Source author record

Wei Zhu

Wei Zhu appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record

Catalog footprint

What is connected

102works

42topics

4close collaborators

Actions

Connect this record

Open graph Browse works

Inspect adjacent papers, topics, institutions and collaborators without losing the researcher page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

preprint2026arXiv

Noise-Started One-Step Real-World Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement

Pre-trained text-to-image (T2I) diffusion models have shown strong potential for real-world image super-resolution (Real-ISR), owing to their noise-started generation process that enables realistic texture synthesis and captures the one-to-many nature of super-resolution. However, diffusion-based Real-ISR methods still face a fundamental efficiency-quality trade-off. Multi-step methods generate high-quality results by iteratively denoising random Gaussian noise under LR conditioning, but suffer from slow sampling. Recent one-step methods greatly improve efficiency, yet they typically replace noise-started generation with direct LR-to-HR restoration, which weakens stochasticity and limits realistic detail synthesis. To address this issue, we propose SMFSR, a noise-started one-step Real-ISR framework via LR-conditioned SplitMeanFlow and GAN refinement. SMFSR preserves the random-noise starting point of diffusion models and learns a direct noise-to-HR mapping conditioned on the LR image. To this end, Interval Splitting Consistency distills the multi-step generative trajectory into a single average-velocity prediction, enabling efficient one-step generation. To compensate for the reduced opportunity for progressive refinement, we further introduce a GAN refinement stage, where a DINOv3-based discriminator enhances realistic texture synthesis and variational score distillation aligns the generated outputs with the natural image distribution under a frozen diffusion teacher. Extensive experiments demonstrate that SMFSR achieves state-of-the-art perceptual quality among one-step diffusion-based Real-ISR methods while retaining fast single-step inference.

preprint2024arXiv

Efficient Multi-domain Text Recognition Deep Neural Network Parameterization with Residual Adapters

Recent advancements in deep neural networks have markedly enhanced the performance of computer vision tasks, yet the specialized nature of these networks often necessitates extensive data and high computational power. Addressing these requirements, this study presents a novel neural network model adept at optical character recognition (OCR) across diverse domains, leveraging the strengths of multi-task learning to improve efficiency and generalization. The model is designed to achieve rapid adaptation to new domains, maintain a compact size conducive to reduced computational resource demand, ensure high accuracy, retain knowledge from previous learning experiences, and allow for domain-specific performance improvements without the need to retrain entirely. Rigorous evaluation on open datasets has validated the model's ability to significantly lower the number of trainable parameters without sacrificing performance, indicating its potential as a scalable and adaptable solution in the field of computer vision, particularly for applications in optical text recognition.

preprint2024arXiv

Text2MDT: Extracting Medical Decision Trees from Medical Texts

Knowledge of the medical decision process, which can be modeled as medical decision trees (MDTs), is critical to build clinical decision support systems. However, the current MDT construction methods rely heavily on time-consuming and laborious manual annotation. In this work, we propose a novel task, Text2MDT, to explore the automatic extraction of MDTs from medical texts such as medical guidelines and textbooks. We normalize the form of the MDT and create an annotated Text-to-MDT dataset in Chinese with the participation of medical experts. We investigate two different methods for the Text2MDT tasks: (a) an end-to-end framework which only relies on a GPT style large language models (LLM) instruction tuning to generate all the node information and tree structures. (b) The pipeline framework which decomposes the Text2MDT task to three subtasks. Experiments on our Text2MDT dataset demonstrate that: (a) the end-to-end method basd on LLMs (7B parameters or larger) show promising results, and successfully outperform the pipeline methods. (b) The chain-of-thought (COT) prompting method \cite{Wei2022ChainOT} can improve the performance of the fine-tuned LLMs on the Text2MDT test set. (c) the lightweight pipelined method based on encoder-based pretrained models can perform comparably with LLMs with model complexity two magnititudes smaller. Our Text2MDT dataset is open-sourced at \url{https://tianchi.aliyun.com/dataset/95414}, and the source codes are open-sourced at \url{https://github.com/michael-wzhu/text2dt}.

preprint2023arXiv

Overview of the PromptCBLUE Shared Task in CHIP2023

This paper presents an overview of the PromptCBLUE shared task (http://cips-chip.org.cn/2023/eval1) held in the CHIP-2023 Conference. This shared task reformualtes the CBLUE benchmark, and provide a good testbed for Chinese open-domain or medical-domain large language models (LLMs) in general medical natural language processing. Two different tracks are held: (a) prompt tuning track, investigating the multitask prompt tuning of LLMs, (b) probing the in-context learning capabilities of open-sourced LLMs. Many teams from both the industry and academia participated in the shared tasks, and the top teams achieved amazing test results. This paper describes the tasks, the datasets, evaluation metrics, and the top systems for both tasks. Finally, the paper summarizes the techniques and results of the evaluation of the various approaches explored by the participating teams.

preprint2022arXiv

A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation

Early exiting allows instances to exit at different layers according to the estimation of difficulty. Previous works usually adopt heuristic metrics such as the entropy of internal outputs to measure instance difficulty, which suffers from generalization and threshold-tuning. In contrast, learning to exit, or learning to predict instance difficulty is a more appealing way. Though some effort has been devoted to employing such "learn-to-exit" modules, it is still unknown whether and how well the instance difficulty can be learned. As a response, we first conduct experiments on the learnability of instance difficulty, which demonstrates that modern neural models perform poorly on predicting instance difficulty. Based on this observation, we propose a simple-yet-effective Hash-based Early Exiting approach (HashEE) that replaces the learn-to-exit modules with hash functions to assign each token to a fixed exiting layer. Different from previous methods, HashEE requires no internal classifiers nor extra parameters, and therefore is more efficient. Experimental results on classification, regression, and generation tasks demonstrate that HashEE can achieve higher performance with fewer FLOPs and inference time compared with previous state-of-the-art early exiting methods.

preprint2022arXiv

AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor

The AlphaFold computer program predicted protein structures for the whole human genome, which has been considered as a remarkable breakthrough both in artificial intelligence (AI) application and structural biology. Despite the varying confidence level, these predicted structures still could significantly contribute to structure-based drug design of novel targets, especially the ones with no or limited structural information. In this work, we successfully applied AlphaFold in our end-to-end AI-powered drug discovery engines constituted of a biocomputational platform PandaOmics and a generative chemistry platform Chemistry42, to identify a first-in-class hit molecule of a novel target without an experimental structure starting from target selection towards hit identification in a cost- and time-efficient manner. PandaOmics provided the targets of interest and Chemistry42 generated the molecules based on the AlphaFold predicted structure, and the selected molecules were synthesized and tested in biological assays. Through this approach, we identified a small molecule hit compound for CDK20 with a Kd value of 8.9 +/- 1.6 uM (n = 4) within 30 days from target selection and after only synthesizing 7 compounds. Based on the available data, the second round of AI-powered compound generation was conducted and through which, a more potent hit molecule, ISM042-2 048, was discovered with a Kd value of 210.0 +/- 42.4 nM (n = 2), within 30 days and after synthesizing 6 compounds from the discovery of the first hit ISM042-2-001. To the best of our knowledge, this is the first reported small molecule targeting CDK20 and more importantly, this work is the first demonstration of AlphaFold application in the hit identification process in early drug discovery.

preprint2022arXiv

Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuning

Since open social platforms allow for a large and continuous flow of unverified information, rumors can emerge unexpectedly and spread quickly. However, existing rumor detection (RD) models often assume the same training and testing distributions and can not cope with the continuously changing social network environment. This paper proposed a Continual Prompt-Tuning RD (CPT-RD) framework, which avoids catastrophic forgetting (CF) of upstream tasks during sequential task learning and enables bidirectional knowledge transfer between domain tasks. Specifically, we propose the following strategies: (a) Our design explicitly decouples shared and domain-specific knowledge, thus reducing the interference among different domains during optimization; (b) Several technologies aim to transfer knowledge of upstream tasks to deal with emergencies; (c) A task-conditioned prompt-wise hypernetwork (TPHNet) is used to consolidate past domains. In addition, CPT-RD avoids CF without the necessity of a rehearsal buffer.

preprint2022arXiv

Deep Federated Anomaly Detection for Multivariate Time Series Data

Despite the fact that many anomaly detection approaches have been developed for multivariate time series data, limited effort has been made on federated settings in which multivariate time series data are heterogeneously distributed among different edge devices while data sharing is prohibited. In this paper, we investigate the problem of federated unsupervised anomaly detection and present a Federated Exemplar-based Deep Neural Network (Fed-ExDNN) to conduct anomaly detection for multivariate time series data on different edge devices. Specifically, we first design an Exemplar-based Deep Neural network (ExDNN) to learn local time series representations based on their compatibility with an exemplar module which consists of hidden parameters learned to capture varieties of normal patterns on each edge device. Next, a constrained clustering mechanism (FedCC) is employed on the centralized server to align and aggregate the parameters of different local exemplar modules to obtain a unified global exemplar module. Finally, the global exemplar module is deployed together with a shared feature encoder to each edge device and anomaly detection is conducted by examining the compatibility of testing data to the exemplar module. Fed-ExDNN captures local normal time series patterns with ExDNN and aggregates these patterns by FedCC, and thus can handle the heterogeneous data distributed over different edge devices simultaneously. Thoroughly empirical studies on six public datasets show that ExDNN and Fed-ExDNN can outperform state-of-the-art anomaly detection algorithms and federated learning techniques.

preprint2022arXiv

Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting

Chemistry research has both high material and computational costs to conduct experiments. Institutions thus consider chemical data to be valuable and there have been few efforts to construct large public datasets for machine learning. Another challenge is that different intuitions are interested in different classes of molecules, creating heterogeneous data that cannot be easily joined by conventional distributed training. In this work, we introduce federated heterogeneous molecular learning to address these challenges. Federated learning allows end-users to build a global model collaboratively while keeping the training data distributed over isolated clients. Due to the lack of related research, we first simulate a heterogeneous federated learning benchmark (FedChem) by jointly performing scaffold splitting and latent Dirichlet allocation on existing datasets for heterogeneously distributed client data. Our results on FedChem show that significant learning challenges arise when working with heterogeneous molecules across clients. We then propose a method to alleviate the problem, namely Federated Learning by Instance reweighTing (FLIT(+)). FLIT(+) can align the local training across heterogeneous clients by improving the performance for uncertain samples. Comprehensive experiments conducted on our new benchmark FedChem validate the advantages of this method over other federated learning schemes. FedChem should enable a new type of collaboration for improving AI in chemistry that mitigates concerns about valuable chemical data.

preprint2022arXiv

Fluid Simulation System Based on Graph Neural Network

Traditional computational fluid dynamics calculates the physical information of the flow field by solving partial differential equations, which takes a long time to calculate and consumes a lot of computational resources. We build a fluid simulation simulator based on the graph neural network architecture. The simulator has fast computing speed and low consumption of computing resources. We regard the computational domain as a structural graph, and the computational nodes in the structural graph determine neighbor nodes through adaptive sampling. Building deep learning architectures with attention graph neural networks. The fluid simulation simulator is trained according to the simulation results of the flow field around the cylinder with different Reynolds numbers. The trained fluid simulation simulator not only has a very high accuracy for the prediction of the flow field in the training set, but also can extrapolate the flow field outside the training set. Compared to traditional CFD solvers, the fluid simulation simulator achieves a speedup of 2-3 orders of magnitude. The fluid simulation simulator provides new ideas for the rapid optimization and design of fluid mechanics models and the real-time control of intelligent fluid mechanisms.

preprint2022arXiv

Identification of stellar-mass black hole binaries and the validity of linear orbital motion approximation in microlensing

Gravitational microlensing is unique in detecting binary black (BH) holes with wide (a few au) separations. Models predict that about $1\%$ of microlensing binaries should be due to binary BHs, and yet zero has been robustly identified. Using simulated events with binary BH lenses, we show that the microlensing parallax effect in a typical binary BH event cannot be reliably detected. Given the crucial role of the parallax parameter in determining the mass of dark microlenses, this may explain the non-detection of binary BHs. Additionally, we show that in only a small fraction ($\lesssim7\%$) of the simulated events the full orbital motion of the binary lens cannot be modeled with the linear orbital motion approximation. This approximation has been frequently used in modelings of binary microlensing events.

preprint2022arXiv

Improving Micro-video Recommendation by Controlling Position Bias

As the micro-video apps become popular, the numbers of micro-videos and users increase rapidly, which highlights the importance of micro-video recommendation. Although the micro-video recommendation can be naturally treated as the sequential recommendation, the previous sequential recommendation models do not fully consider the characteristics of micro-video apps, and in their inductive biases, the role of positions is not in accord with the reality in the micro-video scenario. Therefore, in the paper, we present a model named PDMRec (Position Decoupled Micro-video Recommendation). PDMRec applies separate self-attention modules to model micro-video information and the positional information and then aggregate them together, avoid the noisy correlations between micro-video semantics and positional information being encoded into the sequence embeddings. Moreover, PDMRec proposes contrastive learning strategies which closely match with the characteristics of the micro-video scenario, thus reducing the interference from micro-video positions in sequences. We conduct the extensive experiments on two real-world datasets. The experimental results shows that PDMRec outperforms existing multiple state-of-the-art models and achieves significant performance improvements.

preprint2022arXiv

KMT-2021-BLG-0171Lb and KMT-2021-BLG-1689Lb: Two Microlensing Planets in the KMTNet High-cadence Fields with Followup Observations

Follow-up observations of high-magnification gravitational microlensing events can fully exploit their intrinsic sensitivity to detect extrasolar planets, especially those with small mass ratios. To make followup more uniform and efficient, we develop a system, HighMagFinder, based on the real-time data from the Korean Microlensing Telescope Network (KMTNet) to automatically alert possible ongoing high-magnification events. We started a new phase of follow-up observations with the help of HighMagFinder in 2021. Here we report the discovery of two planets in high-magnification microlensing events, KMT-2021-BLG-0171 and KMT-2021-BLG-1689, which were identified by the HighMagFinder. We find that both events suffer the ``central-resonant'' caustic degeneracy. The planet-host mass-ratio is $q\sim4.7\times10^{-5}$ or $q\sim 2.2\times10^{-5}$ for KMT-2021-BLG-0171, and $q\sim2.5\times10^{-4}$ or $q\sim 1.8\times10^{-4}$ for KMT-2021-BLG-1689. Together with two events reported by Ryu et al. (2022), four cases that suffer such degeneracy have been discovered in the 2021 season alone, indicating that the degenerate solutions may have been missed in some previous studies. We also propose a new factor for weighting the probability of each solution from the phase-space. The resonant interpretations for the two events are disfavored under this consideration. This factor can be included in future statistical studies to weight degenerate solutions.

preprint2022arXiv

Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis

Visual sentiment analysis has received increasing attention in recent years. However, the dataset's quality is a concern because the sentiment labels are crowd-sourcing, subjective, and prone to mistakes, and poses a severe threat to the data-driven models, especially the deep neural networks. The deep models would generalize poorly on the testing cases when trained to over-fit the training samples with noisy sentiment labels. Inspired by the recent progress on learning with noisy labels, we propose a robust learning method to perform robust visual sentiment analysis. Our method relies on external memory to aggregate and filters noisy labels during training. The memory is composed of the prototypes with corresponding labels, which can be updated online. The learned prototypes and their labels can be regarded as denoising features and labels for the local regions and can guide the training process to prevent the model from overfitting the noisy cases. We establish a benchmark for visual sentiment analysis with label noise using publicly available datasets. The experiment results of the proposed benchmark settings comprehensively show the effectiveness of our method.

preprint2022arXiv

Localized Adversarial Domain Generalization

Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attention on domain generalization (DG), which aims to the model's generalization ability to out-of-distribution. Adversarial domain generalization is a popular approach to DG, but conventional approaches (1) struggle to sufficiently align features so that local neighborhoods are mixed across domains; and (2) can suffer from feature space over collapse which can threaten generalization performance. To address these limitations, we propose localized adversarial domain generalization with space compactness maintenance~(LADG) which constitutes two major contributions. First, we propose an adversarial localized classifier as the domain discriminator, along with a principled primary branch. This constructs a min-max game whereby the aim of the featurizer is to produce locally mixed domains. Second, we propose to use a coding-rate loss to alleviate feature space over collapse. We conduct comprehensive experiments on the Wilds DG benchmark to validate our approach, where LADG outperforms leading competitors on most datasets.

preprint2022arXiv

No Significant Correlation between Line-emission and Continuum Substructures in the Molecules with ALMA at Planet-forming Scales Program

Recently, the Molecules with ALMA at Planet-forming Scales (MAPS) ALMA Large Program reported a high number of line emission substructures coincident with dust rings and gaps in the continuum emission, suggesting a causal link between these axisymmetric line emission and dust continuum substructures. To test the robustness of the claimed correlation, we compare the observed spatial overlap fraction in substructures with that from the null hypothesis, in which the overlap is assumed to arise from the random placement of line emission substructures. Our results reveal that there is no statistically significant evidence for a universal correlation between line emission and continuum substructures, questioning the frequently-made link between continuum rings and pressure bumps. The analysis also clearly identifies outliers. The chemical rings and the dust gaps in MWC 480 appear to be strongly correlated (${>}4σ$), and the gaps in the CO isotopologues tend to moderately (${\sim}3σ$) correlate with dust rings.

preprint2022arXiv

OGLE-2016-BLG-1093Lb: A Sub-Jupiter-mass Spitzer Planet Located in Galactic Bulge

OGLE-2016-BLG-1093 is a planetary microlensing event that is part of the statistical $Spitzer$ microlens parallax sample. The precise measurement of the microlens parallax effect for this event, combined with the measurement of finite source effects, leads to a direct measurement of the lens masses and system distance: $M_{\rm host} = 0.38$--$0.57\, M_{\odot}$, $m_p = 0.59$--$0.87\, M_{\rm Jup}$, and the system is located at the Galactic bulge ($D_L \sim 8.1$ kpc). Because this was a high-magnification event, we are also able to empirically show that the "cheap-space parallax" concept Gould & Yee (2012) produces well-constrained (and consistent) results for $|π_{\rm E}|$. This demonstrates that this concept can be extended to many two-body lenses. Finally, we briefly explore systematics in the $Spitzer$ light curve in this event and show that their potential impact is strongly mitigated by the color-constraint.

preprint2022arXiv

OGLE-2018-BLG-0799Lb: a $q \sim 2.7 \times 10^{-3}$ Planet with Spitzer Parallax

We report the discovery and analysis of a planet in the microlensing event OGLE-2018-BLG-0799. The planetary signal was observed by several ground-based telescopes, and the planet-host mass ratio is $q = (2.65 \pm 0.16) \times 10^{-3}$. The ground-based observations yield a constraint on the angular Einstein radius $θ_{\rm E}$, and the microlensing parallax vector $\vecπ_{\rm E}$, is strongly constrained by the Spitzer data. However, the 2019 Spitzer baseline data reveal systematics in the Spitzer photometry, so there is ambiguity in the magnitude of the parallax. In our preferred interpretation, a full Bayesian analysis using a Galactic model indicates that the planetary system is composed of an $M_{\rm planet} = 0.26_{-0.11}^{+0.22}~M_{J}$ planet orbiting an $M_{\rm host} = 0.093_{-0.038}^{+0.082}~M_{\odot}$, at a distance of $D_{\rm L} = 3.71_{-1.70}^{+3.24}$ kpc. An alternate interpretation of the data shifts the localization of the minima along the arc-shaped microlens parallax constraints. This, in turn, yields a more massive host with median mass of $0.13 {M_{\odot}}$ at a distance of 6.3 kpc. This analysis demonstrates the robustness of the osculating circles formalism, but shows that further investigation is needed to assess how systematics affect the specific localization of the microlens parallax vector and, consequently, the inferred physical parameters.

preprint2022arXiv

OGLE-2019-BLG-1470LABc: Another Microlensing Giant Planet in a Binary System?

We report the discovery and analysis of a candidate triple-lens single-source (3L1S) microlensing event, OGLE-2019-BLG-1470. This event was first classified as a normal binary-lens single-source (2L1S) event, but a careful 2L1S modelling showed that it needs an additional lens or source to fit the observed data. It is found that the 3L1S model provides the best fit, but the binary-lens binary-source (2L2S) model is only disfavoured by $Δχ^2 \simeq 18$. All of the feasible models include a planet with planet-to-host mass-ratios $10^{-3} \lesssim q \lesssim 10^{-2}$. A Bayesian analysis based on a Galactic model indicates that the planet is super-Jovian, and the projected host-planet separation is about 3 $\mathrm{au}$. Specifically, for the best-fit 3L1S model, the two stars have masses of $M_1=0.57^{+0.43}_{-0.32}M_{\odot}$, and $M_2=0.18^{+0.15}_{-0.10}M_{\odot}$, with projected separation of $1.3^{+0.5}_{-0.5}$ $\mathrm{au}$, and the planetary mass is $M_3=2.2^{+1.8}_{-1.3}M_{\rm{Jupiter}}$. For the 2L2S model, the masses of the host star and the planet are $0.55^{+0.44}_{-0.31}M_{\odot}$ and $4.6^{+3.7}_{-2.6}M_{\rm{Jupiter}}$, respectively. By investigating the properties of all known microlensing planets in binary systems, we find that all planets in binary systems published by the KMTNet survey are located inside the resonant caustics range with $q \gtrsim 2 \times 10^{-3}$, indicating the incompleteness of the KMTNet sample for planets in binary systems. Thus, planets in binary systems cannot be included in the current study of the KMTNet mass-ratio function, and a systematic search for planetary anomalies in KMTNet microlensing light curves of binary systems is needed.

preprint2022arXiv

Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters

Encoding the scale information explicitly into the representation learned by a convolutional neural network (CNN) is beneficial for many computer vision tasks especially when dealing with multiscale inputs. We study, in this paper, a scaling-translation-equivariant (ST-equivariant) CNN with joint convolutions across the space and the scaling group, which is shown to be both sufficient and necessary to achieve equivariance for the regular representation of the scaling-translation group ST . To reduce the model complexity and computational burden, we decompose the convolutional filters under two pre-fixed separable bases and truncate the expansion to low-frequency components. A further benefit of the truncated filter expansion is the improved deformation robustness of the equivariant representation, a property which is theoretically analyzed and empirically verified. Numerical experiments demonstrate that the proposed scaling-translation-equivariant network with decomposed convolutional filters (ScDCFNet) achieves significantly improved performance in multiscale image classification and better interpretability than regular CNNs at a reduced model size.

preprint2022arXiv

Structure-preserving GANs

Generative adversarial networks (GANs), a class of distribution-learning methods based on a two-player game between a generator and a discriminator, can generally be formulated as a minmax problem based on the variational representation of a divergence between the unknown and the generated distributions. We introduce structure-preserving GANs as a data-efficient framework for learning distributions with additional structure such as group symmetry, by developing new variational representations for divergences. Our theory shows that we can reduce the discriminator space to its projection on the invariant discriminator space, using the conditional expectation with respect to the sigma-algebra associated to the underlying structure. In addition, we prove that the discriminator space reduction must be accompanied by a careful design of structured generators, as flawed designs may easily lead to a catastrophic "mode collapse" of the learned distribution. We contextualize our framework by building symmetry-preserving GANs for distributions with intrinsic group symmetry, and demonstrate that both players, namely the equivariant generator and invariant discriminator, play important but distinct roles in the learning process. Empirical experiments and ablation studies across a broad range of data sets, including real-world medical imaging, validate our theory, and show our proposed methods achieve significantly improved sample fidelity and diversity -- almost an order of magnitude measured in Fréchet Inception Distance -- especially in the small data regime.

preprint2022arXiv

Systematic KMTNet Planetary Anomaly Search, Paper I: OGLE-2019-BLG-1053Lb, A Buried Terrestrial Planet

In order to exhume the buried signatures of "missing planetary caustics" in the KMTNet data, we conducted a systematic anomaly search to the residuals from point-source point-lens fits, based on a modified version of the KMTNet EventFinder algorithm. This search reveals the lowest mass-ratio planetary caustic to date in the microlensing event OGLE-2019-BLG-1053, for which the planetary signal had not been noticed before. The planetary system has a planet-host mass ratio of $q = (1.25 \pm 0.13) \times 10^{-5}$. A Bayesian analysis yields estimates of the mass of the host star, $M_{\rm host} = 0.61_{-0.24}^{+0.29}~M_\odot$, the mass of its planet, $M_{\rm planet} = 2.48_{-0.98}^{+1.19}~M_{\oplus}$, the projected planet-host separation, $a_\perp = 3.4_{-0.5}^{+0.5}$ au, and the lens distance of $D_{\rm L} = 6.8_{-0.9}^{+0.6}$ kpc. The discovery of this very low mass-ratio planet illustrates the utility of our method and opens a new window for a large and homogeneous sample to study the microlensing planet-host mass-ratio function down to $q \sim 10^{-5}$.

preprint2022arXiv

Systematic KMTNet Planetary Anomaly Search. IV. Complete Sample of 2019 Prime-Field

We report the complete statistical planetary sample from the prime fields ($Γ\geq 2~{\rm hr}^{-1}$) of the 2019 Korea Microlensing Telescope Network (KMTNet) microlensing survey. We develop the optimized KMTNet AnomalyFinder algorithm and apply it to the 2019 KMTNet prime fields. We find a total of 14 homogeneously selected planets and report the analysis of three planetary events, KMT-2019-BLG-(1042,1552,2974). The planet-host mass ratios, $q$, for the three planetary events are $6.34 \times 10^{-4}, 4.89 \times 10^{-3}$ and $6.18 \times 10^{-4}$, respectively. A Bayesian analysis indicates the three planets are all cold giant planets beyond the snow line of their host stars. The 13 planets are basically uniform in $\log q$ over the range $-5.0 < \log q < -1.5$. This result suggests that the planets below $q_{\rm break} = 1.7 \times 10^{-4}$ proposed by the MOA-II survey may be more common than previously believed. This work is an early component of a large project to determine the KMTNet mass-ratio function, and the whole sample of 2016--2019 KMTNet events should contain about 120 planets.

preprint2022arXiv

The intrinsic multiplicity distribution of exoplanets revealed from the radial velocity method

Planet multiplicities are useful in constraining the formation and evolution of planetary systems but usually difficult to constrain observationally. Here, we develop a general method that can properly take into account the survey incompleteness and recover the intrinsic planet multiplicity distribution. We then apply it to the radial velocity (RV) planet sample from the California Legacy Survey (CLS). Within the $1\,$au ($10\,$au) region, we find $21 \pm 4\%$ ($19.2 \pm 2.8\%$) of Sun-like stars host planets with masses above $10\,M_\oplus$ ($0.3\,M_{\rm J}$), about 30\% (40\%) of which are multi-planet systems; in terms of the RV semi-amplitude $K$, $33 \pm 7\%$ ($25 \pm 3\%$) of Sun-like stars contain planets of $K>1\,$m/s ($3\,$m/s), and each system hosts on average $1.8 \pm 0.4$ ($1.63 \pm 0.16$) planets. We note that the hot Jupiter rate in the CLS Sun-like sample is higher than the consensus value of $\sim$1\% by a factor of about three. We also confirm previous studies on the correlation between inner ($<1\,$au) and outer ($>1\,$au) planets.

preprint2022arXiv

Two Candidate KH 15D-like Systems from the Zwicky Transient Facility

KH 15D contains a circumbinary disk that is tilted relative to the orbital plane of the central binary. The precession of the disk and the orbital motion of the binary together produce rich phenomena in the photometric light curve. In this work, we present the discovery and preliminary analysis of two objects that resemble the key features of KH 15D from the Zwicky Transient Facility. These new objects, Bernhard-1 and Bernhard-2, show large-amplitude ($>1.5\,$mag), long-duration (more than tens of days), and periodic dimming events. A one-sided screen model is developed to model the photometric behaviour of these objects, the physical interpretation of which is a tilted, warped circumbinary disk occulting the inner binary. Changes in the object light curves suggest potential precession periods over timescales longer than 10 years. Additional photometric and spectroscopic observations are encouraged to better understand the nature of these interesting systems.

preprint2022arXiv

Warning: The mini gamma-ray-bursts in planning hadron colliders beyond the LHC energies

Gluons may converge to a stable state at a critical momentum in nucleon. This gluon condensation will greatly increase the proton-proton cross section provided that the collision energies exceed the gluon condensation threshold. Based on the analyses of cosmic gamma-ray spectra, we find that the $p-Pb$ and $Pb-Pb$ collisions at the LHC are close to the energy region of the gluon condensation effect. We warn that for the next generation of hadron colliders increasing the collision energies, the extremely strong gamma-rays will be emitted in a narrow space of the accelerator due to the gluon condensation effect. Such artificial mini gamma-ray-bursts in the laboratory may damage the detectors.

preprint2021arXiv

Measuring microlensing parallax via simultaneous observations from Chinese Space Station Telescope and Roman Telescope

Simultaneous observations from two spatially well-separated telescopes can lead to the measurements of the microlensing parallax parameter, an important quantity toward the determinations of the lens mass. The separation between Earth and Sun-Earth L2 point, $\sim0.01$ AU, is ideal for parallax measurements of short and ultra-short ($\sim$1\,hr to 10\,days) microlensing events, which are candidates of free-floating planet (FFP) events. In this work, we study the potential of doing so in the context of two proposed space-based missions, the Chinese Space Station Telescope (CSST) in a Leo orbit and the Nancy Grace Roman Space Telescope (\emph{Roman}) at L2. We show that the joint observations of the two can directly measure the microlensing parallax of nearly all FFP events with timescales $t_{\rm E}\lesssim$ 10\,days as well as planetary (and stellar binary) events that show caustic crossing features. The potential of using CSST alone in measuring microlensing parallax is also discussed.

preprint2021arXiv

Neural Networks Enforcing Physical Symmetries in Nonlinear Dynamical Lattices: The Case Example of the Ablowitz-Ladik Model

In this work we introduce symmetry-preserving, physics-informed neural networks (S-PINNs) motivated by symmetries that are ubiquitous to solutions of nonlinear dynamical lattices. Although the use of PINNs have recently attracted much attention in data-driven discovery of solutions chiefly to partial differential equations, we demonstrate that they fail at enforcing important physical laws including symmetries of solutions and conservation laws. Through the correlation of parity symmetries in both space and time of solutions to differential equations with their group equivariant representation, we construct group-equivariant NNs which respect spatio-temporal parity symmetry. Moreover, we adapt the proposed architecture to enforce different types of periodicity (or localization) of solutions to nonlinear dynamical lattices. We do so by applying S-PINNs to the completely integrable Ablowitz-Ladik model, and performing numerical experiments with a special focus on waveforms that are related to rogue structures. These include the Kuznetsov-Ma soliton, and Akhmediev breather as well as the Peregrine soliton. Our numerical results demonstrate the superiority and robustness of the proposed architecture over standard PINNs.

preprint2021arXiv

OGLE-2019-BLG-0468Lb,c: two microlensing giant planets around a G-type star

With the aim of interpreting anomalous lensing events with no suggested models, we conducted a project of reinvestigating microlensing data in and before the 2019 season. In this work, we report a multi-planet system OGLE-2019-BLG-0468L found from the project. The light curve of the lensing event OGLE-2019-BLG-0468, which consists of three distinctive anomaly features, could not be explained by the usual binary-lens or binary-source interpretation. We find a solution explaining all anomaly features with a triple-lens interpretation, in which the lens is composed of two planets and their host, making the lens the fourth multi-planet system securely found by microlensing. The two planets have masses $\sim 3.4~M_{\rm J}$ and $\sim 10.2~M_{\rm J}$, and they are orbiting around a G-type star with a mass $\sim 0.9~M_\odot$ and a distance $\sim 4.4$ kpc. The host of the planets is most likely responsible for the light of the baseline object, although the possibility for the host to be a companion to the baseline object cannot be ruled out.

preprint2021arXiv

Systematic KMTNet Planetary Anomaly Search, Paper II: Six New $q<2\times 10^{-4}$ Mass-ratio Planets

We apply the automated AnomalyFinder algorithm of Paper I (Zang et al. 2021b) to 2018-2019 light curves from the $\simeq 13\,{\rm deg}^2$ covered by the six KMTNet prime fields, with cadences $Γ\geq 2\,{\rm hr}^{-1}$. We find a total of 11 planets with mass ratios $q<2\times 10^{-4}$, including six newly discovered planets, one planet that was reported in Paper I, and recovery of four previously discovered planets. One of the new planets, OGLE-2018-BLG-0977Lb, is in a planetary-caustic event, while the other five (OGLE-2018-BLG-0506Lb, OGLE-2018-BLG-0516Lb, OGLE-2019-BLG-1492Lb, KMT-2019-BLG-0253, and KMT-2019-BLG-0953) are revealed by a "dip" in the light curve as the source crosses the host-planet axis on the opposite side of the planet. These subtle signals were missed in previous by-eye searches. The planet-host separations (scaled to the Einstein radius), $s$, and planet-host mass ratios, $q$, are, respectively, $(s,q\times 10^5) = (0.88, 4.1)$, $(0.96\pm 0.10, 8.3)$, $(0.94\pm 0.07, 13)$, $(0.97\pm 0.07, 18)$, $(0.97\pm0.04,4.1)$, and $(0.74,18)$, where the "$\pm$" indicates a discrete degeneracy. The 11 planets are spread out over the range $-5<\log q < -3.7$. Together with the two planets previously reported with $q\sim 10^{-5}$ from the 2018-2019 non-prime KMT fields, this result suggests that planets toward the bottom of this mass-ratio range may be more common than previously believed.

preprint2021arXiv

The 'COVID' Crash of the 2020 U.S. Stock Market

We employed the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors with different levels of total market capitalizations through four major U.S. stock market indexes, including the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index, representing the stocks overall, the large capitalization stocks, the middle capitalization stocks and the small capitalization stocks, respectively. During the 2020 U.S. stock market crash, all four indexes lost more than a third of their values within five weeks, while both the middle capitalization stocks and the small capitalization stocks have suffered much greater losses than the large capitalization stocks and stocks overall. Our results indicate that the price trajectories of these four stock market indexes prior to the 2020 stock market crash have clearly featured the obvious LPPLS bubble pattern and were indeed in a positive bubble regime. Contrary to the popular belief that the COVID-19 led to the 2020 stock market crash, the 2020 U.S. stock market crash was endogenous, stemming from the increasingly systemic instability of the stock market itself. We also performed the complementary post-mortem analysis of the 2020 U.S. stock market crash. Our analyses indicate that the 2020 U.S. stock market crash originated from a bubble which began to form as early as September 2018; and the bubbles in stocks with different levels of total market capitalizations have significantly different starting time profiles. This study not only sheds new light on the making of the 2020 U.S. stock market crash but also creates a novel pipeline for future real-time crash detection and mechanism dissection of any financial market and/or economic index.

preprint2020arXiv

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization

We improve the robustness of Deep Neural Net (DNN) to adversarial attacks by using an interpolating function as the output activation. This data-dependent activation remarkably improves both the generalization and robustness of DNN. In the CIFAR10 benchmark, we raise the robust accuracy of the adversarially trained ResNet20 from $\sim 46\%$ to $\sim 69\%$ under the state-of-the-art Iterative Fast Gradient Sign Method (IFGSM) based adversarial attack. When we combine this data-dependent activation with total variation minimization on adversarial images and training data augmentation, we achieve an improvement in robust accuracy by 38.9$\%$ for ResNet56 under the strongest IFGSM attack. Furthermore, We provide an intuitive explanation of our defense by analyzing the geometry of the feature space.

preprint2020arXiv

Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification

Skin disease classification from images is crucial to dermatological diagnosis. However, identifying skin lesions involves a variety of aspects in terms of size, color, shape, and texture. To make matters worse, many categories only contain very few samples, posing great challenges to conventional machine learning algorithms and even human experts. Inspired by the recent success of Few-Shot Learning (FSL) in natural image classification, we propose to apply FSL to skin disease identification to address the extreme scarcity of training sample problem. However, directly applying FSL to this task does not work well in practice, and we find that the problem can be largely attributed to the incompatibility between Cross Entropy (CE) and episode training, which are both commonly used in FSL. Based on a detailed analysis, we propose the Query-Relative (QR) loss, which proves superior to CE under episode training and is closely related to recently proposed mutual information estimation. Moreover, we further strengthen the proposed QR loss with a novel adaptive hard margin strategy. Comprehensive experiments validate the effectiveness of the proposed FSL scheme and the possibility to diagnosis rare skin disease with a few labeled samples.

preprint2020arXiv

Anomalous bremsstrahlung and the structure of cosmic ray electron-positron fluxes at the GeV-TeV energy range

We reveal that the energy spectra of electrons-positrons in primary cosmic rays measured at atmosphere top have double structures: an excess component $Φ^s_{e^+}(E)=Φ^s_{e^-}(E)$ around $400 GeV$, which origins from a strong $e^+e^-$-source and the distorted background $Φ^0_{e^-}(E)$. We supposed that the difference between AMS-CALET and Fermi-LAT-DAMPE data origins from the energy loss of the fluxes due to the anomalous bremsstrahlung effect at a special window. The evolution of spectra under anomalous bremsstrahlung effect satisfies an improved electromagnetic cascade equation. The above spectra are parameterized and they can be regarded as the subjects exploring new physics. We suggest to check the previous applications of the Bethe-Heitler formula in the study of the propagation of high energy electrons and photons.

preprint2020arXiv

Designing Xenes with Two-Dimensional Triangular Lattice

Xenes, graphene-like two-dimensional (2D) monoelemental crystals with a honeycomb symmetry, have been the focus of numerous experimental and theoretical studies. In comparison, single-element 2D materials with a triangular lattice symmetry have not received due attention. Here, taking Pb as an example, we investigate the triangular-lattice monolayer made of group-IV atoms employing first-principles density functional theory calculations. The flat Pb monolayer supports a mirror-symmetry-protected spinless nodal line in the absence spin-orbit coupling (SOC). The introduction of an out-of-plane buckling creates a glide mirror, protecting an anisotropic Dirac nodal loop. Both flat and buckled Pb monolayers become topologically trivial after including SOC. A large buckling will make the Pb sheet a 2D semiconductor with symmetry-protected Dirac points below the Fermi level. The electronic structures of other group-IV triangular lattices such as Ge and Sn demonstrate strong similarity to Pb. We further design a quasi-3D crystal PbHfO$_2$ by alternately stacking Pb and 1T-HfO$_2$ monolayers. The new compound PbHfO$_2$ is dynamically stable and retains the properties of Pb monolayer. By applying epitaxial strains to PbHfO$_2$, it is possible to drive an insulator-to-metal transition coupled with an anti-ferroelectric-to-paraelectric phase transition. Our results suggest the potential of the 2D triangular lattice as a complimentary platform to design new type of broadly-defined Xenes.

preprint2020arXiv

Detecting isolated stellar-mass black holes in the absence of microlensing parallax effect

Gravitational microlensing can detect isolated stellar-mass black holes (BHs), which are believed to be the dominant form of Galactic BHs according to population synthesis models. Previous searches for BH events in microlensing data focused on long-timescale events with significant microlensing parallax detections. Here we show that, although BH events preferentially have long timescales, the microlensing parallax amplitudes are so small that in most cases the parallax signals cannot be detected statistically significantly. We then identify OGLE-2006-BLG-044 to be a candidate BH event because of its long timescale and small microlensing parallax. Our findings have implications to future BH searches in microlensing data.

preprint2020arXiv

Improved Bethe-Heitler formula

The Bethe-Heitler formula describes bremsstrahlung and it's a typical and important example in quantum electromagnetic dynamics (QED). This formula is widely applied in many branches of physics and astrophysics. We find that the integrated bremsstrahlung cross section at the static approximation and high energy limit has an unexpected big increment, which is missed by previous bremsstrahlung theory. This anomalous effect also exists in electron-positron pair creation. We derive the relating formulas and point out that electromagnetic cascades at the top of atmosphere can test this effect.

preprint2020arXiv

Looking for the possible gluon condensation signature in sub-TeV gamma-ray spectra: from active galactic nuclei to gamma ray bursts

The gluon condensation in the proton as a dynamical model is used to treat a series of unsolved puzzles in sub-TeV gamma ray spectra, they include the broken power-law of blazar's radiation, the hardening confusion of 1ES 1426+428, Mkn 501, and the recently recorded sub-TeV gamma spectra of GRB 180720B and GRB 190114C. We find that the above anomalous phenomena in gamma ray energy spectra can be understood with the simple broken power law based on a QCD gluon condensation effect.

preprint2020arXiv

OGLE-2017-BLG-0406: ${\it Spitzer}$ Microlens Parallax Reveals Saturn-mass Planet orbiting M-dwarf Host in the Inner Galactic Disk

We report the discovery and analysis of the planetary microlensing event OGLE-2017-BLG-0406, which was observed both from the ground and by the ${\it Spitzer}$ satellite in a solar orbit. At high magnification, the anomaly in the light curve was densely observed by ground-based-survey and follow-up groups, and it was found to be explained by a planetary lens with a planet/host mass ratio of $q=7.0 \times 10^{-4}$ from the light-curve modeling. The ground-only and ${\it Spitzer}$-"only" data each provide very strong one-dimensional (1-D) constraints on the 2-D microlens parallax vector $\bf{π_{\rm E}}$. When combined, these yield a precise measurement of $\bf{π_{\rm E}}$, and so of the masses of the host $M_{\rm host}=0.56\pm0.07\,M_\odot$ and planet $M_{\rm planet} = 0.41 \pm 0.05\,M_{\rm Jup}$. The system lies at a distance $D_{\rm L}=5.2 \pm 0.5 \ {\rm kpc}$ from the Sun toward the Galactic bulge, and the host is more likely to be a disk population star according to the kinematics of the lens. The projected separation of the planet from the host is $a_{\perp} = 3.5 \pm 0.3 \ {\rm au}$, i.e., just over twice the snow line. The Galactic-disk kinematics are established in part from a precise measurement of the source proper motion based on OGLE-IV data. By contrast, the ${\it Gaia}$ proper-motion measurement of the source suffers from a catastrophic $10\,σ$ error.

preprint2020arXiv

OGLE-2018-BLG-1269Lb: A Jovian Planet With A Bright, $I=16$ Host

We report the discovery of a planet in the microlensing event OGLE-2018-BLG-1269, with planet-host mass ratio $q \sim 6\times10^{-4}$, i.e., $0.6$ times smaller than the Jupiter/Sun mass ratio. Combined with the $Gaia$ parallax and proper motion, a strong one-dimensional constraint on the microlens parallax vector allows us to significantly reduce the uncertainties of lens physical parameters. A Bayesian analysis that ignores any information about light from the host yields that the planet is a cold giant $(M_{2} = 0.69_{-0.22}^{+0.44}\,M_{\rm J})$ orbiting a Sun-like star $(M_{1} = 1.13_{-0.35}^{+0.72}\,M_{\odot})$ at a distance of $D_{\rm L} = 2.56_{-0.62}^{+0.92}\,{\rm kpc}$. The projected planet-host separation is $a_{\perp} = 4.61_{-1.17}^{+1.70}\,{\rm au}$. Using {\it Gaia} astrometry, we show that the blended light lies $\lesssim 12\,$mas from the host and therefore must be either the host star or a stellar companion to the host. An isochrone analysis favors the former possibility at $>99.6\%$. The host is therefore a subgiant. For host metallicities in the range of $0.0 \leq {\rm [Fe/H]} \leq +0.3$, the host and planet masses are then in the range of $1.16 \leq M_{1}/M_{\odot} \leq 1.38$ and $0.74 \leq M_{2}/M_{\rm J} \leq 0.89$, respectively. Low host metallicities are excluded. The brightness and proximity of the lens make the event a strong candidate for spectroscopic followup both to test the microlensing solution and to further characterize the system.

preprint2020arXiv

On the patterns observed in Kepler multi-planet systems

Recent studies claimed that planets around the same star have similar sizes and masses and regular spacings, and that planet pairs usually show ordered sizes such that the outer planet is usually the larger one. Here I show that these patterns can be largely explained by detection biases. The \emph{Kepler} planet detections are set by the transit signal-to-noise ratio (S/N). For different stellar properties and orbital period values, the same S/N corresponds to different planetary sizes. This variation in the detection threshold naturally leads to apparent correlations in planet sizes and the observed size ordering. The apparently correlated spacings, measured in period ratios, between adjacent planet pairs in systems with at least three detected planets are partially due to the arbitrary upper limit that the earlier study imposed on the period ratio, and partially due to the varying stability threshold for different planets. After these detection biases are taken into account, we do not find strong evidence for the so-called "intra-system uniformity" or the size ordering effect. Instead, the physical properties of \emph{Kepler} planets are largely independent of the properties of their siblings and the parent star. It is likely that the dynamical evolution has erased the memory of \emph{Kepler} planets about their initial formation conditions. In other words, it will be difficult to infer the initial conditions from the observed properties and the architecture of \emph{Kepler} planets.

preprint2020arXiv

Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach

With the growth of online shopping for fashion products, accurate fashion recommendation has become a critical problem. Meanwhile, social networks provide an open and new data source for personalized fashion analysis. In this work, we study the problem of personalized fashion recommendation from social media data, i.e. recommending new outfits to social media users that fit their fashion preferences. To this end, we present an item-to-set metric learning framework that learns to compute the similarity between a set of historical fashion items of a user to a new fashion item. To extract features from multi-modal street-view fashion items, we propose an embedding module that performs multi-modality feature extraction and cross-modality gated fusion. To validate the effectiveness of our approach, we collect a real-world social media dataset. Extensive experiments on the collected dataset show the superior performance of our proposed approach.

preprint2020arXiv

Unifying Specialist Image Embedding into Universal Image Embedding

Deep image embedding provides a way to measure the semantic similarity of two images. It plays a central role in many applications such as image search, face verification, and zero-shot learning. It is desirable to have a universal deep embedding model applicable to various domains of images. However, existing methods mainly rely on training specialist embedding models each of which is applicable to images from a single domain. In this paper, we study an important but unexplored task: how to train a single universal image embedding model to match the performance of several specialists on each specialist's domain. Simply fusing the training data from multiple domains cannot solve this problem because some domains become overfitted sooner when trained together using existing methods. Therefore, we propose to distill the knowledge in multiple specialists into a universal embedding to solve this problem. In contrast to existing embedding distillation methods that distill the absolute distances between images, we transform the absolute distances between images into a probabilistic distribution and minimize the KL-divergence between the distributions of the specialists and the universal embedding. Using several public datasets, we validate that our proposed method accomplishes the goal of universal image embedding.

preprint2020arXiv

Wave effects in the microlensing of pulsars and FRBs by point masses

Wave effects are often neglected in microlensing studies; however, for coherent point-like sources, such as pulsars and fast radio bursts (FRBs), wave effects will become important in their gravitational lensing. In this paper, we describe the wave optics formalism, its various limits, and the conditions for which these limits hold. Using the simple point lens as an example, we will show that the frequency dependence of wave effects breaks degeneracies that are present in the usual geometric optics limit, and constructive interference results in larger magnifications further from the lens. This latter fact leads to a generic increase in cross section for microlensing events in the wave-optics regime compared to the geometric optics regime. For realistic percent-level spectral sensitivities, this leads to a relative boost in lensing cross section of more than an order of magnitude. We apply the point-lens model to the lensing of FRBs and pulsars and find that these radio sources will be lensed in the full wave-optics regime by isolated masses in the range of $0.1-100\,M_\oplus$, which includes free-floating planets (FFPs), whose Einstein radius is smaller than the Fresnel scale. More generally, the interference pattern allows an instantaneous determination of lens masses, unlike traditional microlensing techniques which only yield a mass inference from the event timescale.

preprint2020arXiv

Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning

This paper investigates the stochastic optimization problem with a focus on developing scalable parallel algorithms for deep learning tasks. Our solution involves a reformation of the objective function for stochastic optimization in neural network models, along with a novel parallel strategy, coined weighted aggregating stochastic gradient descent (WASGD). Following a theoretical analysis on the characteristics of the new objective function, WASGD introduces a decentralized weighted aggregating scheme based on the performance of local workers. Without any center variable, the new method automatically assesses the importance of local workers and accepts them according to their contributions. Furthermore, we have developed an enhanced version of the method, WASGD+, by (1) considering a designed sample order and (2) applying a more advanced weight evaluating function. To validate the new method, we benchmark our schemes against several popular algorithms including the state-of-the-art techniques (e.g., elastic averaging SGD) in training deep neural networks for classification tasks. Comprehensive experiments have been conducted on four classic datasets, including the CIFAR-100, CIFAR-10, Fashion-MNIST, and MNIST. The subsequent results suggest the superiority of the WASGD scheme in accelerating the training of deep architecture. Better still, the enhanced version, WASGD+, has been shown to be a significant improvement over its basic version.

preprint2019arXiv

A possible evidence of the gluon condensation effect in cosmic positron and gamma-ray spectra

The gluon condensation effect in cosmic proton-proton collisions at high energy is used to explain an excess in the positron spectrum observed by AMS. We find that this excess may originate from the GC-effect in Tycho's supernova remnant.

preprint2019arXiv

Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator

We present an advance bubble detection methodology based on the Log Periodic Power Law Singularity (LPPLS) confidence indicator for the early causal identification of positive and negative bubbles in the Chinese stock market using the daily data on the Shanghai Shenzhen CSI 300 stock market index from January 2002 through April 2018. We account for the damping condition of LPPLS model in the search space and implement the stricter filter conditions for the qualification of the valid LPPLS fits by taking account of the maximum relative error, performing the Lomb log-periodic test of the detrended residual, and unit-root tests of the logarithmic residual based on both the Phillips-Perron test and Dickey-Fuller test to improve the performance of LPPLS confidence indicator. Our analysis shows that the LPPLS detection strategy diagnoses the positive bubbles and negative bubbles corresponding to well-known historical events, implying the detection strategy based on the LPPLS confidence indicator has an outstanding performance to identify the bubbles in advance. We find that the probability density distribution of the estimated beginning time of bubbles appears to be skewed and the mass of the distribution is concentrated on the area where the price starts to have an obvious super-exponentially growth. This study is the first work in the literature that identifies the existence of bubbles in the Chinese stock market using the daily data of CSI 300 index with the advance bubble detection methodology of LPPLS confidence indicator. We have shown that it is possible to detect the potential positive and negative bubbles and crashes ahead of time, which in turn limits the bubble sizes and eventually minimizes the damages from the bubble crash.

preprint2019arXiv

KMT-2016-BLG-1836Lb: A Super-Jovian Planet From A High-Cadence Microlensing Field

We report the discovery of a super-Jovian planet in the microlensing event KMT-2016-BLG-1836, which was found by the Korea Microlensing Telescope Network's high-cadence observations (Γ~ 4~{hr}^{-1}). The planet-host mass ratio q ~ 0.004. A Bayesian analysis indicates that the planetary system is composed of a super-Jovian M_{planet} = 2.2_{-1.1}^{+1.9} M_{J} planet orbiting an M or K dwarf M_{\rm host} = 0.49_{-0.25}^{+0.38} M_{Sun}, at a distance of D_{L} = 7.1_{-2.4}^{+0.8} kpc. The projected planet-host separation is 3.5^{+1.1}_{-0.9} AU, implying that the planet is located beyond the snowline of the host star. Future high-resolution images can potentially strongly constrain the lens brightness and thus the mass and distance of the planetary system. Without considering detailed detection efficiency, selection or publication biases, we find a potential "mass ratio desert" at -3.7 \lesssim \log q \lesssim -3.0 for the 31 published KMTNet planets.

preprint2019arXiv

OGLE-2015-BLG-1771Lb: A Microlens Planet Orbiting an Ultracool Dwarf?

We report the discovery and the analysis of the short (tE < 5 days) planetary microlensing event, OGLE-2015-BLG-1771. The event was discovered by the Optical Gravitational Lensing Experiment (OGLE), and the planetary anomaly (at I ~ 19) was captured by The Korea Microlensing Telescope Network (KMTNet). The event has three surviving planetary models that explain the observed light curves, with planet-host mass ratio q \~ 5.4 * 10^{-3}, 4.5 * 10^{-3} and 4.5 * 10^{-2}, respectively. The first model is the best-fit model, while the second model is disfavored by Δχ^2 ~ 3. The last model is strongly disfavored by Δχ^2 ~ 15 but not ruled out. A Bayesian analysis using a Galactic model indicates that the first two models are probably composed of a Saturn-mass planet orbiting a late M dwarf, while the third one could consist of a super-Jovian planet and a mid-mass brown dwarf. The source-lens relative proper motion is mu_rel ~ 9 mas/yr, so the source and lens could be resolved by current adaptive-optics (AO) instruments in 2021 if the lens is luminous.

preprint2019arXiv

Real-time Prediction of Bitcoin Bubble Crashes

In the past decade, Bitcoin as an emerging asset class has gained widespread public attention because of their extraordinary returns in phases of extreme price growth and their unpredictable massive crashes. We apply the log-periodic power law singularity (LPPLS) confidence indicator as a diagnostic tool for identifying bubbles using the daily data on Bitcoin price in the past two years. We find that the LPPLS confidence indicator based on the daily Bitcoin price data fails to provide effective warnings for detecting the bubbles when the Bitcoin price suffers from a large fluctuation in a short time, especially for positive bubbles. In order to diagnose the existence of bubbles and accurately predict the bubble crashes in the cryptocurrency market, this study proposes an adaptive multilevel time series detection methodology based on the LPPLS model and finer (than daily) timescale for the Bitcoin price data. We adopt two levels of time series, 1 hour and 30 minutes, to demonstrate the adaptive multilevel time series detection methodology. The results show that the LPPLS confidence indicator based on this new method is an outstanding instrument to effectively detect the bubbles and accurately forecast the bubble crashes, even if a bubble exists in a short time. In addition, we discover that the short-term LPPLS confidence indicator highly sensitive to the extreme fluctuations of Bitcoin price can provide some useful insights into the bubble status on a shorter time scale - on a day to week scale, and the long-term LPPLS confidence indicator has a stable performance in terms of effectively monitoring the bubble status on a longer time scale - on a week to month scale. The adaptive multilevel time series detection methodology can provide real-time detection of bubbles and advanced forecast of crashes to warn of the imminent risk.

preprint2019arXiv

Spitzer + VLTI-GRAVITY Measure the Lens Mass of a Nearby Microlensing Event

We report the lens mass and distance measurements of the nearby microlensing event TCP J05074264+2447555. We measure the microlens parallax vector $π_{\rm E}$ using Spitzer and ground-based light curves with constraints on the direction of lens-source relative proper motion derived from Very Large Telescope Interferometer (VLTI) GRAVITY observations. Combining this $π_{\rm E}$ determination with the angular Einstein radius $θ_{\rm E}$ measured by VLTI GRAVITY observations, we find that the lens is a star with mass $M_{\rm L} = 0.495 \pm 0.063~M_{\odot}$ at a distance $D_{\rm L} = 429 \pm 21~{\rm pc}$. We find that the blended light basically all comes from the lens. The lens-source proper motion is $μ_{\rm rel,hel} = 26.55 \pm 0.36~{\rm mas\,yr^{-1}}$, so with currently available adaptive-optics (AO) instruments, the lens and source can be resolved in 2021. This is the first microlensing event whose lens mass is unambiguously measured by interferometry + satellite parallax observations, which opens a new window for mass measurements of isolated objects such as stellar-mass black holes.

preprint2019arXiv

Spitzer Microlensing parallax reveals two isolated stars in the Galactic bulge

We report the mass and distance measurements of two single-lens events from the 2017 Spitzer microlensing campaign. The ground-based observations yield the detection of finite-source effects, and the microlens parallaxes are derived from the joint analysis of ground-based observations and Spitzer observations. We find that the lens of OGLE-2017-BLG-1254 is a $0.60 \pm 0.03 M_{\odot}$ star with $D_{\rm LS} = 0.53 \pm 0.11~\text{kpc}$, where $D_{\rm LS}$ is the distance between the lens and the source. The second event, OGLE-2017-BLG-1161, is subject to the known satellite parallax degeneracy, and thus is either a $0.51^{+0.12}_{-0.10} M_{\odot}$ star with $D_{\rm LS} = 0.40 \pm 0.12~\text{kpc}$ or a $0.38^{+0.13}_{-0.12} M_{\odot}$ star with $D_{\rm LS} = 0.53 \pm 0.19~\text{kpc}$. Both of the lenses are therefore isolated stars in the Galactic bulge. By comparing the mass and distance distributions of the eight published Spitzer finite-source events with the expectations from a Galactic model, we find that the Spitzer sample is in agreement with the probability of finite-source effects occurrence in single lens events.

preprint2018arXiv

Electronic nature of coverage-dependent nanosurface effect by cooperative orbital redistribution

Nanomaterial surface states can effectively modify or even dominate their physical and chemical properties due to large surface-to-volume ratios. Such surface effects are highly dependent on particle size and ligand coverage, yet the underlying electronic-level mechanism still remains unknown. Using TiO2 nanosheet as a model system, we reveal the electronic nature of coverage-dependent nanosurface effects through varying ligand coverage and probing the modified surface bonding and electronic band structures with near-edge X-ray absorption fine structure. We discover experimentally that surface ligands can competitively polarize the 3d orbitals of surface Ti atoms into chemisorption states, which is cooperative with increased ligand coverages. Such coverage-dependent cooperative orbital redistribution accounts for various nanosurface effects on regulating the electronic structure, surface reactivity, optical property, and chemisorption of nanomaterials.

preprint2017arXiv

Multi-appearance Segmentation and Extended 0-1 Program for Dense Small Object Tracking

Aiming to address the fast multi-object tracking for dense small object in the cluster background, we review track orientated multi-hypothesis tracking(TOMHT) with consideration of batch optimization. Employing autocorrelation based motion score test and staged hypotheses merging approach, we build our homologous hypothesis generation and management method. A new one-to-many constraint is proposed and applied to tackle the track exclusions during complex occlusions. Besides, to achieve better results, we develop a multi-appearance segmentation for detection, which exploits tree-like topological information and realizes one threshold for one object. Experimental results verify the strength of our methods, indicating speed and performance advantages of our tracker.

preprint2016arXiv

A new perspective on gluon distribution at small x

The corrections of the gluon fusion to the BFKL equation in a unified partonic framework are studied. This modified BFKL equation predicts a stronger shadowing, which suppresses the gluon density and even leads to the gluon disappearance below the saturation region. We suggest that this unexpected effect is caused by a possible chaotic solution of the new equation.

preprint2016arXiv

Dependence of Small Planet Frequency on Stellar Metallicity Hidden by Their Prevalence

The dependence of gas giant planet occurrence rate on stellar metallicity has been firmly established. We extend this so-called planet-metallicity correlation to broader ranges of metallicities and planet masses/radii. In particular, we assume that the planet-metallicity correlation is a power law below some critical saturation threshold, and that the probability of hosting at least one planet is unity for stars with metallicity above the threshold. We then are able to explain the discrepancy between the tentative detection and null detection in previous studies regarding the planet-metallicity correlation for small planets. In particular, we find that the null detection of this correlation can be attributed to the combination of high planet occurrence rate and low detection efficiency. Therefore, a planet-metallicity correlation for small planets cannot be ruled out. We propose that stars with metallicities lower than the Solar value are better targets for testing the planet-metallicity correlation for small planets.

preprint2016arXiv

Emergent quasi-one-dimensionality in a kagomé magnet: A simple route to complexity

We study the ground state phase diagram of the quantum spin-$1/2$ Heisenberg model on the kagomé lattice with first- ($J_1 < 0$), second- ($J_2 < 0$), and third-neighbor interactions ($J_d > 0$) by means of analytical low-energy field theory and numerical density-matrix renormalization group (DMRG) studies. The results offer a consistent picture of the $J_d$-dominant regime in terms of three sets of spin chains weakly coupled by the ferromagnetic inter-chain interactions $J_{1,2}$. When either $J_1$ or $J_2$ is dominant, the model is found to support one of two cuboctohedral phases, cuboc1 and cuboc2. These cuboc states host non-coplanar long-ranged magnetic order and possess finite scalar spin chirality. However, in the compensated regime $J_1 \simeq J_2$, a valence bond crystal phase emerges between the two cuboc phases. We find excellent agreement between an analytical theory based on coupled spin chains and unbiased DMRG calculations, including at a very detailed level of comparison of the structure of the valence bond crystal state. To our knowledge, this is the first such comprehensive understanding of a highly frustrated two-dimensional (2d) quantum antiferromagnet. We find no evidence of either the one-dimensional (1d) gapless spin liquid or the chiral spin liquids, which were previously suggested by parton mean field theories.

preprint2016arXiv

Free-floating planets from core accretion theory: microlensing predictions

We calculate the microlensing event rate and typical time-scales for the free-floating planet (FFP) population that is predicted by the core accretion theory of planet formation. The event rate is found to be ~$1.8\times 10^{-3}$ of that for the stellar population. While the stellar microlensing event time-scale peaks at around 20 days, the median time-scale for FFP events (~0.1 day) is much shorter. Our values for the event rate and the median time-scale are significantly smaller than those required to explain the \cite{Sum+11} result, by factors of ~13 and ~16, respectively. The inclusion of planets at wide separations does not change the results significantly. This discrepancy may be too significant for standard versions of both the core accretion theory and the gravitational instability model to explain satisfactorily. Therefore, either a modification to the planet formation theory is required, or other explanations to the excess of short-time-scale microlensing events are needed. Our predictions can be tested by ongoing microlensing experiment such as KMTNet, and by future satellite missions such as WFIRST and Euclid.

preprint2016arXiv

Mass Measurements of Isolated Objects from Space-based Microlensing

We report on the mass and distance measurements of two single-lens events from the 2015 \emph{Spitzer} microlensing campaign. With both finite-source effect and microlens parallax measurements, we find that the lens of OGLE-2015-BLG-1268 is very likely a brown dwarf. Assuming that the source star lies behind the same amount of dust as the Bulge red clump, we find the lens is a $45\pm7$ $M_{\rm J}$ brown dwarf at $5.9\pm1.0$ kpc. The lens of of the second event, OGLE-2015-BLG-0763, is a $0.50\pm0.04$ $M_\odot$ star at $6.9\pm1.0$ kpc. We show that the probability to definitively measure the mass of isolated microlenses is dramatically increased once simultaneous ground- and space-based observations are conducted.

preprint2016arXiv

OGLE-2015-BLG-0479LA,B: Binary Gravitational Microlens Characterized by Simultaneous Ground-based and Space-based Observation

We present a combined analysis of the observations of the gravitational microlensing event OGLE-2015-BLG-0479 taken both from the ground and by the {\it Spitzer Space Telescope}. The light curves seen from the ground and from space exhibit a time offset of $\sim 13$ days between the caustic spikes, indicating that the relative lens-source positions seen from the two places are displaced by parallax effects. From modeling the light curves, we measure the space-based microlens parallax. Combined with the angular Einstein radius measured by analyzing the caustic crossings, we determine the mass and distance of the lens. We find that the lens is a binary composed of two G-type stars with masses $\sim 1.0\ M_\odot$ and $\sim 0.9\ M_\odot$ located at a distance $\sim 3$ kpc. In addition, we are able to constrain the complete orbital parameters of the lens thanks to the precise measurement of the microlens parallax derived from the joint analysis. In contrast to the binary event OGLE-2014-BLG-1050, which was also observed by {\it Spitzer}, we find that the interpretation of OGLE-2015-BLG-0479 does not suffer from the degeneracy between $(\pm,\pm)$ and $(\pm,\mp)$ solutions, confirming that the four-fold parallax degeneracy in single-lens events collapses into the two-fold degeneracy for the general case of binary-lens events. The location of the blend in the color-magnitude diagram is consistent with the lens properties, suggesting that the blend is the lens itself. The blend is bright enough for spectroscopy and thus this possibility can be checked from future follow-up observations.

preprint2016arXiv

Partonic structure of proton in the resonance region

We separate the contributions of parton distributions from higher twist corrections to the deeply inelastic lepton-proton scattering in the resonance region using the Jefferson Lab data at low $Q^2$. The study indicates that the concept of the valence quarks and their distributions are indispensable even at $Q^2<1GeV^2$. The quark-hadron duality is also discussed.

preprint2016arXiv

The chaotic effects in a nonlinear QCD evolution equation

The corrections of gluon fusion to the DGLAP and BFKL equations are discussed in a united partonic framework. The resulting nonlinear evolution equations are the well-known GLR-MQ-ZRS equation and a new evolution equation. Using the available saturation models as input, we find that the new evolution equation has the chaos solution with positive Lyaponov exponents in the perturbative range. We predict a new kind of shadowing caused by chaos, which blocks the QCD evolution in a critical small $x$ range. The blocking effect in the evolution equation may explain the Abelian gluon assumption and even influence our expectations to the projected Large Hadron Electron Collider (LHeC), Very Large Hadron Collider (VLHC) and the upgrade (CppC) in a circular $e^+e^-$ collider (SppC).

preprint2015arXiv

A determination of the flavor asymmetric sea quarks in the proton

Using DGLAP evolution equation with the corrections of parton recombinations, the flavor asymmetric sea quark distributions in the proton are first extracted from the available experimental data with the global QCD analysis method. Comparisons of our predictions to the CTEQ, MRS, and GRV parton distribution functions for sea quarks are presented. Based on the separation of the flavor symmetric and asymmetric sea, the possible relations between strange quark distribution and symmetric light quark distribution are discussed. The results are used to explain the recent HERMES result of the strange quark distribution.

preprint2015arXiv

A Triangular Decomposition Algorithm for Differential Polynomial Systems with Elementary Computation Complexity

In this paper, a new triangular decomposition algorithm is proposed for ordinary differential polynomial systems, which has triple exponential computational complexity. The key idea is to eliminate one algebraic variable from a set of polynomials in one step using the theory of multivariate resultant. This seems to be the first differential triangular decomposition algorithm with elementary computation complexity.

preprint2015arXiv

Coherence times of precisely depth controlled NV centers in diamond

We investigated the depth dependence of coherence times of nitrogen-vacancy (NV) centers through precisely depth controlling by a moderately oxidative at 580°C in air. By successive nanoscale etching, NV centers could be brought close to the diamond surface step by step, which enable us to trace the evolution of the number of NV centers remained in the chip and to study the depth dependence of coherence times of NV centers with the diamond etching. Our results showed that the coherence times of NV centers declined rapidly with the depth reduction in their last about 22 nm before they finally disappeared, revealing a critical depth for the influence of rapid fluctuating surface spin bath. By monitoring the coherence time variation with depth, we could make a shallow NV center with long coherence time for detecting external spins with high sensitivity.

preprint2015arXiv

Competing Spin Liquid States in the Spin-$1/2$ Heisenberg Model On Triangular Lattice

We study the spin-$1/2$ Heisenberg model on the triangular lattice with the antiferromagnetic first ($J_1$) and second ($J_2$) nearest-neighbor interactions using density matrix renormalization group. By studying the spin correlation function, we find a $120^{\circ}$ magnetic order phase for $J_2 \lesssim 0.07 J_1$ and a stripe antiferromagnetic phase for $J_2 \gtrsim 0.15 J_1$. Between these two phases, we identify a spin liquid region characterized by the exponential decaying spin and dimer correlations, as well as the large spin singlet and triplet excitation gaps on finite-size systems. We find two near degenerating ground states with distinct properties in two sectors, which indicates more than one spin liquid candidates in this region. While the sector with spinon is found to respect the time reversal symmetry, the even sector without a spinon breaks such a symmetry for finite-size systems. Furthermore, we detect the signature of the fractionalization by following the evolution of different ground states with inserting spin flux into the cylinder system. Moreover, by tuning the anisotropic bond coupling, we explore the nature of the spin liquid phase and find the optimal parameter region for the gapped $Z_2$ spin liquid.

preprint2015arXiv

Criteria for Sample Selection to Maximize Planet Sensitivity and Yield from Space-Based Microlens Parallax Surveys

Space-based microlens parallax measurements are a powerful tool for understanding planet populations, especially their distribution throughout the Galaxy. However, if space-based observations of the microlensing events must be specifically targeted, it is crucial that microlensing events enter the parallax sample without reference to the known presence or absence of planets. Hence, it is vital to define objective criteria for selecting events where possible and to carefully consider and minimize the selection biases where not possible so that the final sample represents a controlled experiment. We present objective criteria for initiating observations and determining their cadence for a subset of events, and we define procedures for isolating subjective decision making from information about detected planets for the remainder of events. We also define procedures to resolve conflicts between subjective and objective selections. These procedures maximize planet sensitivity of the sample as a whole by allowing for planet detections even if they occur before satellite observations for objectively-selected events and by helping to trigger fruitful follow-up observations for subjectively-chosen events. This paper represents our public commitment to these procedures, which is a necessary component of enforcing objectivity on the experimental protocol.

preprint2015arXiv

Evidence of Different Formation Mechanisms for Hot versus Warm Super-Earths

Using the Kepler planet sample from Buchhave et al. and the statistical method clarified by Schlaufman, I show that the shorter-period super-Earths have a different dependence on the host star metallicity from the longer-period super-Earths, with the transition period being in the period range from 70 to 100 days. The hosts of shorter-period super-Earths are on average more metal-rich than those of longer-period super-Earths. The existence of such a transition period cannot be explained by any single theory of super-Earth formation, suggesting that super-Earths have formed via at least two mechanisms.

preprint2015arXiv

Galton's Family Heights Data Revisited

Galton's family heights data has been a preeminent historical dataset in regression analysis, on which the original model and basic results have survived the close scrutiny of statisticians for 125 years. However by revisiting Galton's family data, we challenge whether Galton's classic model and his regression towards mean interpretation are proper. Using Galton's data as a benchmark for different regression methods, such as least squares, orthogonal regression, geometric mean regression, and least sine squares regression - a newly developed nonparametric robust regression approach, we elucidate that his regression model has fundamental drawbacks not only in variable and model selection by "transmuting" women into men thus the simple linear model, but also a strong bias in least squares regression leading to otherwise alternative conclusions on the true relationships between the heights of the child and his or her parents.

preprint2015arXiv

Nucleon spin structure

This paper contains three parts relating to the nucleon spin structure in a simple picture of the nucleon: (i) The polarized gluon distribution in the proton is dynamically predicted starting from a low scale by using a nonlinear QCD evolution equation-the DGLAP equation with the parton recombination corrections, where the nucleon is almost only consisted of valence quarks. We find that the contribution of the gluon polarization to the nucleon spin structure is much larger than the predictions of most other theories. This result suggests a significant orbital angular momentum of the gluons is required to balance the gluon spin momentum; (ii) The spin structure function $g_1^p$ of the proton is studied, where the perturbative evolution of parton distributions and nonperturbative Vector Meson Dominance (VMD) model are used. We predict $g_1^p$ asymptotic behavior at small $x$ from lower $Q^2$ to higher $Q^2$. The results are compatible with the data including the HERA early estimations and COMPASS new results; (iii) The generalized Gerasimov-Drell-Hearn (GDH) sum rule is understood based on the polarized parton distributions of the proton with the higher twist contributions. A simple parameterized formula is proposed to clearly present the contributions of different components in the proton to $Γ_1^p(Q^2)$. The results suggest a possible extended objects with size $0.2-0.3~ fm$ inside the proton.

preprint2015arXiv

Nucleon spin structure II: Spin structure function $g_1^p$ at small $x$

The spin structure function $g_1^p$ of the proton is studied in a two component framework, where the perturbative evolution of parton distributions and nonperturbative vector meson dominance model are used. We predict the $g_1^p$ asymmetric behavior at small $x$ from lower $Q^2$ to higher $Q^2$. We find that the contribution of the large gluon helicity dominates $g_1^p$ at $x>10^{-3}$ but mixed with nonperturbative component which complicates the asymptomatic behavior of $g_1^p$ at $x<10^{-3}$. The results are compatible with the data including the HERA early estimations and COMPASS new results. The predicted strong $Q^2$- and $x$-dependence of $g_1^p$ at $0.01<Q^2<3 GeV^2$ and $x<0.1$ can be checked on the next Electron-Ion Collider.

preprint2015arXiv

Nucleon spin structure III: Origins of the generalized Gerasimov-Drell-Hearn sum rule

The generalized Gerasimov-Drell-Hearn (GDH) sum rule is understood based on the polarized parton distributions of the proton with the higher twist contributions. A simple parameterized formula is proposed to clearly present the contributions of different components in proton to $Γ_1^p(Q^2)$. We find that the contribution of quark helicity to $Γ_1^p(Q^2)$ is almost constant ($\sim 0.123$); the twist-4 effect dominates the suppression of $Γ_1^p(Q^2)$ at $Q^2<3GeV^2$, while the twist-6 effect arises a dramatic change of $Γ_1^p(Q^2)$ at $Q^2<0.3 GeV^2$, it implies a possible extended objects with size $0.2-0.3~ fm$ inside the proton.

preprint2015arXiv

Planet Sensitivity from Combined Ground- and Space-based Microlensing Observations

To move one step forward toward a Galactic distribution of planets, we present the first planet sensitivity analysis for microlensing events with simultaneous observations from space and the ground. We present this analysis for two such events, OGLE-2014-BLG-0939 and OGLE-2014-BLG-0124, which both show substantial planet sensitivity even though neither of them reached high magnification. This suggests that an ensemble of low to moderate magnification events can also yield significant planet sensitivity and therefore probability to detect planets. The implications of our results to the ongoing and future space-based microlensing experiments to measure the Galactic distribution of planets are discussed.

preprint2015arXiv

Quantum phase diagram of the spin-$1$ $J_1-J_2$ Heisenberg model on the honeycomb lattice

Strongly correlated systems with geometric frustrations can host the emergent phases of matter with unconventional properties. Here, we study the spin $S = 1$ Heisenberg model on the honeycomb lattice with the antiferromagnetic first- ($J_1$) and second-neighbor ($J_2$) interactions ($0.0 \leq J_2/J_1 \leq 0.5$) by means of density matrix renormalization group (DMRG). In the parameter regime $J_2/J_1 \lesssim 0.27$, the system sustains a Néel antiferromagnetic phase. At the large $J_2$ side $J_2/J_1 \gtrsim 0.32$, a stripe antiferromagnetic phase is found. Between the two magnetic ordered phases $0.27 \lesssim J_2/J_1 \lesssim 0.32$, we find a \textit{non-magnetic} intermediate region with a plaquette valence-bond order. Although our calculations are limited within $6$ unit-cell width on cylinder, we present evidence that this plaquette state could be a strong candidate for this non-magnetic region in the thermodynamic limit. We also briefly discuss the nature of the quantum phase transitions in the system. We gain further insight of the non-magnetic phases in the spin-$1$ system by comparing its phase diagram with the spin-$1/2$ system.

preprint2015arXiv

RCR: Robust Compound Regression for Robust Estimation of Errors-in-Variables Model

The errors-in-variables (EIV) regression model, being more realistic by accounting for measurement errors in both the dependent and the independent variables, is widely adopted in applied sciences. The traditional EIV model estimators, however, can be highly biased by outliers and other departures from the underlying assumptions. In this paper, we develop a novel nonparametric regression approach - the robust compound regression (RCR) analysis method for the robust estimation of EIV models. We first introduce a robust and efficient estimator called least sine squares (LSS). Taking full advantage of both the new LSS method and the compound regression analysis method developed in our own group, we subsequently propose the RCR approach as a generalization of those two, which provides a robust counterpart of the entire class of the maximum likelihood estimation (MLE) solutions of the EIV model, in a 1-1 mapping. Technically, our approach gives users the flexibility to select from a class of RCR estimates the optimal one with a predefined regression efficiency criterion satisfied. Simulation studies and real-life examples are provided to illustrate the effectiveness of the RCR approach.

preprint2015arXiv

Spitzer as Microlens Parallax Satellite: Mass and Distance Measurements of Binary Lens System OGLE-2014-BLG-1050L

We report the first mass and distance measurement of a caustic-crossing binary system OGLE-2014-BLG-1050L using the space-based microlens parallax method. \emph{Spitzer} captured the second caustic-crossing of the event, which occurred $\sim$10 days before that seen from Earth. Due to the coincidence that the source-lens relative motion was almost parallel to the direction of the binary-lens axis, the four-fold degeneracy, which was known before only to occur in single-lens events, persists in this case, leading to either a lower-mass (0.2 $M_\odot$ and 0.07 $M_\odot$) binary at $\sim$1.1 kpc or a higher-mass (0.9 $M_\odot$ and 0.35 $M_\odot$) binary at $\sim$3.5 kpc. However, the latter solution is strongly preferred for reasons including blending and lensing probability. OGLE-2014-BLG-1050L demonstrates the power of microlens parallax in probing stellar and substellar binaries.

preprint2015arXiv

Sudden transition from naked atom decay to dressed atom decay

The studies on quantum open system play key roles not only in fundamental problems in quantum mechanics but also in quantum computing and information processes. Here we propose a scheme to use a one dimensional coupling cavity array (CCA) as an artificial electromagnetic environment of a two-level atom. For a finite length of CCA, we find that after a turning time the population of excited state deviates suddenly from the exponential decay. We show that physically this phenomena corresponds to a transition from a naked atom decay to a dressed state decay. We hope that our finding will promote the studies on quantum system with a finite size environment.

preprint2015arXiv

Variational Monte Carlo study of chiral spin liquid in the extended Heisenberg model on the Kagome lattice

We investigate the extended Heisenberg model on the Kagome lattice by using Gutzwiller projected fermionic states and the variational Monte Carlo technique. In particular, when both second- and third-neighbor super-exchanges are considered, we find that a gapped spin liquid described by non-trivial magnetic fluxes and long-range chiral-chiral correlations is energetically favored compared to the gapless U(1) Dirac state. Furthermore, the topological Chern number, obtained by integrating the Berry curvature, and the degeneracy of the ground state, by constructing linearly independent states, lead us to identify this flux state as the chiral spin liquid with $C=1/2$ fractionalized Chern number.

preprint2014arXiv

Applications of a nonlinear evolution equation I: the parton distributions in the proton

The parton distributions in the proton are evaluated dynamically using a nonlinear QCD evolution equation - the DGLAP equation with twist-4 (the GLR-MQ-ZSR) corrections - starting from a low scale $μ^2$, where the nucleon consists of valence quarks. We find that the negative nonlinear corrections can improve the perturbative stability of the QCD evolution equation at low $Q^2$. Our resulting parton distributions of the proton with four free parameters are compatible with the existing databases. We show that the sea quark distributions exhibit a positive and flattish behavior at small $x$ and low $Q^2$. This approach provides a powerful tool to connect the quark models of the hadron and various non-perturbative effects on them at scale $μ^2$ with the measured structure functions at high scale $Q^2>> μ^2$.

preprint2014arXiv

Applications of a nonlinear evolution equation II: the EMC effect

The EMC effect is studied by using the GLR-MQ-ZSR equation with minimum number of free parameters, where the nuclear shadowing effect is a dynamical evolution result of the equation, and nucleon swelling and Fermi motion in the nuclear environment deform the input parton distributions. Parton distributions of both proton and nucleus are predicted in a unified framework. We show that the parton recombination as a higher twist correction plays an essential role in the evolution of parton distributions either of proton or nucleus. We find that the nuclear antishadowing contributes a part of enhancement of the ratio of the structure functions around $x\sim 0.1$, while the other part origins from the deformation of the nuclear valence quark distributions. We point out that the nuclear shadowing and antishadowing effects in the gluon distribution are not stronger than that in the quark distributions.

preprint2014arXiv

Constraining the Oblateness of Kepler Planets

We use Kepler short cadence light curves to constrain the oblateness of planet candidates in the Kepler sample. The transits of rapidly rotating planets that are deformed in shape will lead to distortions in the ingress and egress of their light curves. We report the first tentative detection of an oblate planet outside of the solar system, measuring an oblateness of $0.22 \pm 0.11$ for the 18 $M_J$ mass brown dwarf Kepler 39b (KOI-423.01). We also provide constraints on the oblateness of the planets (candidates) HAT-P-7b, KOI-686.01, and KOI-197.01 to be < 0.067, < 0.251, and < 0.186, respectively. Using the Q'-values from Jupiter and Saturn, we expect tidal synchronization for the spins of HAT-P-7b, KOI-686.01 and KOI-197.01, and for their rotational oblateness signatures to be undetectable in the current data. The potentially large oblateness of KOI-423.01 (Kepler 39b) suggests that the Q'-value of the brown dwarf needs to be two orders of magnitude larger than that of the solar system gas giants to avoid being tidally spun-down.

preprint2014arXiv

Detection of Interlayer Interaction in Few-layer Graphene through Landau Level Spectroscopy

We demonstrate that surface relaxation, which is insignificant in trilayer graphene, starts to manifest in Bernal-stacked tetralayer graphene. Bernal-stacked few-layer graphene has been investigated by analyzing its Landau level spectra through quantum capacitance measurements. We find that in trilayer graphene, the interlayer interaction parameters were similar to that of graphite. However, in tetralayer graphene, the hopping parameters between the bulk and surface bilayers are quite different. This shows a direct evidence for the surface relaxation phenomena. In spite of the fact that the Van der Waals interaction between the carbon layers is thought to be insignificant, we suggest that the interlayer interaction is an important factor in explaining the observed results and the symmetry-breaking effects in graphene sublattice are not negligible.

preprint2014arXiv

Emergent Chiral Spin Liquid: Fractional Quantum Hall Effect in a Kagome Heisenberg Model

The fractional quantum Hall effect (FQHE) realized in two-dimensional electron systems under a magnetic field is one of the most remarkable discoveries in condensed matter physics. Interestingly, it has been proposed that FQHE can also emerge in time-reversal invariant spin systems, known as the chiral spin liquid (CSL) characterized by the topological order and the emerging of the fractionalized quasiparticles. A CSL can naturally lead to the exotic superconductivity originating from the condense of anyonic quasiparticles. Although CSL was highly sought after for more than twenty years, it had never been found in a spin isotropic Heisenberg model or related materials. By developing a density-matrix renormalization group based method for adiabatically inserting flux, we discover a FQHE in a spin-$\frac{1}{2}$ isotropic kagome Heisenberg model. We identify this FQHE state as the long-sought CSL with a uniform chiral order spontaneously breaking time reversal symmetry, which is uniquely characterized by the half-integer quantized topological Chern number protected by a robust excitation gap. The CSL is found to be at the neighbor of the previously identified $Z_2$ spin liquid, which may lead to an exotic quantum phase transition between two gapped topological spin liquids.

preprint2014arXiv

Empirical Study of Simulated Two-planet Microlensing Event

We undertake the first study of two-planet microlensing models recovered from simulations of microlensing events generated by realistic multi-planet systems in which 292 planetary events including 16 two-planet events were detected from 6690 simulated light curves. We find that when two planets are recovered, their parameters are usually close to those of the two planets in the system most responsible for the perturbations. However, in one of the 16 examples, the apparent mass of both detected planets was more than doubled by the unmodeled influence of a third, massive planet. This fraction is larger than, but statistically consistent with, the roughly 1.5% rate of serious mass errors due to unmodeled planetary companions for the 274 cases from the same simulation in which a single planet is recovered. We conjecture that an analogous effect due to unmodeled stellar companions may occur more frequently. For seven out of 23 cases in which two planets in the system would have been detected separately, only one planet was recovered because the perturbations due to the two planets had similar forms. This is a small fraction (7/274) of all recovered single-planet models, but almost a third of all events that might plausibly have led to two-planet models. Still, in these cases, the recovered planet tends to have parameters similar to one of the two real planets most responsible for the anomaly.

preprint2014arXiv

Global Phase Diagram of Competing Ordered and Quantum Spin Liquid Phases on the Kagomé Lattice

We study the quantum phase diagram of the spin-$1/2$ Heisenberg model on the kagomé lattice with first-, second-, and third-neighbor interactions $J_1$, $J_2$, and $J_3$ by means of density matrix renormalization group. For small $J_2$ and $J_3$, this model sustains a time-reversal invariant quantum spin liquid phase. With increasing $J_2$ and $J_3$, we find in addition a $q=(0,0)$ Néel phase, a chiral spin liquid phase, a valence-bond crystal phase, and a complex non-coplanar magnetically ordered state with spins forming the vertices of a cuboctahedron known as a cuboc1 phase. Both the chiral spin liquid and cuboc1 phase break time reversal symmetry in the sense of spontaneous scalar spin chirality. We show that the chiralities in the chiral spin liquid and cuboc1 are distinct, and that these two states are separated by a strong first order phase transition. The transitions from the chiral spin liquid to both the $q=(0,0)$ phase and to time-reversal symmetric spin liquid, however, are consistent with continuous quantum phase transitions.

preprint2014arXiv

High-Sensitivity Temperature Sensing Using an Implanted Single Nitrogen-Vacancy Center Array in Diamond

We presented a high-sensitivity temperature detection using an implanted single Nitrogen-Vacancy center array in diamond. The high-order Thermal Carr-Purcell-Meiboom-Gill (TCPMG) method was performed on the implanted single nitrogen vacancy (NV) center in diamond in a static magnetic field. We demonstrated that under small detunings for the two driving microwave frequencies, the oscillation frequency of the induced fluorescence of the NV center equals approximately to the average of the detunings of the two driving fields. On basis of the conclusion, the zero-field splitting D for the NV center and the corresponding temperature could be determined. The experiment showed that the coherence time for the high-order TCPMG was effectively extended, particularly up to 108 μs for TCPMG-8, about 14 times of the value 7.7 μs for thermal Ramsey method. This coherence time corresponded to a thermal sensitivity of 10.1 mK/Hz1/2. We also detected the temperature distribution on the surface of a diamond chip in three different circumstances by using the implanted NV center array with the TCPMG-3 method. The experiment implies the feasibility for using implanted NV centers in high-quality diamonds to detect temperatures in biology, chemistry, material science and microelectronic system with high-sensitivity and nanoscale resolution.

preprint2014arXiv

Multi-mode effects in cavity QED based on a one-dimensional cavity array

We present a microscopic mo del of cavity quantum electro dynamics based on a one-dimensional coupled cavity array (1D CCA), where a sup er cavity (SC) is comp osed by a segment of the 1D CCA with relatively smaller couplings with the outsides. The single-photon scattering problem for the SC empty or with a two-level atom is investigated. We obtain the exact theoretical result on the transmission rate for our system, which predicts the transmission p eaks shall app ear near the eigen-energies. Our numerical results further prove that the SC is a well-defined multi-mo de cavity. When a two-level atom resonant with the SC lo cates at the antino de of the resonant mo de, the transmission sp ectrum shows a clear sign of vacuum Rabi splitting as exp ected. However, when the atom lo cates at the no de of the resonant mo de, we observe a deep valley in the transmission p eak, which can b e explained by the destructive interference of two transmission channels, one is the resonant mo de, while the other is arising from the atom coupling with the non-resonance mo des. The effect of non-resonance mo des on vacuum Rabi splitting is also analyzed.

preprint2014arXiv

Parton recombination effect in polarized parton distributions

Parton recombination corrections to the standard spin-dependent Altarelli-Parisi evolution equation are considered in a nonlinear evolution equation. The properties of this recombination equation and its relation with the spin-averaged form are discussed.

preprint2014arXiv

Plaquette Ordered Phase and Quantum Phase Diagram in the Spin-1/2 J1-J2 Square Heisenberg Model

We study the spin-1/2 Heisenberg model on the square lattice with first- and second-neighbor antiferromagnetic interactions J1 and J2, which possesses a nonmagnetic region that has been debated for many years and might realize the interesting Z2 spin liquid. We use the density matrix renormalization group approach with explicit implementation of SU(2) spin rotation symmetry and study the model accurately on open cylinders with different boundary conditions. With increasing J2, we find a Neel phase, a plaquette valence-bond (PVB) phase with a finite spin gap, and a possible spin liquid in a small region of J2 between these two phases. From the finite-size scaling of the magnetic order parameter, we estimate that the Neel order vanishes at J2/J1~0.44. For 0.5<J2/J1<0.61, we find dimer correlations and PVB textures whose decay lengths grow strongly with increasing system width, consistent with a long-range PVB order in the two-dimensional limit. The dimer-dimer correlations reveal the s-wave character of the PVB order. For 0.44<J2/J1<0.5, spin order, dimer order, and spin gap are small on finite-size systems and appear to scale to zero with increasing system width, which is consistent with a possible gapless SL or a near-critical behavior. We compare and contrast our results with earlier numerical studies.

preprint2014arXiv

Predictions for Microlensing Planetary Events from Core Accretion Theory

We conduct the first microlensing simulation in the context of planet formation model. The planet population is taken from the Ida & Lin core accretion model for $0.3M_\odot$ stars. With $6690$ microlensing events, we find for a simplified Korea Microlensing Telescopes Network (KMTNet) the fraction of planetary events is $2.9\%$ , out of which $5.5\%$ show multiple-planet signatures. The number of super-Earths, super-Neptunes and super-Jupiters detected are expected to be almost equal. Our simulation shows that high-magnification events and massive planets are favored by planet detections, which is consistent with previous expectation. However, we notice that extremely high-magnification events are less sensitive to planets, which is possibly because the 10 min sampling of KMTNet is not intensive enough to capture the subtle anomalies that occur near the peak. This suggests that while KMTNet observations can be systematically analyzed without reference to any follow-up data, follow-up observations will be essential in extracting the full science potential of very high-magnification events. The uniformly high-cadence observations expected for KMTNet also result in $\sim 55\%$ of all detected planets being non-caustic-crossing, and more low-mass planets even down to Mars-mass being detected via planetary caustics. We also find that the distributions of orbital inclinations and planet mass ratios in multiple-planet events agree with the intrinsic distributions.

preprint2013arXiv

A new modified Altarelli-Parisi evolution equation with parton recombination in proton

The coefficients of the nonlinear terms in a modified Altarelli-Parisi evolution equation with parton recombination are determined in the leading logarithmic ($Q^2$) approximation. The results are valid in the whole $x$ region and contain the translation $GG\to q\bar q$, which is inhibited in the double leading logarithmic approximation. The comparisons of the new evolution equation with the Gribov-Levin-Ryskin equation are presented.

preprint2013arXiv

From EMC- and Cronin-effects to signals of quark-gluon plasma

The EMC- and Cronin-effects are explained by a unitarized evolution equation, where the shadowing and antishadowing corrections are dynamically produced by gluon fusions. For this sake, an alternative form of the GLR-MQ-ZRS equation is derived. The resulting integrated and unintegrated gluon distributions in proton and nuclei are used to analyze the contributions of the initial parton distributions to the nuclear suppression factor in heavy ion collisions. A simulation of the fractional energy loss is extracted from the RHIC and LHC data, where the contributions of the nuclear shadowing and antishadowing effects are considered. We find a rapid crossover from week energy loss to strong energy loss at a universal critical energy of gluon jet $E_c\sim 10 GeV$.

preprint2013arXiv

Properties of the gluon recombination functions

The gluon recombination functions in the twist-4 QCD evolution equations are studied at the leading logarithmic approximation using both the covariant and non-covariant methods. We justify that the infrared singularities in the twist-4 coefficient functions impede us to simply separate the QCD evolution kernels from the coefficient functions at the equivalent particle approximation. In particulary, we point out that the gluon recombination functions in the GLR-MQ evolution equation are unavailable. The methods avoiding the IR divergences are discussed, which can be used in the derivations of the evolution kernels and coefficient functions at the higher twist level.

preprint2012arXiv

Are valence quarks rotating?

We suggest to compare the deep inelastic scattering structure functions measured in the unpolarized charged-lepton scattering off a transversely polarized proton and off a longitudinally polarized proton at larger Bjorken variable $x$, one may get a direct evidence concerning the valence quark orbital angular momentum in the proton. This possible rotating effect is estimated by using a proton-ensemble model.

preprint2012arXiv

Stable magnetostructural coupling with tunable magnetoresponsive effects in hexagonal phase-transition ferromagnets

The magnetostructural coupling between the structural and the magnetic transition plays a crucial role in magnetoresponsive effects in a martensitic-transition system. A combination of various magnetoresponsive effects based on this coupling may facilitate the multifunctional applications of a host material. Here, we demonstrate a possibility to obtain a stable magnetostructural coupling in a broad temperature window from 350 to 70 K, showing tunable magnetoresponsive effects, based on simultaneous manipulation of the phase stability and the magnetic structure by suitable chemical substitution of iron in MnNiGe. The resultant MnNiGe:Fe exhibits a magnetic-field-induced martensitic transition from paramagnetic austenite to ferromagnetic martensite, featuring (i) a large volume increase, (ii) a distinct magnetization change, (iii) small thermal hysteresis and (iv) a giant negative magnetocaloric effect. The results indicate that stable magnetostructural coupling is accessible in hexagonal phase-transition systems to attain the magnetoresponsive effects with broad tunability.

preprint2010arXiv

Modeling and Simulation of Liquid Crystal Elastomers

We consider a continuum model describing the dynamic behavior of nematic liquid crystal elastomers (LCEs) and implement a numerical scheme to solve the governing equations. In the model, the Helmholtz free energy and Rayleigh dissipation are used, within a Lagrangian framework, to obtain the equations of motion. The free energy consists of both elastic and liquid crystalline contributions, each of which is a function of the material displacement and the orientational order parameter. The model gives dynamics for the material displacement, the scalar order parameter and the nematic director, the latter two of which correspond to the orientational order parameter tensor. Our simulations are carried out by solving the governing equations using an implicit-explicit scheme and the Chebyshev polynomial method. The simulations show that the model can successfully capture the shape changing dynamics of LCEs that have been observed in experiments, and also track the evolution of the order parameter tensor.

preprint2010arXiv

Particle multiplicities at LHC and deviations from limiting fragmentation

The pseudorapidity density of charged particles produced at LHC collisions are predicted by using two complementary production mechanisms with a set of consistent integrated and unintegrated parton distributions. We discuss the limiting fragmentation hypothesis and its possible violation, and we compare our model with other partonic models.

preprint2008arXiv

Nuclear Shadowing and Antishadowing in a Unitarized BFKL Equation

The nuclear shadowing and antishadowing effects are explained by a unitarized BFKL equation. The $Q^2$- and $x$-variations of the nuclear parton distributions are detailed based on the level of the unintegrated gluon distribution. In particular, the asymptotical behavior of the unintegrated gluon distribution near the saturation limit in nuclear targets is studied. Our results in the nuclear targets are insensitive to the input distributions if the parameters are fixed by the data of a free proton.

preprint2006arXiv

Antishadowing effects in the unitarized BFKL equation

A unitarized BFKL equation incorporating shadowing and antishadowing corrections of the gluon recombination is proposed. This equation reduces to the Balitsky-Kovchegov evolution equation near the saturation limit. We find that the antishadowing effects have a sizeable influence on the gluon distribution function in the preasymptotic regime.

preprint2005arXiv

A geometrizing higher twist effect on nuclear target

The higher twist effects in deep inelastic scattering on the nuclear target are studied using time ordered perturbation theory. We showed that the collinear rescattering of the outgoing quark on the extra nucleons via the contacting gluon-pair is dominant in nuclear size-dependent effects. The Qiu-Vitev resummation is proved by using the geometric properties of the higher twist amplitudes. The leading contributions of nuclear-enhanced effect to the DGLAP evolution equation are resummed in the same framework.

preprint2003arXiv

Contributions of gluon recombination to saturation phenomena

Parton distributions in the small $x$ region are numerically predicted by using a modified DGLAP equation with the GRV-like input distributions. We find that gluon recombination at twist-4 level obviously suppresses the rapid growth of parton densities with $x$ decrease. We show that before the saturation scale $Q^2_s$ is reached, saturation and partial saturation appear in the small $x$ behavior of parton distributions in nucleus and free proton, respectively. The antishadowing contributions to the saturation phenomena are also discussed.

preprint1998arXiv

A new approach to parton recombination in a QCD evolution equation

Parton recombination is reconsidered in perturbation theory without using the AGK cutting rules in the leading order of the recombination. We use time-ordered perturbation theory to sum the cut diagrams, which are neglected in the GLR evolution equation. We present a set of new evolution equations including parton recombination.

Wei Zhu

What is connected

Connect this record

See the researcher in context

Building this map preview

102 published item(s)

Noise-Started One-Step Real-World Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement

Efficient Multi-domain Text Recognition Deep Neural Network Parameterization with Residual Adapters

Text2MDT: Extracting Medical Decision Trees from Medical Texts

Overview of the PromptCBLUE Shared Task in CHIP2023

A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation

AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor

Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuning

Deep Federated Anomaly Detection for Multivariate Time Series Data

Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting

Fluid Simulation System Based on Graph Neural Network

Identification of stellar-mass black hole binaries and the validity of linear orbital motion approximation in microlensing

Improving Micro-video Recommendation by Controlling Position Bias

KMT-2021-BLG-0171Lb and KMT-2021-BLG-1689Lb: Two Microlensing Planets in the KMTNet High-cadence Fields with Followup Observations

Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis

Localized Adversarial Domain Generalization

No Significant Correlation between Line-emission and Continuum Substructures in the Molecules with ALMA at Planet-forming Scales Program

OGLE-2016-BLG-1093Lb: A Sub-Jupiter-mass Spitzer Planet Located in Galactic Bulge

OGLE-2018-BLG-0799Lb: a $q \sim 2.7 \times 10^{-3}$ Planet with Spitzer Parallax

OGLE-2019-BLG-1470LABc: Another Microlensing Giant Planet in a Binary System?

Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters

Structure-preserving GANs

Systematic KMTNet Planetary Anomaly Search, Paper I: OGLE-2019-BLG-1053Lb, A Buried Terrestrial Planet

Systematic KMTNet Planetary Anomaly Search. IV. Complete Sample of 2019 Prime-Field

The intrinsic multiplicity distribution of exoplanets revealed from the radial velocity method

Two Candidate KH 15D-like Systems from the Zwicky Transient Facility

Warning: The mini gamma-ray-bursts in planning hadron colliders beyond the LHC energies

Measuring microlensing parallax via simultaneous observations from Chinese Space Station Telescope and Roman Telescope

Neural Networks Enforcing Physical Symmetries in Nonlinear Dynamical Lattices: The Case Example of the Ablowitz-Ladik Model

OGLE-2019-BLG-0468Lb,c: two microlensing giant planets around a G-type star

Systematic KMTNet Planetary Anomaly Search, Paper II: Six New $q<2\times 10^{-4}$ Mass-ratio Planets

The 'COVID' Crash of the 2020 U.S. Stock Market

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization

Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification

Anomalous bremsstrahlung and the structure of cosmic ray electron-positron fluxes at the GeV-TeV energy range

Designing Xenes with Two-Dimensional Triangular Lattice

Detecting isolated stellar-mass black holes in the absence of microlensing parallax effect

Improved Bethe-Heitler formula

Looking for the possible gluon condensation signature in sub-TeV gamma-ray spectra: from active galactic nuclei to gamma ray bursts

OGLE-2017-BLG-0406: ${\it Spitzer}$ Microlens Parallax Reveals Saturn-mass Planet orbiting M-dwarf Host in the Inner Galactic Disk

OGLE-2018-BLG-1269Lb: A Jovian Planet With A Bright, $I=16$ Host

On the patterns observed in Kepler multi-planet systems

Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach

Unifying Specialist Image Embedding into Universal Image Embedding

Wave effects in the microlensing of pulsars and FRBs by point masses

Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning

A possible evidence of the gluon condensation effect in cosmic positron and gamma-ray spectra

Detection of Chinese Stock Market Bubbles with LPPLS Confidence Indicator

KMT-2016-BLG-1836Lb: A Super-Jovian Planet From A High-Cadence Microlensing Field

OGLE-2015-BLG-1771Lb: A Microlens Planet Orbiting an Ultracool Dwarf?

Real-time Prediction of Bitcoin Bubble Crashes

Spitzer + VLTI-GRAVITY Measure the Lens Mass of a Nearby Microlensing Event

Spitzer Microlensing parallax reveals two isolated stars in the Galactic bulge

Electronic nature of coverage-dependent nanosurface effect by cooperative orbital redistribution

Multi-appearance Segmentation and Extended 0-1 Program for Dense Small Object Tracking

A new perspective on gluon distribution at small x

Dependence of Small Planet Frequency on Stellar Metallicity Hidden by Their Prevalence

Emergent quasi-one-dimensionality in a kagomé magnet: A simple route to complexity

Free-floating planets from core accretion theory: microlensing predictions

Mass Measurements of Isolated Objects from Space-based Microlensing

OGLE-2015-BLG-0479LA,B: Binary Gravitational Microlens Characterized by Simultaneous Ground-based and Space-based Observation

Partonic structure of proton in the resonance region

The chaotic effects in a nonlinear QCD evolution equation

A determination of the flavor asymmetric sea quarks in the proton

A Triangular Decomposition Algorithm for Differential Polynomial Systems with Elementary Computation Complexity

Coherence times of precisely depth controlled NV centers in diamond

Competing Spin Liquid States in the Spin-$1/2$ Heisenberg Model On Triangular Lattice

Criteria for Sample Selection to Maximize Planet Sensitivity and Yield from Space-Based Microlens Parallax Surveys

Evidence of Different Formation Mechanisms for Hot versus Warm Super-Earths

Galton's Family Heights Data Revisited

Nucleon spin structure

Nucleon spin structure II: Spin structure function $g_1^p$ at small $x$

Nucleon spin structure III: Origins of the generalized Gerasimov-Drell-Hearn sum rule

Planet Sensitivity from Combined Ground- and Space-based Microlensing Observations

Quantum phase diagram of the spin-$1$ $J_1-J_2$ Heisenberg model on the honeycomb lattice