The observed structure could be identified with the $ϕ(2170)$, then the ratio of partial width between the $ϕη^{\prime}$ by BESIII and $ϕη$ by BABAR is ($\mathcal{B}^{R}_{ϕη}Γ^{R}_{ee})/{(\mathcal{B}^{R}_{ϕη^{\prime}}Γ^{R}_{ee})}$ = 0.23 $\pm$ 0.10 (stat) $\pm$ 0.18 (syst), which is smaller than the prediction of the $s\bar{s}g$ hybrid models by several orders of magnitude.

preprint2020arXiv

Observation of photon antibunching with a single conventional detector

The second-order photon correlation function is of great importance in quantum optics which is typically measured with the Hanbury Brown and Twiss interferometer which employs a pair of single-photon detectors and a dual-channel time acquisition module. Here we demonstrate a new method to measure and extract the second-order correlation function with a standard single-photon avalanche photodiode (dead-time = 22 ns) and a single-channel time acquisition module. This is realized by shifting the informative coincidence counts near the zero-time delay to a time window which is not obliterated by the dead-time and after-pulse of detection system. The new scheme is verified by measuring the second-order correlation from a single colloidal nanocrystal. Photon antibunching is unambiguously observed and agrees well with the result measured using the standard HBT setup. Our scheme simplifies the higher-order correlation technique and might be favored in cost-sensitive circumstances.

preprint2020arXiv

Observation of the $Y(4220)$ and $Y(4360)$ in the process $e^{+}e^{-} \to ηJ/ψ$

The cross sections of the process $e^{+}e^{-} \to ηJ/ψ$ at center-of-mass energies ($\sqrt{s}$) between 3.81 and 4.60 GeV are measured with high precision by using data samples collected with the BESIII detector operating at the BEPCII storage ring. Three structures are observed by analyzing the lineshape of the measured cross sections, and a maximum-likelihood fit including three resonances is performed by assuming the lowest lying structure is the $ψ(4040)$. For the other resonances, we obtain masses of $(4218.7 \pm 4.0 \pm 2.5)$ and $(4380.4 \pm 14.2 \pm 1.8)$ MeV/c$^{2}$ with corresponding widths of $(82.5 \pm 5.9 \pm 0.5)$ and $(147.0 \pm 63.0 \pm 25.8)$ MeV, respectively, where the first uncertainties are statistical and the second ones systematic. The measured resonant parameters are consistent with those of the $Y(4220)$ and $Y(4360)$ from pr evious measurements of different final states. For the first time, we observe the decays of the $Y(4220)$ and $Y(4360)$ into $ηJ/ψ$ final states.

preprint2020arXiv

Optimal Configuration of Wind-to-Ammonia with the Electric Network and Hydrogen Supply Chain: A Case Study of Inner Mongolia

Converting wind energy into ammonia (WtA) has been recognized as a promising pathway to enhance the usage of wind generation. This paper proposes a generic optimal configuration model of WtA at the network level to minimize the ammonia production cost by optimizing capacities and locations of WtA facilities including wind turbines, electrolyzers, hydrogen tanks and optimizing supply modes among regions. Specifically, the temporal fluctuation characteristics of wind resources, the operation flexibility of the ammonia synthesis reactor and the transport distances are considered. Three typical supply modes, i.e., the Local WtA, the EN (electric network)-based WtA and the HSC (hydrogen supply chain)-based WtA, combined with two energy transport modes including EN and HT (Hydrogen truck trailers) are included with the consideration of the maximal energy transport capacity of EN and transport distance per day of HT (500km). Real data of Inner Mongolia (a typical province in China with rich wind resources and existing ammonia industries) is employed to verify the effectiveness and significance of proposed model. The effect of above significant factors on optimal planning capacity of WtA facilities and optimal energy transport modes is analyzed, which provides guidelines for WtA configuration. The economic analysis shows that the average LCOA (levelized cost of ammonia) for WtA is approximately 0.57 euro/kg in Inner Mongolia and comparable to that for CtA (coal-to-ammonia, 0.41 euro/kg) with a reduction of 30% in capacity cost of the facilities.

preprint2020arXiv

Partial wave analysis of $ψ(3686)\rightarrow K^{+}K^{-}η$

Using a sample of $(448.1\pm2.9)\times10^6$ $ψ(3686)$ events collected with the BESIII detector, we perform the first partial wave analysis of $ψ(3686)\rightarrow K^+K^-η$. In addition to the well established states, $ϕ(1020)$, $ϕ(1680)$, and $K_3^*(1780)$, contributions from $X(1750)$, $ρ(2150)$, $ρ_3(2250)$, and $K^*_2(1980)$ are also observed. The $X(1750)$ state is determined to be a $1^{--}$ resonance. The simultaneous observation of the $ϕ(1680)$ and $X(1750)$ indicates that the $X(1750)$, with previous observations in photoproduction, is distinct from the $ϕ(1680)$. The masses, widths, branching fractions of $ψ(3686)\rightarrow K^+K^-η$ and the intermediate resonances are also measured.

preprint2020arXiv

Quasibound states in the continuum in terahertz free-standing metal complementary periodic cross-shaped resonators

We numerically and experimentally achieve quasi-bound states in the continuums (BICs) with high-Q factors in the free-standing metal complementary periodic cross-shaped resonators (CPCRs) at terahertz (THz) frequencies. Such induced quasi-BICs arises from the breaking of the mirror symmetry of CPCRs. By properly tuning the asymmetric factor, the measured Q factor of quasi-BIC can reach 102, which is lower than the simulated Q factor of 166 due to the limited system resolutions. We also simulate the electric field magnitude and vector distributions at the quasi-BICs, where the out-phase alignment between the electric dipoles is found. The sharp quasi-BICs realized in this thin free-standing metal structure may immediately boost the performance of filters and sensors in terahertz wave manipulation or biomolecular sensing.

preprint2020arXiv

Search for baryon and lepton number violating decays $D^+\to\barΛ(\barΣ^0)e^+$ and $D^+\toΛ(Σ^0)e^+$

Using a 2.93 fb$^{-1}$ data sample of electron-positron collisions taken with the BESIII detector at a center-of-mass energy of 3.773 GeV, which corresponds to $(8296\pm31\pm64)\times10^3 D^+D^-$ pairs, we search for the baryon and lepton number violating decays $D^+\to\barΛ(\barΣ^0)e^+$ and $D^+\toΛ(Σ^0)e^+$. No obvious signals are found with the current statistics and upper limits on the branching fractions of these four decays are set at the level of $10^{-6}$ at 90% confidence level.

preprint2020arXiv

Search for New Hadronic Decays of $h_c$ and Observation of $h_c\rightarrow K^{+}K^{-}π^{+}π^{-}π^{0}$

Ten hadronic final states of the $h_c$ decays are investigated via the process $ψ(3686)\rightarrow π^0 h_c$, using a data sample of $(448.1 \pm 2.9) \times 10^6$ $ψ(3686)$ events collected with the BESIII detector. The decay channel $h_c\rightarrow K^{+}K^{-}π^{+}π^{-}π^{0}$ is observed for the first time with a significance of $6.0 σ$. The corresponding branching fraction is determined to be $\mathcal{B}(h_c\rightarrow K^{+}K^{-}π^{+}π^{-}π^{0}) =(3.3 \pm 0.6 \pm 0.6)\times 10^{-3}$ (the first uncertainty is statistical and the second systematical). Evidence for the decays $h_c\rightarrow π^{+} π^{-} π^{0} η$ and $h_c\rightarrow K^{0}_{S}K^{\pm}π^{\mp}π^{+}π^{-}$ is found with a significance of $3.6 σ$ and $3.8 σ$, respectively. The corresponding branching fractions (and upper limits) are obtained to be $\mathcal{B}(h_c\rightarrow π^{+} π^{-} π^{0} η) =(7.2 \pm 1.8 \pm 1.3)\times 10^{-3}$ $(< 1.8 \times 10^{-2})$ and $\mathcal{B}(h_c\rightarrow K^{0}_{S}K^{\pm}π^{\mp}π^{+}π^{-}) =(2.8 \pm 0.9 \pm 0.5)\times 10^{-3}$ $(<4.7\times 10^{-3})$. Upper limits on the branching fractions for the final states $h_c \rightarrow K^{+}K^{-}π^{0}$, $K^{+}K^{-}η$, $K^{+}K^{-}π^{+}π^{-}η$, $2(K^{+}K^{-})π^{0}$, $K^{+}K^{-}π^{0}η$, $K^{0}_{S}K^{\pm}π^{\mp}$, and $p\bar{p}π^{0}π^{0}$ are determined at a confidence level of 90\%.

preprint2020arXiv

Search for the decay $J/ψ\toγ+ \rm {invisible}$

We search for $J/ψ$ radiative decays into a weakly interacting neutral particle, namely an invisible particle, using the $J/ψ$ produced through the process $ψ(3686)\toπ^+π^-J/ψ$ in a data sample of $(448.1\pm2.9)\times 10^6$ $ψ(3686)$ decays collected by the BESIII detector at BEPCII. No significant signal is observed. Using a modified frequentist method, upper limits on the branching fractions are set under different assumptions of invisible particle masses up to 1.2 $\mathrm{\ Ge\kern -0.1em V}/c^2$. The upper limit corresponding to an invisible particle with zero mass is 7.0$\times 10^{-7}$ at the 90\% confidence level.

preprint2020arXiv

Search for the semileptonic decay $D^{0(+)}\to b_1(1235)^{-(0)} e^+ν_e$

Using $2.93~\mathrm{fb}^{-1}$ of $e^+e^-$ annihilation data collected at a center-of-mass energy $\sqrt{s}=3.773$ GeV with the BESIII detector operating at the BEPCII collider, we search for the semileptonic $D^{0(+)}$ decays into a $b_1(1235)^{-(0)}$ axial-vector meson for the first time. No significant signal is observed for either charge combination. The upper limits on the product branching fractions are ${\mathcal B}_{D^0\to b_1(1235)^- e^+ν_e}\cdot {\mathcal B}_{b_1(1235)^-\to ωπ^-}<1.12\times 10^{-4}$ and ${\mathcal B}_{D^+\to b_1(1235)^0 e^+ν_e}\cdot {\mathcal B}_{b_1(1235)^0\to ωπ^0}<1.75\times 10^{-4}$ at the 90\% confidence level.

preprint2020arXiv

Segmentation-based Method combined with Dynamic Programming for Brain Midline Delineation

The midline related pathological image features are crucial for evaluating the severity of brain compression caused by stroke or traumatic brain injury (TBI). The automated midline delineation not only improves the assessment and clinical decision making for patients with stroke symptoms or head trauma but also reduces the time of diagnosis. Nevertheless, most of the previous methods model the midline by localizing the anatomical points, which are hard to detect or even missing in severe cases. In this paper, we formulate the brain midline delineation as a segmentation task and propose a three-stage framework. The proposed framework firstly aligns an input CT image into the standard space. Then, the aligned image is processed by a midline detection network (MD-Net) integrated with the CoordConv Layer and Cascade AtrousCconv Module to obtain the probability map. Finally, we formulate the optimal midline selection as a pathfinding problem to solve the problem of the discontinuity of midline delineation. Experimental results show that our proposed framework can achieve superior performance on one in-house dataset and one public dataset.

preprint2020arXiv

Self-controlled growth of highly uniform Ge/Si hut wires for scalable qubit devices

Semiconductor nanowires have been playing a crucial role in the development of nanoscale devices for the realization of spin qubits, Majorana fermions, single photon emitters, nanoprocessors, etc. The monolithic growth of site-controlled nanowires is a prerequisite towards the next generation of devices that will require addressability and scalability. Here, combining top-down nanofabrication and bottom-up self-assembly, we report on the growth of Ge wires on pre-patterned Si (001) substrates with controllable position, distance, length and structure. This is achieved by a novel growth process which uses a SiGe strain-relaxation template and can be generalized to other material combinations. Transport measurements show an electrically tunable spin-orbit coupling, with a spin-orbit length similar to that of III-V materials. Also, capacitive coupling between closely spaced wires is observed, which underlines their potential as a host for implementing two qubit gates. The reported results open a path towards scalable qubit devices with Si compatibility.

preprint2020arXiv

Softmax Splatting for Video Frame Interpolation

Differentiable image sampling in the form of backward warping has seen broad adoption in tasks like depth estimation and optical flow prediction. In contrast, how to perform forward warping has seen less attention, partly due to additional challenges such as resolving the conflict of mapping multiple pixels to the same target location in a differentiable way. We propose softmax splatting to address this paradigm shift and show its effectiveness on the application of frame interpolation. Specifically, given two input frames, we forward-warp the frames and their feature pyramid representations based on an optical flow estimate using softmax splatting. In doing so, the softmax splatting seamlessly handles cases where multiple source pixels map to the same target location. We then use a synthesis network to predict the interpolation result from the warped representations. Our softmax splatting allows us to not only interpolate frames at an arbitrary time but also to fine tune the feature pyramid and the optical flow. We show that our synthesis approach, empowered by softmax splatting, achieves new state-of-the-art results for video frame interpolation.

preprint2020arXiv

Study of $e^{+}e^{-} \to D^{+} D^{-} π^{+} π^{-} $ at center-of-mass energies from 4.36 to 4.60 GeV

We report a study of the $e^{+}e^{-} \to D^{+} D^{-} π^{+} π^{-}$ process using $e^{+}e^{-}$ collision data samples with an integrated luminosity of $2.5\,\rm{fb}^{-1}$ at center-of-mass energies from 4.36 to $4.60 \rm{GeV}$, collected with the BESIII detector at the BEPCII storage ring. The $D_{1}(2420)^+$ is observed in the $D^{+} π^{+} π^{-}$ mass spectrum. The mass and width of the $D_{1}(2420)^+$ are measured to be $(2427.2\pm 1.0_{\rm stat.}\pm 1.2_{\rm syst.}) \rm{MeV}/c^2$ and $(23.2\pm 2.3_{\rm stat.} \pm2.3_{\rm syst.}) \rm{MeV}$, respectively. The first errors are statistical and the second ones are systematic. In addition, the Born cross sections of the $e^{+}e^{-} \to D_{1}(2420)^+D^- + c.c. \to D^{+} D^{-} π^{+} π^{-}$ and $e^{+}e^{-} \to ψ(3770) π^{+} π^{-} \to D^{+} D^{-} π^{+} π^{-}$ processes are measured as a function of the center-of-mass energy.

preprint2020arXiv

Study of BESIII Trigger Efficiencies with the 2018 $J/ψ$ Data

Using a dedicated data sample taken in 2018 on the $J/ψ$ peak, we perform a detailed study of the trigger efficiencies of the BESIII detector. The efficiencies are determined from three representative physics processes, namely Bhabha-scattering, dimuon production and generic hadronic events with charged particles. The combined efficiency of all active triggers approaches $100\%$ in most cases with uncertainties small enough as not to affect most physics analyses.

preprint2020arXiv

Study of open-charm decays and radiative transitions of the X(3872)

The processes $X(3872)\to D^{*0}\bar{D^{0}}+c.c.,~γJ/ψ,~γψ(2S),$ and $γD^{+}D^{-}$ are searched for in a $9.0~\rm fb^{-1}$ data sample collected at center-of-mass energies between $4.178$ and $4.278$ GeV with the BESIII detector. We observe $X(3872)\to D^{*0}\bar{D^{0}}+c.c.$ and find evidence for $X(3872)\toγJ/ψ$ with statistical significances of $7.4σ$ and $3.5σ$, respectively. No evident signals for $X(3872)\toγψ(2S)$ and $γD^{+}D^{-}$ are found, and upper limit on the relative branching ratio $R_{γψ} \equiv\frac{\mathcal{B}(X(3872)\toγψ(2S))}{\mathcal{B}(X(3872)\toγJ/ψ)}<0.59$ is set at 90$\%$ confidence level. Measurements of branching ratios relative to decay $X(3872)\toπ^+π^- J/ψ$ are also reported for decays $X(3872)\to D^{*0}\bar{D^{0}}+c.c., ~γψ(2S),~γJ/ψ$, $γD^{+}D^{-}$, as well as the non-$D^{*0}\bar{D}^{0}$ three-body decays $π^0 D^{0}\bar{D}^{0}$ and $γD^{0}\bar{D}^{0}$.

preprint2020arXiv

Terahertz composite plasmonic slabs based on double-layer metallic gratings

A composite plasmonic slab based on double-layer metallic gratings and a dielectric film is experimentally and numerically demonstrated in terahertz (THz) regions, which can support two resonance modes and then form a broad bandgap (40%). As compared to the double-layer metal grating, the dielectric film in composite THz slabs significantly enhances the transmission of the transverse magnetic (TM) mode. Electric field vector proved that the low-frequency resonance mode originates from the symmetric plasmonic mode and the high-frequency resonance mode is induced by the hybrid mode of plasmonic and dielectric modes. The inherently near field coupling between metal gratings and dielectric film has been analyzed by changing the structural parameters. We further demonstrate that by tuning the metallic grating width, the plasmonic bandgap can be manipulated. These results suggest that this composite plasmonic slab has great potential for use as a filter, polarizer, and sensor in THz regions.

preprint2020arXiv

Terahertz metallic photonic crystals integrated with dielectric waveguides

Compact and low-loss photonic crystal waveguides are critical in integrated terahertz (THz) applications. Compared with pure metal or dielectric photonic crystal waveguides, hybrid (metal-dielectric) integrated waveguides provide a simple way to further improve the field confinement and the propagation loss. In this work, we investigate a hybrid waveguide consisting of metallic photonic crystals and dielectric films in 0.1-1.0 THz. Photonic crystal waveguides based on metal pillar arrays (MPAs) support two resonance modes including the fundamental and high-order transverse magnetic (TM) modes and then form one apparent bandgap in 0.45-0.55 THz. The high-order TM-mode shows higher confinement than the fundamental mode and are thus sensitive to the dielectric film on the MPAs. The propagation loss and field confinement can be optimized by changing the dielectric film thickness and refractive index. The investigation shows that the lowest loss occurs at 0.68 THz because the high-order TM-mode THz waves are tightly confined inside the hybrid waveguide. This work proves that such hybrid waveguides based on metallic photonic crystals are promising to develop as a compact integrated terahertz device.

preprint2020arXiv

Topological Phase Transitions in a Hybridized Three-Dimensional Topological Insulator

As the thickness of a three-dimensional (3D) topological insulator (TI) becomes comparable to the penetration depth of the surface states, quantum tunneling between surfaces turns their gapless Dirac electronic structure into a gapped surface state. Analytical formulation suggests that the hybridization gap scales exponentially with decrease in number of layers while the system oscillates between topologically trivial and non-trivial insulators. This work explores the transport properties of a 3D TI in the inter-surface hybridization regime. By experimentally probing the hybridization gap as a function of BiSbTeSe2 thickness using three different methods, we map the crossover from the 3D to 2D state. In the 2D topological state, we observe a finite longitudinal conductance at ~2e2/h when the Fermi level is aligned within the surface gap, indicating a quantum spin Hall (QSH) state. Additionally, we study the response of trivial and non-trivial hybridization gapped states modulated by external out-of-plane magnetic and electric fields. Our revelations of surface gap-closing and/or reopening features are strongly indicative of topological phase transitions (TPTs) in the hybridization gap regime, realizing magnetic/electric field switching between band insulating and QSH states with immense potential for practical applications.

preprint2020arXiv

xQSM: Quantitative Susceptibility Mapping with Octave Convolutional and Noise Regularized Neural Networks

Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed dipole inversion process. In this study, a new deep learning method for QSM reconstruction, namely xQSM, was designed by introducing modified state-of-the-art octave convolutional layers into the U-net backbone. The xQSM method was compared with recentlyproposed U-net-based and conventional regularizationbased methods, using peak signal to noise ratio (PSNR), structural similarity (SSIM), and region-of-interest measurements. The results from a numerical phantom, a simulated human brain, four in vivo healthy human subjects, a multiple sclerosis patient, a glioblastoma patient, as well as a healthy mouse brain showed that the xQSM led to suppressed artifacts than the conventional methods, and enhanced susceptibility contrast, particularly in the ironrich deep grey matter region, than the original U-net, consistently. The xQSM method also substantially shortened the reconstruction time from minutes using conventional iterative methods to only a few seconds.

preprint2019arXiv

Magnetic Weyl semimetals with diamond structure realized in spinel compounds

Diamond-structure materials have been extensively studied for decades, which form the foundation for most semiconductors and their modern day electronic devices. Here, we discover a e$_g$-orbital ($d_{z^2}$,$d_{x^2-y^2}$ ) model within the diamond lattice (e$_g$-diamond model) that hosts novel topological states. Specifically, the e$_g$-diamond model yields a 3D nodal cage (3D-NC), which is characterized by a $d$-$d$ band inversion protected by two types of degenerate states (i.e., e$_g$-orbital and diamond-sublattice degeneracies). We demonstrate materials realization of this model in the well-known spinel compounds (AB$_2$X$_4$), where the tetrahedron-site cations (A) form the diamond sub-lattice. An ideal half metal with one metallic spin channel formed by well-isolated and half-filled e$_g$-diamond bands, accompanied by a large spin gap (4.36 eV) is discovered in one 4-2 spinel compound (VMg$_2$O$_4$), which becomes a magnetic Weyl semimetal when spin-orbit coupling effect is further considered. Our discovery greatly enriches the physics of diamond structure and spinel compounds, opening a door to their application in spintronics.

preprint2019arXiv

Observation of the decays $χ_{cJ} \to ϕϕη$

Using a data sample of $(448.1\pm2.9)\times10^{6}$ $ψ(3686)$ decays collected by the BESIII detector at the Beijing Electron Positron Collider (BEPCII), we observe the decays $χ_{cJ}\to ϕϕη~(J=0,~1,~2)$, where the $χ_{cJ}$ are produced via the radiative processes $ψ(3686)\toγχ_{cJ}$. The branching fractions are measured to be $\mathcal B(χ_{c0}\toϕϕη)=(8.41\pm0.74\pm0.62)\times10^{-4}$, $\mathcal B(χ_{c1}\toϕϕη)=(2.96\pm0.43\pm0.22)\times 10^{-4}$, and $\mathcal B(χ_{c2} \to ϕϕη)=(5.33\pm0.52\pm0.39) \times 10^{-4}$, where the first uncertainties are statistical and the second are systematic. We also search for intermediate states in the $ϕϕ$ or $ηϕ$ combinations, but no significant structure is seen due to the limited statistics.

preprint2019arXiv

Search for the rare decay $η'\rightarrowπ^{0}π^{0}π^{0}π^{0}$ at BESIII

Based on a sample of 1.31 billion $J/ψ$ events collected with the BESIII detector, we perform a search for the rare decay $η'\rightarrow 4π^{0}$ via $J/ψ\rightarrowγη'$. No significant $η'$ signal is observed in the invariant mass spectrum of 4$π^{0}$. With a Bayesian approach, the upper limit on the branching fraction of $η'\rightarrow 4π^{0}$ is determined to be $\mathcal{B}(η'\rightarrow 4π^{0})$ $< 4.94\times10^{-5}$ at the 90\% confidence level, which is a factor of six smaller than the previous experimental limit.

preprint2017arXiv

Observation of the decay $Λ_c^+\rightarrow Σ^- π^+π^+π^0$

We report the first observation of the decay $Λ^+_{c}\rightarrow Σ^- π^+π^+π^0$, based on data obtained in $e^+e^-$ annihilations with an integrated luminosity of 567~pb$^{-1}$ at $\sqrt{s}=4.6$~GeV. The data were collected with the BESIII detector at the BEPCII storage rings. The absolute branching fraction $\mathcal{B}(Λ^+_{c}\rightarrowΣ^-π^+π^+π^0)$ is determined to be $(2.11\pm0.33({\rm stat.})\pm0.14({\rm syst.}))\%$. In addition, an improved measurement of $\mathcal{B}(Λ^+_{c}\rightarrowΣ^-π^+π^+)$ is determined as $(1.81\pm0.17({\rm stat.})\pm0.09({\rm syst.}))\%$.

preprint2015arXiv

Measurement of the $\mathrm e^+\mathrm e^-\rightarrow\mathrmπ^+\mathrmπ^-$ Cross Section between 600 and 900 MeV Using Initial State Radiation

We extract the $e^+e^-\rightarrow π^+π^-$ cross section in the energy range between 600 and 900 MeV, exploiting the method of initial state radiation. A data set with an integrated luminosity of 2.93 fb$^{-1}$ taken at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider is used. The cross section is measured with a systematic uncertainty of 0.9%. We extract the pion form factor $|F_π|^2$ as well as the contribution of the measured cross section to the leading order hadronic vacuum polarization contribution to $(g-2)_μ$. We find this value to be $a_μ^{ππ,\rm LO}(600-900\;\rm MeV) = (368.2 \pm 2.5_{\rm stat} \pm 3.3_{\rm sys})\cdot 10^{-10}$.

Feng Liu

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157 published item(s)

UniCorrn: Unified Correspondence Transformer Across 2D and 3D

Generalising Traffic Forecasting to Regions without Traffic Observations

SCP: Accelerating Discovery with a Global Web of Autonomous Scientific Agents

From Data to Insights: A Comprehensive Survey on Advanced Applications in Thyroid Cancer Research

Investigation of the $ΔI = 1/2$ rule and test of CP violation through the measurement of decay asymmetry parameters in $Ξ^-$ decays

Millikelvin confocal microscope with free-space access and high-frequency electrical control

Search for hidden-charm tetraquark with strangeness in $e^{+}e^{-}\rightarrow K^+ D_{s}^{*-} D^{*0}+c.c.$

2D GANs Meet Unsupervised Single-view 3D Reconstruction

A novel stereo matching pipeline with robustness and unfixed disparity search range

A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images

Adversarial Attack and Defense for Non-Parametric Two-Sample Tests

Amplitude analysis and branching fraction measurement of the decay $D_{s}^{+} \to K^+π^+π^-$

Amplitude analysis and branching-fraction measurement of $D_{s}^{+} \to π^{+}π^{0}η^{\prime}$

Balanced Graph Structure Learning for Multivariate Time Series Forecasting

BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks

Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels

Controllable and Guided Face Synthesis for Unconstrained Face Recognition

Cross section measurements of the processes $e^+e^- \rightarrow ωπ^{0}$ and $ωη$ at center-of-mass energies between 3.773 and 4.701 GeV

Disentangleing Content and Fine-grained Prosody Information via Hybrid ASR Bottleneck Features for Voice Conversion

Double-Pulse Generation of Indistinguishable Single Photons with Optically Controlled Polarization

Edge states in a non-Hermitian topological crystalline insulator

Effective Model for Fractional Topological Corner Modes in Quasicrystals

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack

First Observation of the Semileptonic Decay $Λ_c^+\rightarrow pK^- e^+ν_e$

FRT-PAD: Effective Presentation Attack Detection Driven by Face Related Task

Identifying the phase diagram structure for optimal information integration in morphogen systems

Incentive Mechanism Design for Emergency Frequency Control in Multi-Infeed Hybrid AC-DC System

Instant tissue field and magnetic susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks

Laser plasma accelerated ultra-intense electron beam for efficiently exciting nuclear isomers

Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects

Measurement of $e^{+}e^{-} \to K^{+}K^{-}π^{0}$ cross section and observation of a resonant structure

Measurement of $Λ$ baryon polarization in $e^+e^-\rightarrowΛ\barΛ$ at $\sqrt{s} = 3.773$ GeV

Measurement of the $D \to K^-π^+π^+π^-$ and $D \to K^-π^+π^0$ coherence factors and average strong-phase differences in quantum-correlated ${D\bar{D}}$ decays

Measurement of the branching fraction and decay asymmetry of $Λ\to nγ$

Measurement of the branching fraction for $ψ(3686)\to ωK^0_SK^0_S$

Measurement of the branching fraction of the doubly Cabibbo-suppressed decay $D^0\to K^+π^-π^0$ and search for $D^0\to K^+π^-π^0π^0$

Measurement of the Cross Section for $e^{+}e^{-}\to$ hadrons at Energies from 2.2324 to 3.6710 GeV

Measurement of the cross section of $e^{+}e^{-}\toηπ^{+}π^{-}$ at center-of-mass energies from 3.872 GeV to 4.700 GeV

Measurement of the total and leptonic decay widths of the $J/ψ$ resonance with an energy scan method at BESIII

Measurements of Absolute Branching Fractions of $D^0\to K_L^0ϕ$, $K_L^0η$, $K_L^0ω$, and $K_L^0η^{\prime}$

Measurements of the absolute branching fractions of hadronic $D$-meson decays involving kaons and pions

Meta Discovery: Learning to Discover Novel Classes given Very Limited Data

Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data

Multi-channel deep convolutional neural networks for multi-classifying thyroid disease

Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms

Nanomechanical Characterization of an Antiferromagnetic Topological Insulator

Negative Interatomic Spring Constant Manifested by Topological Phonon Flat Band

Neighborhood Collective Estimation for Noisy Label Identification and Correction

Observation of $a_0(1710)^+ \to K_S^0K^+$ in study of the $D_s^+\to K_S^0K^+π^0$ decay

Observation of $η_c(2S) \to 3(π^+π^-)$ and measurements of $χ_{cJ} \to 3(π^+π^-)$ in $ψ(3686)$ radiative transitions

Observation of resonance structures in $e^+e^-\to π^+π^-ψ_2(3823)$ and mass measurement of $ψ_2(3823)$

Observation of the double Dalitz decay $η&#39;\to e^+e^-e^+e^-$

Observation of the electromagnetic Dalitz decay $D^{\ast 0}\to D^{0}e^{+}e^{-}$

Observation of the Singly Cabibbo-Suppressed Decay $Λ_{c}^{+} \to nπ^{+}$

On Nash-Stackelberg-Nash Games under Decision-Dependent Uncertainties: Model and Equilibrium

Orbital Design of Flat Bands in Non-Line-Graph Lattices via Line-Graph Wavefunctions

Partial wave analysis of $J/ψ\to γη^{\prime} η^{\prime}$

Practical considerations for the effect of finite coverage on the azimuthal dependence of global spin alignment

Probabilistic Margins for Instance Reweighting in Adversarial Training

Robust Representation via Dynamic Feature Aggregation

Search for $X(3872)\toπ^0χ_{c0}$ and $X(3872)\toππχ_{c0}$ at BESIII

Search for baryon and lepton number violating decays $D^{0}\to \bar{p}e^{+}$ and $D^{0}\to pe^{-}$

Search for baryon and lepton number violation decay $D^{\pm}\to n(\bar{n})e^{\pm}$

Search for invisible decays of the $Λ$ baryon

Search for new hadronic decays of $h_{c}$ and observation of $h_{c}\to p\bar{p}η$

Search for the decay $D^{0} \to π^{0} ν\barν$

Search for the decay $h_c\rightarrowπ^0J/ψ$

Shift-tolerant Perceptual Similarity Metric

SNeRF: Stylized Neural Implicit Representations for 3D Scenes

The State of Aerial Surveillance: A Survey

TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation

Search for hidden-charm tetraquark with strangeness in $e^{+}e^{-}\rightarrow K^+ D_{s}^{-} D^{0}+c.c.$

Observation of the double Dalitz decay $η'\to e^+e^-e^+e^-$

Cross section measurements of the $e^+e^-\to D^{+}D^{-}$ and $e^+e^-\to D^{*+}D^{-}$ processes at center-of-mass energies from 4.085 to 4.600 GeV

Cross section measurement of $e^+e^- \rightarrow η'J/ψ$ from $\sqrt{s} = 4.178$ to $4.600$ GeV

Erratum to "Measurement of the $e^+e^-\toπ^+π^-$ cross section between 600 and 900 MeV using initial state radiation"