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Yong Yang

Publications and source records attributed to Yong Yang.

At least 181 records · Page 10Linked to original sources
arXiv2022

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'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'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.

astro-ph.GA↗
arXiv2022

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.

physics.ins-det↗
arXiv2022

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.

math.AC↗
arXiv2022

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.

cs.CV↗
arXiv2022

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.

cs.CV↗
arXiv2022

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.

math.GR↗
arXiv2021

A 500 MS/s waveform digitizer for PandaX dark matter experiments

Waveform digitizers are key readout instruments in particle physics experiments. In this paper, we present a waveform digitizer for the PandaX dark matter experiments. It supports both external-trigger readout and triggerless readout, accommodating the needs of low rate full-waveform readout and channel-independent low threshold acquisition, respectively. This digitizer is a 8-channel VME board with a sampling rate of 500 MS/s and 14-bit resolution for each channel. A digitizer system consisting of 72 channels has been tested in situ of the PandaX-4T experiment. We report the system performance with real data.

physics.ins-det↗
arXiv2021

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/$c^2$.

hep-ex↗
arXiv2021

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'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.

physics.ins-det↗
arXiv2021

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.

astro-ph.SR↗
arXiv2021

A search for solar axions and anomalous neutrino magnetic moment with the complete PandaX-II data

We report a search for new physics signals using the low energy electron recoil events in the complete data set from PandaX-II, in light of the recent event excess reported by XENON1T. The data correspond to a total exposure of 100.7 ton-day with liquid xenon. With robust estimates of the dominant background spectra, we perform sensitive searches on solar axions and neutrinos with enhanced magnetic moment. We find that the axion-electron coupling $g_{Ae}<4.6\times 10^{-12}$ for an axion mass less than $\rm 0.1~keV/c^2$ and the neutrino magnetic moment $μ_ν<4.9\times 10^{-11}μ_{B}$ at 90% confidence level. The observed excess from XENON1T is within our experimental constraints.

hep-ex↗
arXiv2021

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.

astro-ph.SR↗
arXiv2021

On Gluck's conjecture

This paper presents the best known bounds for a conjecture of Gluck and a conjecture of Navarro.

math.GR↗
arXiv2021

Constraining self-interacting dark matter with the full dataset of PandaX-II

Self-interacting Dark Matter (SIDM) is a leading candidate proposed to solve discrepancies between predictions of the prevailing cold dark matter theory and observations of galaxies. Many SIDM models predict the existence of a light force carrier that mediate strong dark matter self-interactions. If the mediator couples to the standard model particles, it could produce characteristic signals in dark matter direct detection experiments. We report searches for SIDM models with a light mediator using the full dataset of the PandaX-II experiment, based on a total exposure of 132 tonne-days. No significant excess over background is found, and our likelihood analysis leads to a strong upper limit on the dark matter-nucleon coupling strength. We further combine the PandaX-II constraints and those from observations of the light element abundances in the early universe, and show that direct detection and cosmological probes can provide complementary constraints on dark matter models with a light mediator.

hep-ex↗
arXiv2021

Meta-optimization for Fully Automated Radiation Therapy Treatment Planning

Objective: Radiation therapy treatment planning is a time-consuming process involving iterative adjustments of hyperparameters. To automate the treatment planning process, we propose a meta-optimization framework, called MetaPlanner (MP). Methods: Our MP algorithm automates planning by performing optimization of treatment planning hyperparameters. The algorithm uses a derivative-free method (i.e. parallel Nelder-Mead simplex search) to search for weight configurations that minimize a meta-scoring function. Meta-scoring is performed by constructing a tier list of the relevant considerations (e.g. dose homogeneity, conformity, spillage, and OAR sparing) to mimic the clinical decision-making process. Additionally, we have made our source code publicly available via github. Results: The proposed MP method is evaluated on two datasets (21 prostate cases and 6 head and neck cases) collected as part of clinical workflow. MP is applied to both IMRT and VMAT planning and compared to a baseline of manual VMAT plans. MP in both IMRT and VMAT scenarios has comparable or better performance than manual VMAT planning for all evaluated metrics. Conclusion: Our proposed MP provides a general framework for fully automated treatment planning that produces high quality treatment plans. Significance: Our MP method promises to substantially reduce the workload of treatment planners while maintaining or improving plan quality.

physics.med-ph↗
arXiv2021

FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation

The RGB-Thermal (RGB-T) information for semantic segmentation has been extensively explored in recent years. However, most existing RGB-T semantic segmentation usually compromises spatial resolution to achieve real-time inference speed, which leads to poor performance. To better extract detail spatial information, we propose a two-stage Feature-Enhanced Attention Network (FEANet) for the RGB-T semantic segmentation task. Specifically, we introduce a Feature-Enhanced Attention Module (FEAM) to excavate and enhance multi-level features from both the channel and spatial views. Benefited from the proposed FEAM module, our FEANet can preserve the spatial information and shift more attention to high-resolution features from the fused RGB-T images. Extensive experiments on the urban scene dataset demonstrate that our FEANet outperforms other state-of-the-art (SOTA) RGB-T methods in terms of objective metrics and subjective visual comparison (+2.6% in global mAcc and +0.8% in global mIoU). For the 480 x 640 RGB-T test images, our FEANet can run with a real-time speed on an NVIDIA GeForce RTX 2080 Ti card.

cs.CV↗