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Jia Zhang

Publications and source records attributed to Jia Zhang.

At least 91 records · Page 5Linked to original sources
arXiv2024

Deep and low mass-ratio contact binaries and their third bodies

Deep and low mass-ratio contact binaries (DLMCBs) are believed to be in the final stage of their contact phase, potentially leading to the formation of fast-rotating single stars such as FK Com-type stars and blue stragglers, as well as luminous red novae. These systems serve as an excellent laboratory for studying stellar coalescence and merging processes. Our search for DLMCBs began in 2004 and has since identified a group of such systems. Together with that collected from the literature, more than 100 DLMCBs have been detected so far. Half of them have had their periods investigated based on O-C curves. Some have shown period increases, while others have exhibited period decreases. Among them, more than half DLMCBs have cyclic variations, suggesting the possibility of the existence of a third body orbiting around the DLMCBs. Furthermore, with more data obtained extending the span of the O-C curve, more cyclic variations could be detected. The high proportion of signs of the presence of third bodies makes them an essential factor to consider when studying the merger of contact binaries.

astro-ph.SR↗
arXiv2024

Temporal Graph Neural Network-Powered Paper Recommendation on Dynamic Citation Networks

Due to the rapid growth of scientific publications, identifying all related reference articles in the literature has become increasingly challenging yet highly demanding. Existing methods primarily assess candidate publications from a static perspective, focusing on the content of articles and their structural information, such as citation relationships. There is a lack of research regarding how to account for the evolving impact among papers on their embeddings. Toward this goal, this paper introduces a temporal dimension to paper recommendation strategies. The core idea is to continuously update a paper's embedding when new citation relationships appear, enhancing its relevance for future recommendations. Whenever a citation relationship is added to the literature upon the publication of a paper, the embeddings of the two related papers are updated through a Temporal Graph Neural Network (TGN). A learnable memory update module based on a Recurrent Neural Network (RNN) is utilized to study the evolution of the embedding of a paper in order to predict its reference impact in a future timestamp. Such a TGN-based model learns a pattern of how people's views of the paper may evolve, aiming to guide paper recommendations more precisely. Extensive experiments on an open citation network dataset, including 313,278 articles from https://paperswithcode.com/about PaperWithCode, have demonstrated the effectiveness of the proposed approach.

cs.IR↗
arXiv2024

Magnetostriction, piezomagnetism and domain nucleation in a kagome antiferromagnet

Whenever the elastic energy of a solid depends on magnetic field, there is a magnetostrictive response. Field-linear magnetostriction implies piezomagnetism and vice versa. Here, we show that Mn$_3$Sn, a non-collinear antiferromanget with Weyl nodes, hosts a large and almost perfectly linear magnetostriction even at room temperature. The longitudinal and transverse magnetostriction, with opposite signs and similar amplitude are restricted to the kagome planes and the out-of-plane response is negligibly small. By studying four different samples with different Mn:Sn ratios, we find a clear correlation between the linear magnetostriction, the spontaneous magnetization and the concentration of Sn vacancies. The recently reported piezomagnetic data fits in our picture. We show that linear magnetostriction and piezomagnetism are both driven by the field-induced in-plane twist of spins. A quantitative account of the experimental data requires the distortion of the spin texture by Sn vacancies. We find that the field-induced domain nucleation within the hysteresis loop corresponds to a phase transition. Within the hysteresis loop, a concomitant mesoscopic modulation of local strain and spin twist angles, leading to twisto-magnetic stripes, arises as a result of the competition between elastic and magnetic energies.

cond-mat.str-el↗
arXiv2024

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Computational simulation of chemical and biological systems using ab initio molecular dynamics has been a challenge over decades. Researchers have attempted to address the problem with machine learning and fragmentation-based methods. However, the two approaches fail to give a satisfactory description of long-range and many-body interactions, respectively. Inspired by fragmentation-based methods, we propose the Long-Short-Range Message-Passing (LSR-MP) framework as a generalization of the existing equivariant graph neural networks (EGNNs) with the intent to incorporate long-range interactions efficiently and effectively. We apply the LSR-MP framework to the recently proposed ViSNet and demonstrate the state-of-the-art results with up to 40% MAE reduction for molecules in MD22 and Chignolin datasets. Consistent improvements to various EGNNs will also be discussed to illustrate the general applicability and robustness of our LSR-MP framework. The code for our experiments and trained model weights could be found at https://github.com/liyy2/LSR-MP.

physics.chem-ph↗
arXiv2024

ISPO: An Integrated Ontology of Symptom Phenotypes for Semantic Integration of Traditional Chinese Medical Data

Symptom phenotypes are one of the key types of manifestations for diagnosis and treatment of various disease conditions. However, the diversity of symptom terminologies is one of the major obstacles hindering the analysis and knowledge sharing of various types of symptom-related medical data particularly in the fields of Traditional Chinese Medicine (TCM). Objective: This study aimed to construct an Integrated Ontology of symptom phenotypes (ISPO) to support the data mining of Chinese EMRs and real-world study in TCM field. Methods: To construct an integrated ontology of symptom phenotypes (ISPO), we manually annotated classical TCM textbooks and large-scale Chinese electronic medical records (EMRs) to collect symptom terms with support from a medical text annotation system. Furthermore, to facilitate the semantic interoperability between different terminologies, we incorporated public available biomedical vocabularies by manual mapping between Chinese terms and English terms with cross-references to source vocabularies. In addition, we evaluated the ISPO using independent clinical EMRs to provide a high-usable medical ontology for clinical data analysis. Results: By integrating 78,696 inpatient cases of EMRs, 5 biomedical vocabularies, 21 TCM books and dictionaries, ISPO provides 3,147 concepts, 23,475 terms, and 55,552 definition or contextual texts. Adhering to the taxonomical structure of the related anatomical systems of symptom phenotypes, ISPO provides 12 top-level categories and 79 middle-level sub-categories. The validation of data analysis showed the ISPO has a coverage rate of 95.35%, 98.53% and 92.66% for symptom terms with occurrence rates of 0.5% in additional three independent curated clinical datasets, which can demonstrate the significant value of ISPO in mapping clinical terms to ontologies.

cs.CL↗
arXiv2024

A corner-cube-feedback Faraday laser with 8 kHz linewidth

A single-mode Cs atom 852 nm Faraday laser based on the corner cube feedback is demonstrated, and termed as corner-cube-feedback Faraday laser. Using the corner-cube retroreflector as external cavity feedback element in Faraday laser, mechanical robustness can be greatly improved due to the precise reflection of the incident light beam back to its original direction. This Faraday laser can achieve laser oscillation at a large angle, which between the incident light and the optical axis of corner cube, ranging from +3° to -3°. The most probable linewidth is 8 kHz measured by heterodyne beating with two identical lasers. Moreover, its output frequency remains close to the Cs atomic Doppler-broadened transition line, even though the diode current changes from 55 mA to 155 mA and the diode working temperature varies from 11.8 to 37.2 degrees Celsius. The corner-cube-feedback Faraday laser with high mechanical robustness as well as narrow linewidth can be widely used in quantum precision measurement, such as atomic clocks, atomic gravimeters, and atomic magnetometers, etc.

physics.optics↗
arXiv2024

Acceleration without Disruption: DFT Software as a Service

Density functional theory (DFT) has been a cornerstone in computational chemistry, physics, and materials science for decades, benefiting from advancements in computational power and theoretical methods. This paper introduces a novel, cloud-native application, Accelerated DFT, which offers an order of magnitude acceleration in DFT simulations. By integrating state-of-the-art cloud infrastructure and redesigning algorithms for graphic processing units (GPUs), Accelerated DFT achieves high-speed calculations without sacrificing accuracy. It provides an accessible and scalable solution for the increasing demands of DFT calculations in scientific communities. The implementation details, examples, and benchmark results illustrate how Accelerated DFT can significantly expedite scientific discovery across various domains.

physics.chem-ph↗
arXiv2024

Crystal facet orientation and temperature dependence of charge and spin Hall effects in noncollinear antiferromagnet: A first-principles investigation

Noncollinear antiferromagnets (nc-AFMs) have attracted increasing research attention in spintronics due to their unique spin structures and fascinating charge and spin transport properties. By using first-principles calculations, we comprehensively investigate the charge and spin Hall effects in representative noncollinear antiferromagnet Mn3Pt. Our study reveals that the Hall effects in nc-AFMs are critically dependent on the crystal facet orientation and temperature. For (001) orientated Mn3Pt, each charge and spin Hall conductivity element is comprised of both time reversal odd (T-odd) and even (T-even) contribution, associated with longitudinal conductivity, which leads to sizable and highly anisotropic Hall conductivity. The temperature dependence of charge and spin Hall conductivity has been elucidated by considering both phonon and spin disorder scattering. The scaling relations between Hall conductivity and longitudinal conductivity have also been investigated. The existence of prominent spin Hall effect in nc-AFMs may generate spin current with Sz spin polarization, which is advantageous for field free switching of perpendicular magnetization. Our work may provide unambiguous understanding on the charge and spin transport in noncollinear antiferromagnets and pave their way for applications in antiferromagnetic spintronics.

cond-mat.mtrl-sci↗
arXiv2024

LordNet: An Efficient Neural Network for Learning to Solve Parametric Partial Differential Equations without Simulated Data

Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large amount of simulated data, which can be costly to collect. This can be avoided by learning physics from the physics-constrained loss, which we refer to it as mean squared residual (MSR) loss constructed by the discretized PDE. We investigate the physical information in the MSR loss, which we called long-range entanglements, and identify the challenge that the neural network requires the capacity to model the long-range entanglements in the spatial domain of the PDE, whose patterns vary in different PDEs. To tackle the challenge, we propose LordNet, a tunable and efficient neural network for modeling various entanglements. Inspired by the traditional solvers, LordNet models the long-range entanglements with a series of matrix multiplications, which can be seen as the low-rank approximation to the general fully-connected layers and extracts the dominant pattern with reduced computational cost. The experiments on solving Poisson's equation and (2D and 3D) Navier-Stokes equation demonstrate that the long-range entanglements from the MSR loss can be well modeled by the LordNet, yielding better accuracy and generalization ability than other neural networks. The results show that the Lordnet can be $40\times$ faster than traditional PDE solvers. In addition, LordNet outperforms other modern neural network architectures in accuracy and efficiency with the smallest parameter size.

cs.LG↗
arXiv2024

Learning Service Selection Decision Making Behaviors During Scientific Workflow Development

Increasingly, more software services have been published onto the Internet, making it a big challenge to recommend services in the process of a scientific workflow composition. In this paper, a novel context-aware approach is proposed to recommending next services in a workflow development process, through learning service representation and service selection decision making behaviors from workflow provenance. Inspired by natural language sentence generation, the composition process of a scientific workflow is formalized as a step-wise procedure within the context of the goal of workflow, and the problem of next service recommendation is mapped to next word prediction. Historical service dependencies are first extracted from scientific workflow provenance to build a knowledge graph. Service sequences are then generated based on diverse composition path generation strategies. Afterwards, the generated corpus of composition paths are leveraged to study previous decision making strategies. Such a trained goal-oriented next service prediction model will be used to recommend top K candidate services during workflow composition process. Extensive experiments on a real-word repository have demonstrated the effectiveness of this approach.

cs.SE↗
arXiv2024

CSS_J154915.7+375506: A low-mass-ratio marginal contact binary system with a hierarchical third body

We presented the multi-filter light curves of CSS_J154915.7+375506 inaugurally, which were observed by the 1.5 m AZT-22 telescope at Maidanak Astronomical Observatory. A low-resolution spectrum obtained by LAMOST reveals it is an A-type close binary. By analyzing the BVRI total-eclipse light curves, we are able to derive a reliable photometric solution for this system, which indicates that CSS_J154915.7+375506 is an extremely low-mass-ratio (q=0.138) marginal contact binary system. The location in the HR diagram shows that its secondary component with a much smaller mass is the more evolved one, indicating the mass ratio reversal occurred. The present secondary component had transferred a significant amount of mass to the present primary one. By the combination of a total of 20 times of minimum, we investigated its O-C curve. A periodic oscillation and a possible period decrease have been detected. As the period decreases, the system will evolve towards the contact phase. This makes CSS\_J154915.7+375506 a valuable case to study the formation scenario of contact binaries through mass reversal. The periodic oscillation suggested a third body with a minimal mass of $0.91\,M_{\odot}$, which is larger than that of the less massive component in the central binary. This implies that the secondary body was not replaced by the third body during early stellar interactions, indicating that it is a fossil system and retains its original dynamical information.

astro-ph.SR↗
arXiv2024

Tunable high-temperature tunneling magnetoresistance in all-van der Waals antiferromagnet/semiconductor/ferromagnet junctions

Magnetic tunnel junctions (MTJs) have been widely applied in spintronic devices for efficient spin detection through the imbalance of spin polarization at the Fermi level. The van der Waals (vdW) nature of two-dimensional (2D) magnets with atomic-scale flat surfaces and negligible surface roughness greatly facilitates the development of MTJs, yet is only restricted to ferromagnets. Here, we report A-type antiferromagnetism in 2D vdW single-crystal (Fe0.8Co0.2)3GaTe2 with TN~203 K in bulk and ~185 K in 9-nm nanosheets. The metallic nature and out-of-plane magnetic anisotropy make it a suitable candidate for MTJ electrodes. By constructing heterostructures based on (Fe0.8Co0.2)3GaTe2/WSe2/Fe3GaTe2, we obtain a large tunneling magnetoresistance (TMR) ratio of 180% at low temperature and the TMR retains at near-room temperature 280 K. Moreover, the TMR is tunable by the electric field down to 1 mV, implying the potential in energy-efficient spintronic devices. Our work provides new opportunities for 2D antiferromagnetic spintronics and quantum devices.

cond-mat.mtrl-sci↗
arXiv2024

Ab initio evaluation of the electron-ion energy transfer rate in a non-equilibrium warm dense metal

Electron-ion interactions play a central role for the energy relaxation processes and ultra-fast structure dynamics in laser-heated matter. The accurate prediction of the electron-ion energy exchange in a transient excited two-temperature situation still remains an open and challenging problem even though various theoretical efforts have been made. Here, following our recent work [Zhang et al., Materials 15, 1902 (2022)], we take an approach combining finite temperature DFT-MD and corresponding density functional perturbation theory to evaluate the electron-ion coupling factors in the warm dense regime. The use of density-temperature-dependent Eliashberg functions and electron density of states are highlighted. Good agreement of our DFT based results can be observed with recent data by Simoni et al. [Phys. Rev. Lett. 122, 205001 (2019)]. For a proof of concept, we use our newly obtained energy transfer rates to discuss temperature equilibration in warm dense aluminum.

cond-mat.other↗
arXiv2024

Thermal effect in hot QCD matter in strong magnetic fields

The quasiparticle model is improved by the free magnetic contribution to investigated the QCD matter in a strong magnetic field. The temperature-dependent bag function is determined by the thermodynamic consistency to represent the difference in energy density between physical vacuum and lowest state of QCD. It is found that the positive bag function vanishes at high temperature indicating the deconfinement. The rapid decrease of the bag function in stronger magnetic fields reveals the so-called inverse magnetic catalysis. The interaction measure at high temperature remains so large that the usual Stefan-Boltzmann limit can not be reached. We suggest a limit $|q_iB_m|T^2/4$ for each landau level pressure. Finally, it is demonstrated that the positive magnetization modified by the bag function and free magnetic contribution indicates the paramagnetic characteristic of QCD matter.

hep-ph↗
arXiv2023

Deep3DSketch: 3D modeling from Free-hand Sketches with View- and Structural-Aware Adversarial Training

This work aims to investigate the problem of 3D modeling using single free-hand sketches, which is one of the most natural ways we humans express ideas. Although sketch-based 3D modeling can drastically make the 3D modeling process more accessible, the sparsity and ambiguity of sketches bring significant challenges for creating high-fidelity 3D models that reflect the creators' ideas. In this work, we propose a view- and structural-aware deep learning approach, \textit{Deep3DSketch}, which tackles the ambiguity and fully uses sparse information of sketches, emphasizing the structural information. Specifically, we introduced random pose sampling on both 3D shapes and 2D silhouettes, and an adversarial training scheme with an effective progressive discriminator to facilitate learning of the shape structures. Extensive experiments demonstrated the effectiveness of our approach, which outperforms existing methods -- with state-of-the-art (SOTA) performance on both synthetic and real datasets.

cs.MM↗
arXiv2023

The Nearest Neutron Star Candidate in a Binary Revealed by Optical Time-domain Surveys

The near-Earth (within $\sim 100$ pc) supernova explosions in the past several million years can cause the global deposition of radioactive elements (e.g., $^{60}$Fe) on Earth. The remnants of such supernovae are too old to be easily identified. It is therefore of great interest to search for million-year-old near-Earth neutron stars or black holes, the products of supernovae. However, neutron stars and black holes are challenging to find even in our Solar neighbourhood if they are not radio pulsars or X-ray/$γ$-ray emitters. Here we report the discovery of one of the nearest ($127.7 \pm 0.3$ pc) neutron star candidates in a detached single-lined spectroscopic binary LAMOST J235456.73+335625.9 (hereafter J2354). Utilizing the time-resolved ground-based spectroscopy and space photometry, we find that J2354 hosts an unseen compact object with $M_{\mathrm{inv}}$ being $1.4 \sim 1.6\ M_{\odot}$. The follow-up Swift ultraviolet (UV) and X-ray observations suggest that the UV and X-ray emission is produced by the visible star rather than the compact object. Hence, J2354 probably harbours a neutron star rather than a hot ultramassive white dwarf. Two-hour exceptionally sensitive radio follow-up observations with Five-hundred-meter Aperture Spherical radio Telescope fail to reveal any pulsating radio signals at the $6σ$ flux upper limit of $12.5\ μ\mathrm{Jy}$. Therefore, the neutron star candidate in J2354 can only be revealed via our time-resolved observations. Interestingly, the distance between J2354 and our Earth can be as close as $\sim 50$ pc around $2.5$ Myrs ago, as revealed by the Gaia kinematics. Our discovery demonstrates a promising way to unveil the hidden near-Earth neutron stars in binaries by exploring the optical time domain, thereby facilitating understanding of the metal-enrichment history in our Solar neighbourhood.

astro-ph.HE↗
arXiv2023

Crystal facet orientated Altermagnets for detecting ferromagnetic and antiferromagnetic states by giant tunneling magnetoresistance effect

Emerging altermagnetic materials with vanishing net magnetizations and unique band structures have been envisioned as an ideal electrode to design antiferromagnetic tunnel junctions. Their momentum-resolved spin splitting in band structures defines a spin-polarized Fermi surface, which allows altermagnetic materials to polarize current as a ferromagnet, when the current flows along specific directions relevant to their altermagnetism. Here, we design an Altermagnet/Insulator barrier/Ferromagnet junction, renamed as altermagnetic tunnel junction (ATMTJ), using RuO$_2$/TiO$_2$/CrO$_2$ as a prototype. Through first-principles calculations, we investigate the tunneling properties of the ATMTJ along the [001] and [110] directions, which shows that the tunneling magnetoresistance (TMR) is almost zero when the current flows along the [001] direction, while it can reach as high as 6100\% with current flows along the [110] direction. The spin-resolved conduction channels of the altermagnetic RuO$_2$ electrode are found responsible for this momentum-dependent (or transport-direction-dependent) TMR effect. Furthermore, this ATMTJ can also be used to readout the Néel vector of the altermagnetic electrode RuO$_2$. Our work promotes the understanding toward the altermagnetic materials and provides an alternative way to design magnetic tunnel junctions with ultrahigh TMR ratios and robustness of the altermagnetic electrode against external disturbance, which broadens the application avenue for antiferromagnetic spintronic devices.

cond-mat.mtrl-sci↗