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Researcher profile

Yong Yang

Yong Yang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
hep-exphysics.ins-detmath.GRcond-mat.mtrl-sciComputer Visionastro-ph.GAastro-ph.SRcond-mat.dis-nnmath.RTphysics.med-phArtificial IntelligenceCryptography and Securityhep-phMachine Learningmath.RAnucl-exphysics.app-phphysics.opticsastro-ph.COastro-ph.HEComputer Science and Game Theorycond-mat.mes-hallcond-mat.softDatabaseseess.ASmath-phmath.ACmath.MPphysics.chem-phphysics.comp-phphysics.data-anquant-phQuantitative MethodsSound

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Published work

52 published item(s)

preprint2026arXiv

GPS-Synchronized Monitoring of Core-collapse Supernova Bursts with PandaX-4T via Coherent Elastic Neutrino Nuclear Scattering

The landmark detection of neutrinos from SN1987A marked the dawn of neutrino astrophysics. The neutrino burst provided essential insights into fundamental properties of neutrinos, and served as key probes of stellar evolution and supernova dynamics. The recent advancement in coherent elastic neutrino-nucleus scattering enables the detection of core-collapse supernova burst neutrinos using tonne-scale liquid xenon detectors originally designed for dark matter direct detection. Leveraging this capability, we developed and deployed an online supernova monitoring system for the PandaX-4T experiment. This system features a GPS module with millisecond-level timing precision, a low false-alarm rate, and high sensitivity to galactic core-collapse supernova explosion events. The methodology is robust, directly scalable, and planned for implementation in the next-generation PandaX-20T experiment.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Shattering the Echo Chamber: Hidden Safeguards in Manuscripts Against the AI Takeover of Peer Review

As LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer review to commercial chatbots. This concern stems from prior findings that current chatbots lack the independent critical thinking and depth of reasoning required to assess scientific novelty. One promising direction for mitigating this concern is to embed hidden instructions into manuscripts that disrupt or alter chatbot-generated reviews. However, existing methods remain intuitive and fragile, as they typically rely on homogeneous payloads injected in an inter-stream manner, rendering them susceptible to sanitization or neutralization. In this paper, we identify End-to-End Review Outsourcing as an emerging threat and propose IntraGuard, a black-box, venue-agnostic defense framework grounded in the structural--visual decoupling inherent to the PDF. Designed for committee-side deployment, IntraGuard supports both explicit strategies that trigger refusal or warning signals, and implicit strategies that embed predefined textual markers into the generated review. These strategies can be deployed via any of three intra-stream injection mechanisms, each of which seamlessly embeds heterogeneous defensive text objects within the PDF's underlying structure without altering its visual presentation. Extensive evaluations across 7 real-world commercial chatbot settings and 12 venues spanning diverse disciplines show that IntraGuard achieves a defense success rate of up to 84%, while preserving peer-review invariance for human reviewers. IntraGuard is lightweight and hardware-independent, incurring an average overhead of only one second per manuscript on a commodity personal computer. We further evaluate 11 adaptive attacks spanning manuscript sanitization and instruction interference, and discuss the implications of constructing ensemble defenses.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Cohomology of Restricted Twisted Heisenberg Lie Algebras

Over an algebraically closed ffeld F of characteristic p>0, the restricted twisted Heisenberg Lie algebras are studied. We use the Hochschild-Serre spectral sequence relative to its Heisenberg ideal to compute the trivial cohomology. The ordinary 1- and 2-cohomology spaces are used to compute the restricted 1- and 2-cohomology spaces and describe the restricted 1-dimensional central extensions, including explicit formulas for the Lie brackets and [p]-operators.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces

The sequential interaction network usually find itself in a variety of applications, e.g., recommender system. Herein, inferring future interaction is of fundamental importance, and previous efforts are mainly focused on the dynamics in the classic zero-curvature Euclidean space. Despite the promising results achieved by previous methods, a range of significant issues still largely remains open: On the bipartite nature, is it appropriate to place user and item nodes in one identical space regardless of their inherent difference? On the network dynamics, instead of a fixed curvature space, will the representation spaces evolve when new interactions arrive continuously? On the learning paradigm, can we get rid of the label information costly to acquire? To address the aforementioned issues, we propose a novel Contrastive model for Sequential Interaction Network learning on Co-Evolving RiEmannian spaces, CSINCERE. To the best of our knowledge, we are the first to introduce a couple of co-evolving representation spaces, rather than a single or static space, and propose a co-contrastive learning for the sequential interaction network. In CSINCERE, we formulate a Cross-Space Aggregation for message-passing across representation spaces of different Riemannian geometries, and design a Neural Curvature Estimator based on Ricci curvatures for modeling the space evolvement over time. Thereafter, we present a Reweighed Co-Contrast between the temporal views of the sequential network, so that the couple of Riemannian spaces interact with each other for the interaction prediction without labels. Empirical results on 5 public datasets show the superiority of CSINCERE over the state-of-the-art methods.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

A First Search for Solar $^8$B Neutrino in the PandaX-4T Experiment using Neutrino-Nucleus Coherent Scattering

A search for interactions from solar $^8$B neutrinos elastically scattering off xenon nuclei using PandaX-4T commissioning data is reported. The energy threshold of this search is further lowered compared with the previous search for dark matter, with various techniques utilized to suppress the background that emerges from data with the lowered threshold. A blind analysis is performed on the data with an effective exposure of 0.48 tonne$\cdot$year, and no significant excess of events is observed. Among results obtained using the neutrino-nucleus coherent scattering, our results give the best constraint on the solar $^8$B neutrino flux. We further provide a more stringent limit on the cross section between dark matter and nucleon in the mass range from 3 to 9 GeV/c$^2$.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Async-fork: Mitigating Query Latency Spikes Incurred by the Fork-based Snapshot Mechanism from the OS Level

In-memory key-value stores (IMKVSes) serve many online applications because of their efficiency. To support data backup, popular industrial IMKVSes periodically take a point-in-time snapshot of the in-memory data with the system call fork. However, this mechanism can result in latency spikes for queries arriving during the snapshot period because fork leads the engine into the kernel mode in which the engine is out-of-service for queries. In contrast to existing research focusing on optimizing snapshot algorithms, we optimize the fork operation to address the latency spikes problem from the operating system (OS) level, while keeping the data persistent mechanism in IMKVSes unchanged. Specifically, we first conduct an in-depth study to reveal the impact of the fork operation as well as the optimization techniques on query latency. Based on findings in the study, we propose Async-fork to offload the work of copying the page table from the engine (the parent process) to the child process as copying the page table dominates the execution time of fork. To keep data consistent between the parent and the child, we design the proactive synchronization strategy. Async-fork is implemented in the Linux kernel and deployed into the online Redis database in public clouds. Our experiment results show that compared with the default fork method in OS, Async-fork reduces the tail latency of queries arriving during the snapshot period by 81.76% on an 8GB instance and 99.84% on a 64GB instance.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

On the Characterization of Alternating Groups by Codegrees

Let $G$ be a finite group and $\mathrm{Irr}(G)$ the set of all irreducible complex characters of $G$. Define the codegree of $χ\in \mathrm{Irr}(G)$ as $\mathrm{cod}(χ):=\frac{|G:\mathrm{ker}(χ) |}{χ(1)}$ and denote by $\mathrm{cod}(G):=\{\mathrm{cod}(χ) \mid χ\in \mathrm{Irr}(G)\}$ the codegree set of $G$. Let $\mathrm{A}_n$ be an alternating group of degree $n \ge 5$. In this paper, we show that $\mathrm{A}_n$ is determined up to isomorphism by $\mathrm{cod}(\mathrm{A}_n)$.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

On the Characterization of Sporadic Simple Groups by Codegrees

Let $G$ be a finite group and $\mathrm{Irr}(G)$ the set of all irreducible complex characters of $G$. Define the codegree of $χ\in \mathrm{Irr}(G)$ as $\mathrm{cod}(χ):=\frac{|G:\mathrm{ker}(χ) |}{χ(1)}$ and denote by $\mathrm{cod}(G):=\{\mathrm{cod}(χ)|χ\in \mathrm{Irr}(G)\}$ the codegree set of $G$. Let $H$ be one of the $26$ sporadic simple groups. In this paper, we show that $H$ is determined up to isomorphism by cod$(H)$.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A New Cold Stream near the Southern Galactic Pole

We report the discovery of a cold stream near the southern Galactic pole (dubbed as SGP-S) detected in $Gaia$ Early Data Release 3. The stream is at a heliocentric distance of $\sim$ 9.5 kpc and spans nearly 58$^\circ$ by 0.6$^\circ$ on sky. The colour-magnitude diagram of SGP-S indicates an old and metal-poor (age $\sim$ 12 Gyr, [M/H] $\sim$ -2.0 dex) stellar population. The stream's surface brightness reaches an exceedingly low level of $Σ_G \simeq$ 36.2 mag arcsec$^{-2}$. Neither extant globular clusters nor other known streams are associated with SGP-S.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A Search for the Cosmic Ray Boosted Sub-GeV Dark Matter at the PandaX-II Experiment

We report a novel search for the cosmic ray boosted dark matter using the 100~tonne$\cdot$day full data set of the PandaX-II detector located at the China Jinping Underground Laboratory. With the extra energy gained from the cosmic rays, sub-GeV dark matter particles can produce visible recoil signals in the detector. The diurnal modulations in rate and energy spectrum are utilized to further enhance the signal sensitivity. Our result excludes the dark matter-nucleon elastic scattering cross section between 10$^{-31}$cm$^{2}$ and 10$^{-28}$cm$^{2}$ for a dark matter masses from 0.1 MeV/$c^2$ to 0.1 GeV/$c^2$, with a large parameter space previously unexplored by experimental collaborations.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A search for two-component Majorana dark matter in a simplified model using the full exposure data of PandaX-II experiment

In the two-component Majorana dark matter model, one dark matter particle can scatter off the target nuclei, and turn into a slightly heavier component. In the framework of a simplified model with a vector boson mediator, both the tree-level and loop-level processes contribute to the signal in direct detection experiment. In this paper, we report the search results for such dark matter from PandaX-II experiment, using total data of the full 100.7 tonne$\cdot$day exposure. No significant excess is observed, so strong constraints on the combined parameter space of mediator mass and dark matter mass are derived. With the complementary search results from collider experiments, a large range of parameter space can be excluded.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Atomic Origin of Annealing Embrittlement in Metallic Glasses

An atomistic understanding of annealing embrittlement is a longstanding issue for metallic glasses, which is still lacking due to the insurmountable gap between the thermal history of atomic models and laboratory-made samples. Here, based on a thermal-cycling annealing method that can vary the effective quenching rate over ten orders of magnitude, we perform an atomistic study of the ductile-brittle transition in a ternary model metallic glass, which can be keyed to the annealing embrittlement in bulk metallic glasses. We reveal that thermal annealing can effectively obliterate thermally active-able "defects", which are abundant in the hyper-quenched and ductile glass but gives rise to strain-created shear events in the well-annealed and brittle glass. While the activation of the strain-created events eventually causes single shear banding, other local structural disruptions can be "healed" by the same type of events upon stress reversal, thereby hindering shear band broadening or multiplication, and resulting in annealing embrittlement.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Automatic Generation of Product-Image Sequence in E-commerce

Product images are essential for providing desirable user experience in an e-commerce platform. For a platform with billions of products, it is extremely time-costly and labor-expensive to manually pick and organize qualified images. Furthermore, there are the numerous and complicated image rules that a product image needs to comply in order to be generated/selected. To address these challenges, in this paper, we present a new learning framework in order to achieve Automatic Generation of Product-Image Sequence (AGPIS) in e-commerce. To this end, we propose a Multi-modality Unified Image-sequence Classifier (MUIsC), which is able to simultaneously detect all categories of rule violations through learning. MUIsC leverages textual review feedback as the additional training target and utilizes product textual description to provide extra semantic information. Based on offline evaluations, we show that the proposed MUIsC significantly outperforms various baselines. Besides MUIsC, we also integrate some other important modules in the proposed framework, such as primary image selection, noncompliant content detection, and image deduplication. With all these modules, our framework works effectively and efficiently in JD.com recommendation platform. By Dec 2021, our AGPIS framework has generated high-standard images for about 1.5 million products and achieves 13.6% in reject rate.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Deep learning-based person re-identification methods: A survey and outlook of recent works

In recent years, with the increasing demand for public safety and the rapid development of intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot research topics in the computer vision field. The main research goal of person Re-ID is to retrieve persons with the same identity from different cameras. However, traditional person Re-ID methods require manual marking of person targets, which consumes a lot of labor cost. With the widespread application of deep neural networks, many deep learning-based person Re-ID methods have emerged. Therefore, this paper is to facilitate researchers to understand the latest research results and the future trends in the field. Firstly, we summarize the studies of several recently published person Re-ID surveys and complement the latest research methods to systematically classify deep learning-based person Re-ID methods. Secondly, we propose a multi-dimensional taxonomy that classifies current deep learning-based person Re-ID methods into four categories according to metric and representation learning, including methods for deep metric learning, local feature learning, generative adversarial learning and sequence feature learning. Furthermore, we subdivide the above four categories according to their methodologies and motivations, discussing the advantages and limitations of part subcategories. Finally, we discuss some challenges and possible research directions for person Re-ID.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Disappeared Command: Spoofing Attack On Automatic Speech Recognition Systems with Sound Masking

The development of deep learning technology has greatly promoted the performance improvement of automatic speech recognition (ASR) technology, which has demonstrated an ability comparable to human hearing in many tasks. Voice interfaces are becoming more and more widely used as input for many applications and smart devices. However, existing research has shown that DNN is easily disturbed by slight disturbances and makes false recognition, which is extremely dangerous for intelligent voice applications controlled by voice.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Global-Local Dynamic Feature Alignment Network for Person Re-Identification

The misalignment of human images caused by bounding box detection errors or partial occlusions is one of the main challenges in person Re-Identification (Re-ID) tasks. Previous local-based methods mainly focus on learning local features in predefined semantic regions of pedestrians. These methods usually use local hard alignment methods or introduce auxiliary information such as key human pose points to match local features, which are often not applicable when large scene differences are encountered. To solve these problems, we propose a simple and efficient Local Sliding Alignment (LSA) strategy to dynamically align the local features of two images by setting a sliding window on the local stripes of the pedestrian. LSA can effectively suppress spatial misalignment and does not need to introduce extra supervision information. Then, we design a Global-Local Dynamic Feature Alignment Network (GLDFA-Net) framework, which contains both global and local branches. We introduce LSA into the local branch of GLDFA-Net to guide the computation of distance metrics, which can further improve the accuracy of the testing phase. Evaluation experiments on several mainstream evaluation datasets including Market-1501, DukeMTMC-reID, CUHK03 and MSMT17 show that our method has competitive accuracy over the several state-of-the-art person Re-ID methods. Specifically, it achieves 86.1% mAP and 94.8% Rank-1 accuracy on Market1501.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Low Radioactive Material Screening and Background Control for the PandaX-4T Experiment

PandaX-4T is a ton-scale dark matter direct detection experiment using a dual-phase TPC technique at the China Jinping Underground Laboratory. Various ultra-low background technologies have been developed and applied to material screening for PandaX-4T, including HPGe gamma spectroscopy, ICP-MS, NAA, radon emanation measurement system, krypton assay station, and alpha detection system. Low background materials were selected to assemble the detector. Surface treatment procedures were investigated to further suppress radioactive background. Combining measured results and Monte Carlo simulation, the total material background rates of PandaX-4T in the energy region of 1-25 keV$\rm{}_{ee}$ are estimated to be (9.9 $\pm$ 1.9) $\times \ 10^{-3}$ mDRU for electron recoil and (2.8 $\pm$ 0.6) $\times \ 10^{-4}$ mDRU for nuclear recoil. In addition, $^{nat}$Kr in the detector is estimated to be <8 ppt.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Neutron-induced nuclear recoil background in the PandaX-4T experiment

Neutron-induced nuclear recoil background is critical to the dark matter searches in the PandaX-4T liquid xenon experiment. This paper studies the feature of neutron background in liquid xenon and evaluates their contribution in the single scattering nuclear recoil events through three methods. The first method is fully Monte Carlo simulation based. The last two are data-driven methods that also use the multiple scattering signals and high energy signals in the data, respectively. In the PandaX-4T commissioning data with an exposure of 0.63 tonne-year, all these methods give a consistent result that there are $1.15\pm0.57$ neutron-induced background in dark matter signal region within an approximated nuclear recoil energy window between 5 and 100 keV.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

On cohomology and deformations of Jacobi-Jordan algebras

In this paper we study cohomology and deformations of Jacobi-Jordan algebras. We develop their formal deformation theory. In particular, we introduce a method to construct a versal deformation for a given Jacobi-Jordan algebra, which can induce all deformations and is unique on the infinitesimal level. We construct formal 1-parameter deformations of Jacobi-Jordan algebras up to dimension 5 and versal deformations for 3-dimensional Jacobi-Jordan algebras.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Readout electronics and data acquisition system of PandaX-4T experiment

PandaX-4T is a dark matter direct detection experiment located in China jinping underground laboratory. The central apparatus is a dual-phase xenon detector containing 4 ton liquid xenon in the sensitive volume, with about 500 photomultipliers instrumented in the top and the bottom of the detector. In this paper we present a completely new system of readout electronics and data acquisition in the PandaX-4T experiment. Compared to the one used in the previous PandaX dark matter experiments, the new system features triggerless readout and higher bandwidth. With triggerless readout, dark matter searches are not affected by the efficiency loss of external triggers. The system records single photelectron signals of the dominant PMTs with an average efficiency of 96\%, and achieves the bandwidth of more than 450 MB/s. The system has been used to successfully acquire data during the commissioning runs of PandaX-4T.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Revisit NGC 5466 Tidal Stream with $Gaia$, SDSS/SEGUE and LAMOST

By mining the data from $Gaia$ EDR3, SDSS/SEGUE DR16 and LAMOST DR8, 11 member stars of the NGC 5466 tidal stream are detected and 7 of them are newly identified. To reject contaminators, a variety of cuts are applied in sky position, color-magnitude diagram, metallicity, proper motion and radial velocity. We compare our data to a mock stream generated by modeling the cluster&#39;s disruption under a smooth Galactic potential plus the Large Magellanic Cloud (LMC). The concordant trends in phase-space between the model and observations imply that the stream might have been perturbed by LMC. The two most distant stars among 11 detected members trace the stream&#39;s length to $60^\circ$ of sky, supporting and extending the previous length of $45^\circ$. Given that NGC 5466 is so distant and potentially has a longer tail than previously thought, we expect that NGC 5466 tidal stream could be a useful tool in constraining the Milky Way gravitational field.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Study of background from accidental coincidence signals in the PandaX-II experiment

The PandaX-II experiment employed a 580kg liquid xenon detector to search for the interactions between dark matter particles and the target xenon atoms. The accidental coincidences of isolated signals result in a dangerous background which mimic the signature of the dark matter. We performed a detailed study on the accidental coincidence background in PandaX-II, including the possible origin of the isolated signals, the background level and corresponding background suppression method. With a boosted-decision-tree algorithm, the accidental coincidence background is reduced by 70% in the dark matter signal region, thus the sensitivity of dark matter search at PandaX-II is improved.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The Prime Graphs of Some Classes of Finite Groups

In this paper we study prime graphs of finite groups. The prime graph of a finite group $G$, also known as the Gruenberg-Kegel graph, is the graph with vertex set {primes dividing $|G|$} and an edge $p$-$q$ if and only if there exists an element of order $pq$ in $G$. In finite group theory, studying the prime graph of a group has been an important topic for the past almost half century. Only recently prime graphs of solvable groups have been characterized in graph theoretical terms only. In this paper, we continue this line of research and give complete characterizations of several classes of groups, including groups of square-free order, metanilpotent groups, groups of cube-free order, and, for any $n\in \mathbb{N}$, solvable groups of $n^\text{th}$-power-free order. We also explore the prime graphs of groups whose composition factors are cyclic or $A_5$ and draw connections to a conjecture of Maslova. We then propose an algorithm that recovers the prime graph from a dual prime graph.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks

One major goal of the AI security community is to securely and reliably produce and deploy deep learning models for real-world applications. To this end, data poisoning based backdoor attacks on deep neural networks (DNNs) in the production stage (or training stage) and corresponding defenses are extensively explored in recent years. Ironically, backdoor attacks in the deployment stage, which can often happen in unprofessional users&#39; devices and are thus arguably far more threatening in real-world scenarios, draw much less attention of the community. We attribute this imbalance of vigilance to the weak practicality of existing deployment-stage backdoor attack algorithms and the insufficiency of real-world attack demonstrations. To fill the blank, in this work, we study the realistic threat of deployment-stage backdoor attacks on DNNs. We base our study on a commonly used deployment-stage attack paradigm -- adversarial weight attack, where adversaries selectively modify model weights to embed backdoor into deployed DNNs. To approach realistic practicality, we propose the first gray-box and physically realizable weights attack algorithm for backdoor injection, namely subnet replacement attack (SRA), which only requires architecture information of the victim model and can support physical triggers in the real world. Extensive experimental simulations and system-level real-world attack demonstrations are conducted. Our results not only suggest the effectiveness and practicality of the proposed attack algorithm, but also reveal the practical risk of a novel type of computer virus that may widely spread and stealthily inject backdoor into DNN models in user devices. By our study, we call for more attention to the vulnerability of DNNs in the deployment stage.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

At what mass are stars braked? The implication from the turnoff morphology of NGC 6819

Extended main-sequence turnoffs apparent in most young and intermediate-age clusters (younger than ~2 Gyr) are known features caused by fast rotating early-type (earlier than F-type) stars. Late-type stars are not fast rotators because their initial angular momenta have been quickly dispersed due to magnetic braking. However, the mass limit below which stars have been magnetically braked has not been well constrained by observation. In this paper, we present an analysis of the eMSTO of NGC 6819, an open cluster of an intermediate-age (~2.5 Gyr), believed to be comparable to the lifetime of stars near the mass limit for magnetic braking. By comparing the observation with synthetic CMDs, we find that NGC 6819 does not harbor an obvious eMSTO. The morphology of its TO region can be readily explained by a simple stellar population considering the observational uncertainties as well as the differential reddening. In addition, the MSTO stars in NGC 6819 have very small values of average rotational velocity and dispersion, indicating that they have undergone significant magnetic braking. Combining with results in the literature for clusters of younger ages, our current work suggests that the critical age for the disappearance of eMSTO in star clusters must be shorter but very close to the age of NGC 6819, and this, in turn, implies a critical stellar mass for magnetic braking at solar metallicity above but close to 1.54 $M_{\odot}$ based on the PARSEC model. We emphasize that the phenomenon of eMSTO could provide a unique way to constrain the onset mass of magnetic braking.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Atomic Resonant Tunneling in the Surface Diffusion of H Atoms on Pt(111)

The quantum motions of hydrogen (H) atoms play an important role in the dynamical properties and functionalities of condensed phase materials as well as biological systems. In this work, based on the transfer matrix method and first-principles calculations, we study the dynamics of H atoms on Pt(111) surface and numerically calculate the quantum probability of H transferring across the surface potential fields. Atomic resonant tunneling (ART) is demonstrated along a number of diffusion pathways. Owing to resonant tunneling, anomalous rate of transfer is predicted for H diffusion along certain path at low temperatures.The role of nuclear quantum effects (NQEs) on the surface reactions involving H is investigated, by analyzing the probabilities of barrier-crossing. The effective barrier is significantly reduced due to quantum tunneling, and decreases monotonically with temperature within a certain region. For barrier-crossing processes where the Arrhenius type relation applies, we show the existence of a nonzero low-temperature limit of rate constant, which indicates the nontrivial activity of H-involved reactions at cryogenic conditions.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Dark Matter Search Results from the PandaX-4T Commissioning Run

We report the first dark matter search results using the commissioning data from PandaX-4T. Using a time projection chamber with 3.7-tonne of liquid xenon target and an exposure of 0.63 tonne$\cdot$year, 1058 candidate events are identified within an approximate nuclear recoil energy window between 5 and 100 keV. No significant excess over background is observed. Our data set a stringent limit to the dark matter-nucleon spin-independent interactions, with a lowest excluded cross section (90% C.L.) of $3.8\times10^{-47} $cm$^2$ at a dark matter mass of 30 GeV/$c^2$.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Fully Automated Noncoplanar Radiation Therapy Treatment Planning

Noncoplanar radiation therapy treatment planning has the potential to improve dosimetric quality as compared to traditional coplanar techniques. Likewise, automated treatment planning algorithms can reduce a planner&#39;s active treatment planning time and remove inter-planner variability. To address the limitations of traditional treatment planning, we have been developing a suite of algorithms called station parameter optimized radiation therapy (SPORT). Within the SPORT suite of algorithms, we propose a method called NC-POPS to produce noncoplanar (NC) plans using the fully automated Pareto Optimal Projection Search (POPS) algorithm. Our NC-POPS algorithm extends the original POPS algorithm to the noncoplanar setting with potential applications to both IMRT and VMAT. The proposed algorithm consists of two main parts: 1) noncoplanar beam angle optimization (BAO) and 2) fully automated inverse planning using the POPS algorithm. We evaluate the performance of NC-POPS by comparing between various noncoplanar and coplanar configurations. To evaluate plan quality, we compute the homogeneity index (HI), conformity index (CI), and dose-volume histogram (DVH) statistics for various organs-at-risk (OARs). As compared to the evaluated coplanar baseline methods, the proposed NC-POPS method achieves significantly better OAR sparing, comparable or better dose conformity, and similar dose homogeneity. Our proposed NC-POPS algorithm provides a modular approach for fully automated treatment planning of noncoplanar IMRT cases with the potential to substantially improve treatment planning workflow and plan quality.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Internal Calibration of the PandaX-II Detector with Radon Gaseous Sources

We have developed a low-energy electron recoil (ER) calibration method with $^{220}$Rn for the PandaX-II detector. $^{220}$Rn, emanated from natural thorium compounds, was fed into the detector through the xenon purification system. From 2017 to 2019, we performed three dedicated calibration campaigns with different radon sources. We studied the detector response to $α$, $β$, and $γ$ particles with focus on low energy ER events. During the runs in 2017 and 2018, the amount of radioactivity of $^{222}$Rn were on the order of 1\% of that of $^{220}$Rn and thorium particulate contamination was negligible, especially in 2018. We also measured the background contribution from $^{214}$Pb for the first time in PandaX-II with the help from a $^{222}$Rn injection. Calibration strategy with $^{220}$Rn and $^{222}$Rn will be implemented in the upcoming PandaX-4T experiment and can be useful for other xenon-based detectors as well.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Light yield and field dependence measurement in PandaX-II dual-phase xenon detector

The dual-phase xenon time projection chamber (TPC) is one of the most sensitive detector technology for dark matter direct search, where the energy deposition of incoming particle can be converted into photons and electrons through xenon excitation and ionization. The detector response to signal energy deposition varies significantly with the electric field in liquid xenon. We study the detector&#39;s light yield and its dependence on the electric field in the PandaX-II dual-phase detector containing 580~kg liquid xenon in the sensitive volume. From our measurements, the light yield at electric fields from 0~V/cm to 317~V/cm is obtained for energy depositions up to 236~keV.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Liquefaction-induced Plasticity from Entropy-boosted Amorphous Ceramics

Ceramics are easy to break, and very few generic mechanisms are available for improving their mechanical properties, e.g., the 1975-discovered anti-fracture mechanism is strictly limited to zirconia and hafnia. Here we report a general mechanism for achieving high plasticity through liquefaction of ceramics. We further disclose the general material design strategies to achieve this difficult task through entropy-boosted amorphous ceramics (EBACs), enabling fracture-resistant properties that can withstand severe plastic deformation (e.g., over 95%, deformed to a thickness of a few nanometers) while maintaining high hardness and reduced modulus. The findings reported here open a new route to ductile ceramics and many applications.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Pareto Optimal Projection Search (POPS): Automated Radiation Therapy Treatment Planning by Direct Search of the Pareto Surface

Objective: Radiation therapy treatment planning is a time-consuming, iterative process with potentially high inter-planner variability. Fully automated treatment planning processes could reduce a planner&#39;s active treatment planning time and remove inter-planner variability, with the potential to tremendously improve patient turnover and quality of care. In developing fully automated algorithms for treatment planning, we have two main objectives: to produce plans that are 1) Pareto optimal and 2) clinically acceptable. Here, we propose the Pareto optimal projection search (POPS) algorithm, which provides a general framework for directly searching the Pareto front. Methods: Our POPS algorithm is a novel automated planning method that combines two main search processes: 1) gradient-free search in the decision variable space and 2) projection of decision variables to the Pareto front using the bisection method. We demonstrate the performance of POPS by comparing with clinical treatment plans. As one possible quantitative measure of treatment plan quality, we construct a clinical acceptability scoring function (SF) modified from the previously developed general evaluation metric (GEM). Results: On a dataset of 21 prostate cases collected as part of clinical workflow, our proposed POPS algorithm produces Pareto optimal plans that are clinically acceptable in regards to dose conformity, dose homogeneity, and sparing of organs-at-risk. Conclusion: Our proposed POPS algorithm provides a general framework for fully automated treatment planning that achieves clinically acceptable dosimetric quality without requiring active planning from human planners. Significance: Our fully automated POPS algorithm addresses many key limitations of other automated planning approaches, and we anticipate that it will substantially improve treatment planning workflow.

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preprint2021arXiv

Results of Dark Matter Search using the Full PandaX-II Exposure

We report the dark matter search results obtained using the full 132 ton$\cdot$day exposure of the PandaX-II experiment, including all data from March 2016 to August 2018. No significant excess of events is identified above the expected background. Upper limits are set on the spin-independent dark matter-nucleon interactions. The lowest 90% confidence level exclusion on the spin-independent cross section is $2.2\times 10^{-46}$ cm$^2$ at a WIMP mass of 30 GeV/$c^2$.

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preprint2021arXiv

White dwarfs identified in LAMOST Data Release 5

In this paper, we report white dwarfs identified in the 5th Data Release of the Large Area Multi-Object fibre Spectroscopic Telescope, including spectral types of DA, DB, DC, DZ, and so on. There are 2 625 DA spectra of 2 281 DA stars, 182 DB spectra of 166 DB stars, 62 DC spectra of 58 DC stars, 36 DZ spectra of 33 DZ stars and many other types identified, in addition to our previous paper (Data Release 2). Among those sources, 393 DA stars and 46 DB stars are new identifications after cross-matching with the literature. In order to select DA candidates, we use the classification result from the LAMOST pipeline, colour-colour cut method and a random forest machine learning method. For DBs, since there is no template for DB in the pipeline model, a random forest machine learning method is chosen to select candidates. All the WD candidates have been visually checked individually. The parameters of effective temperature, surface gravity, mass, and cooling age have been estimated for relatively high signal-to-noise ratio DAs and DBs. The peaks of the DA and DB mass distributions are found to be around 0.62Msun and 0.65Msun, respectively. Finally, the data and method we used to select white dwarf candidates for the second phase of LAMOST survey are also addressed in this paper.

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preprint2020arXiv

A Catalog of RV Variable Star Candidates from LAMOST

RV variable stars are important in astrophysics. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has provided ~ 6.5 million stellar spectra in its Data Release 4 (DR4). During the survey, ~ 4.7 million unique sources were targeted and ~ 1 million stars observed repeatedly. The probabilities of stars being RV variables are estimated by comparing the observed radial velocity variations with the simulated ones. We build a catalog of 80,702 RV variable candidates with probability greater than 0.60 by analyzing the duplicate-observed multi-epoch sources covered by the LAMOST DR4. Simulations and cross-identifications show that the purity of the catalog is higher than 80%. The catalog consists of 77% binary systems and 7% pulsating stars as well as 16% pollution by single stars. 3,138 RV variables are classified through cross-identifications with published results in literatures. By using the 3,138 sources common to both LAMOST and a collection of published RV variable catalogs we are able to analyze LAMOST&#39;s RV variable detection rate. The efficiency of the method adopted in this work relies not only on the sampling frequency of observations but also periods and amplitudes of RV variables. With the progress of LAMOST, Gaia and other surveys, more and more RV variables would will be confirmed and classified. This catalog is valuable for other large-scale surveys, especially for RV variable searches. The catalog will be released according to the LAMOST Data Policy via http://dr4.lamost.org.

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preprint2020arXiv

A high entropy alloy as very low melting point solder for advanced electronic packaging

SnBiInZn based high entropy alloy (HEA) was studied as a low reflow temperature solder with melting point around 80 oC. The wetting angle is about 52o after reflow at 100 oC for 10 min. The interfacial intermetallic compound (IMC) growth kinetics was measured to be ripening-control with a low activation energy about 18.0 kJ/mol, however, the interfacial reaction rate is very slow, leading to the formation of a very thin IMC layer. The low melting point HEA solder has potential applications in advanced electronic packaging technology, especially for bio-medical devices.

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preprint2020arXiv

A lower bound for the number of odd-degree representations of a finite group

Let $G$ be a finite group and $P$ a Sylow $2$-subgroup of $G$. We obtain both asymptotic and explicit bounds for the number of odd-degree irreducible complex representations of $G$ in terms of the size of the abelianization of $P$. To do so, we, on one hand, make use of the recent proof of the McKay conjecture for the prime 2 by Malle and Späth, and, on the other hand, prove lower bounds for the class number of the semidirect product of an odd-order group acting on an abelian $2$-group.

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preprint2020arXiv

Adjoint cohomology of two-step nilpotent Lie superalgebras

In this paper, we study the cup products and Betti numbers over cohomology superspaces of two-step nilpotent Lie superalgebras with coefficients in the adjoint modules over an algebraically closed field of characteristic zero. As an application, we prove that the cup product over the adjoint cohomology superspaces for Heisenberg Lie superalgebras is trivial and we also determine the adjoint Betti numbers for Heisenberg Lie superalgebras by means of Hochschild-Serre spectral sequences.

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preprint2020arXiv

Cost Sharing Security Information with Minimal Release Delay

We study a cost sharing problem derived from bug bounty programs, where agents gain utility by the amount of time they get to enjoy the cost shared information. Once the information is provided to an agent, it cannot be retracted. The goal, instead of maximizing revenue, is to pick a time as early as possible, so that enough agents are willing to cost share the information and enjoy it for a premium time period, while other agents wait and enjoy the information for free after a certain amount of release delay. We design a series of mechanisms with the goal of minimizing the maximum delay and the total delay. Under prior-free settings, our final mechanism achieves a competitive ratio of $4$ in terms of maximum delay, against an undominated mechanism. Finally, we assume some distributions of the agents&#39; valuations, and investigate our mechanism&#39;s performance in terms of expected delays.

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preprint2020arXiv

Data-driven dose calculation algorithm based on deep learning

In this study we performed a feasibility investigation on implementing a fast and accurate dose calculation based on a deep learning technique. A two dimensional (2D) fluence map was first converted into a three dimensional (3D) volume using ray traversal algorithm. A 3D U-Net like deep residual network was then established to learn a mapping between this converted 3D volume, CT and 3D dose distribution. Therefore an indirect relationship was built between a fluence map and its corresponding 3D dose distribution without using significantly complex neural networks. 200 patients, including nasopharyngeal, lung, rectum and breast cancer cases, were collected and applied to train the proposed network. Additional 47 patients were randomly selected to evaluate the accuracy of the proposed method through comparing dose distributions, dose volume histograms (DVH) and clinical indices with the results from a treatment planning system (TPS), which was used as the ground truth in this study. Results: The proposed deep learning based dose calculation algorithm achieved good predictive performance. For 47 tested patients, the average per-voxel bias of the deep learning calculated value and standard deviation (normalized to the prescription), relative to the TPS calculation, is 0.17%. The average deep learning calculated values and standard deviations for relevant clinical indices were compared with the TPS calculated results and the t-test p-values demonstrated the consistency between them. Conclusions: In this study we developed a new deep learning based dose calculation method. This approach was evaluated by the clinical cases with different sites. Our results demonstrated its feasibility and reliability and indicated its great potential to improve the efficiency and accuracy of radiation dose calculation for different treatment modalities

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preprint2020arXiv

On p-parts of Brauer character degrees and p-regular conjugacy class sizes

Let $G$ be a finite group, $p$ a prime, and $IBr_p(G)$ the set of irreducible $p$-Brauer characters of $G$. Let $\bar e_p(G)$ be the largest integer such that $p^{\bar e_p(G)}$ divides $χ(1)$ for some $χ\in IBr_p(G)$. We show that $|G:O_p(G)|_p \leq p^{k \bar e_p(G)}$ for an explicitly given constant $k$. We also study the analogous problem for the $p$-parts of the conjugacy class sizes of $p$-regular elements of finite groups.

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preprint2020arXiv

On the odd order composition factors of finite linear groups

In this paper, we study the product of orders of composition factors of odd order in a composition series of a finite linear group. First we generalize a result by Manz and Wolf about the order of solvable linear groups of odd order. Then we use this result to find bounds for the product of orders of composition factors of odd order in a composition series of a finite linear group.

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preprint2020arXiv

Region Proposal Network with Graph Prior and IoU-Balance Loss for Landmark Detection in 3D Ultrasound

3D ultrasound (US) can facilitate detailed prenatal examinations for fetal growth monitoring. To analyze a 3D US volume, it is fundamental to identify anatomical landmarks of the evaluated organs accurately. Typical deep learning methods usually regress the coordinates directly or involve heatmap-matching. However, these methods struggle to deal with volumes with large sizes and the highly-varying positions and orientations of fetuses. In this work, we exploit an object detection framework to detect landmarks in 3D fetal facial US volumes. By regressing multiple parameters of the landmark-centered bounding box (B-box) with a strict criteria, the proposed model is able to pinpoint the exact location of the targeted landmarks. Specifically, the model uses a 3D region proposal network (RPN) to generate 3D candidate regions, followed by several 3D classification branches to select the best candidate. It also adopts an IoU-balance loss to improve communications between branches that benefits the learning process. Furthermore, it leverages a distance-based graph prior to regularize the training and helps to reduce false positive predictions. The performance of the proposed framework is evaluated on a 3D US dataset to detect five key fetal facial landmarks. Results showed the proposed method outperforms some of the state-of-the-art methods in efficacy and efficiency.

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preprint2020arXiv

Revealing Rejuvenated Disorder States towards Crystallization in a Supercooled Metallic Glass-Forming Liquid

We report a metadynamics simulation study of crystallization in a deep undercooled metallic glass-forming liquid by developing appropriate collective variables. Through a combined analysis of free energy surface (FES) and atomic-level behaviors, a picture of an abnormal-endothermic crystallization process is revealed: rejuvenated disorder states with less local fivefold-symmetry and fast dynamics form firstly by changing the local chemical order around Cu atoms, which then act as the precursor for the nucleation of well-ordered crystallites. This process reflects a complex energy landscape with well-separated glassy and crystal basins, giving rise to the direct evidence of intrinsic frustration against crystallization in deep undercooled metallic glass forming liquids. Moreover, the rejuvenated disorder states with distinct physical behaviors offer great opportunities to tailor the performances of metallic glass by controlling the thermal history of a metallic melt.

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preprint2020arXiv

Soft mode parameter as an indicator for the activation energy spectra in metallic glass

The activation energy (E_A) spectra of potential energy landscape (PEL) provides a convenient perspective for interpreting complex phenomena in amorphous materials; however, the link between the E_A spectra and other physical properties in metallic glasses is still mysterious. By systematically probing the E_A spectra for numerous metallic glass samples with distinct local geometric ordering, which correspond to broad processing histories, it is found that the shear modulus of the samples are strongly correlated with the arithmetic mean of the E_A spectra rather than with the local geometrical ordering. Furthermore, we studied the correlation of the obtained E_A spectra and various well-established physical parameters. The outcome of our research clearly demonstrates that the soft mode parameter Ψ and the E_A spectrum are correlated; therefore, it could be a good indicator of metallic glass properties and sheds important light on the structure-property relationship in metallic glass through the medium of PEL.

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preprint2020arXiv

Tailored pore gradient in phenolic membranes for adjustable permselectivity by leveraging different poloxamers

Cost-affordable phenolic membranes having gradient nanostructures can be facilely synthesized from resol oligomers in the presence of ZnCl2 and poloxamers. The gradient nanostructures are formed by stacking phenolic nanoparticles with gradually enlarged diameters as the distance from the upper surface increases. The use of poloxamers for creating gelation surroundings is of great significance for controlling the growth of phenolic nanoparticles, which in turn dictates the performance of the phenolic membranes thus-produced. Hence, a study of the effects of poloxamers species on the preparation of the phenolic membranes is highly demanded since such robust membranes have much potential to be scale up for mass production. Herein, the poloxamer Pluronic F127 (EO106-PO70-EO106; EO = ethyleneoxide, PO = propyleneoxide) was introduced in the membrane-forming formulations. As opposed to P123 (EO20-PO70-EO20) that we used previously, F127 possessing extended PEO chains can delay the gelation during membrane formation. Hence, the phenolic nucleates are able to grow for longer durations, leading to the generation of more distinct gradient nanostructures in the phenolic membranes. Enhanced permeance can then be realized with F127-derived phenolic membranes. We also demonstrate that L31 (EO1-PO22-EO1) with merely single terminal EO units at the ends of the PPO block could be used to prepare gradient phenolic membranes. This work is not only much helpful to deeply understand the design of the structural gradient in phenolic membranes, but capable of sheding light on the development of such intriguing structures for water purification.

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preprint2019arXiv

In situ observation of slow and tunnelling light at the cutoff wavelength of an optical fiber

Slow waves and tunneling waves can meet at the cutoff wavelengths and/or transmission band edges of optical and quantum mechanical waveguides. The experimental investigation of this phenomenon, previously performed using various optical microstructures, is challenged by fabrication imperfections and material losses. Here, we demonstrate this phenomenon in situ for whispering gallery modes slowly propagating along a standard optical fiber, which possesses the record uniformity and exceptionally small transmission losses. Slow axial propagation dramatically increases the longitudinal wavelength of light and allows us to measure nanosecond-long tunneling times along tunable potential barriers having the width of hundreds of microns. This demonstration paves a simple and versatile way to investigate and employ the interplaying slow and tunneling light.

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preprint2019arXiv

Rectangular SNAP microresonator fabricated with a femtosecond laser

SNAP microresonators, which are fabricated by nanoscale effective radius variation (ERV) of the optical fiber with sub-angstrom precision, can be potentially used as miniature classical and quantum signal processors, frequency comb generators, as well as ultraprecise microfluidic and environmental optical sensors. Many of these applications require the introduction of nanoscale ERV with a large contrast α which is defined as the maximum shift of the fiber cutoff wavelength introduced per unit length of the fiber axis. The previously developed fabrication methods of SNAP structures, which used focused CO2 and femtosecond laser beams, achieved α ~ 0.02 nm/um. Here we develop a new fabrication method of SNAP microresonators with a femtosecond laser which allows us to demonstrate a 50-fold improvement of previous results and achieve α ~ 1 nm/um. Furthermore, our fabrication method enables the introduction of ERV which is several times larger than the maximum ERV demonstrated previously. As an example, we fabricate a rectangular SNAP resonator and investigate its group delay characteristics. Our experimental results are in good agreement with theoretical simulations. Overall, the developed approach allows us to reduce the axial scale of SNAP structures by an order of magnitude.

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preprint2019arXiv

Searching for Neutrino-less Double Beta Decay of $^{136}$Xe with PandaX-II Liquid Xenon Detector

We report the Neutrino-less Double Beta Decay (NLDBD) search results from PandaX-II dual-phase liquid xenon time projection chamber. The total live time used in this analysis is 403.1 days from June 2016 to August 2018. With NLDBD-optimized event selection criteria, we obtain a fiducial mass of 219 kg of natural xenon. The accumulated xenon exposure is 242 kg$\cdot$yr, or equivalently 22.2 kg$\cdot$yr of $^{136}$Xe exposure. At the region around $^{136}$Xe decay Q-value of 2458 keV, the energy resolution of PandaX-II is 4.2%. We find no evidence of NLDBD in PandaX-II and establish a lower limit for decay half-life of 2.4 $ \times 10^{23} $ yr at the 90% confidence level, which corresponds to an effective Majorana neutrino mass $m_{ββ} < (1.3 - 3.5)$ eV. This is the first NLDBD result reported from a dual-phase xenon experiment.

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