arXiv subjects

Yang Sun

Publications and source records attributed to Yang Sun.

At least 145 records · Page 8Linked to original sources

arXiv2023

Prediction of superconductivity in metallic boron-carbon compounds from 0 to 100 GPa by high-throughput screening

Boron carbon compounds have been shown to have feasible superconductivity. In our earlier paper [Zheng et al., Phys. Rev. B 107, 014508 (2023)], we identified a new conventional superconductor of LiB3C at 100 GPa. Here, we aim to extend the investigation of possible superconductivity in this structural framework by replacing Li atoms with 27 different cations under pressures ranging from 0 to 100 GPa. Using the high-throughput screening method of zone-center electron-phonon interaction, we find that ternary compounds like CaB3C, SrB3C, TiB3C, and VB3C are promising candidates for superconductivity. The consecutive calculations using the full Brillouin zone confirm that they have Tc < 31 K at moderate pressures. Our study demonstrates that fast screening of superconductivity by calculating zone-center electron-phonon coupling strength is an effective strategy for high-throughput identification of new superconductors.

cond-mat.supr-con↗

arXiv2023

Prediction of Van Hove singularity systems in ternary borides

A computational search for stable structures among both $α$ and $β$ phases of ternary ATB4 borides (A= Mg, Ca, Sr, Ba, Al, Ga, and Zn, T is 3d or 4d transition elements) has been performed. We found that $α$-ATB4 compounds with A=Mg, Ca, Al, and T=V, Cr, Mn, Fe, Ni, and Co form a family of structurally stable or almost stable materials. These systems are metallic in non-magnetic states and characterized by the formation of the localized molecular-like state of 3d transition metal atom dimers, which leads to the appearance of numerous Van Hove singularities (VHS) in the electronic spectrum. The closeness of these VHS to the Fermi level can be easily tuned by electron doping. For the atoms in the middle of the 3d row (Cr, Mn, and Fe), these VHS led to magnetic instabilities and new magnetic ground states with a weakly metallic or semiconducting nature. The magnetic ground states in these systems appear as an analog of the spin glass state. Experimental attempts to produce MgFeB4 and associated challenges are discussed, and promising directions for further synthetic studies are formulated.

cond-mat.mtrl-sci↗

arXiv2023

Maximizing the performance for microcomb based microwave photonic transversal signal processors

Microwave photonic (MWP) transversal signal processors offer a compelling solution for realizing versatile high-speed information processing by combining the advantages of reconfigurable electrical digital signal processing and high-bandwidth photonic processing. With the capability of generating a number of discrete wavelengths from micro-scale resonators, optical microcombs are powerful multi-wavelength sources for implementing MWP transversal signal processors with significantly reduced size, power consumption, and complexity. By using microcomb-based MWP transversal signal processors, a diverse range of signal processing functions have been demonstrated recently. In this paper, we provide a detailed analysis for the processing inaccuracy that is induced by the imperfect response of experimental components. First, we investigate the errors arising from different sources including imperfections in the microcombs, the chirp of electro-optic modulators, chromatic dispersion of the dispersive module, shaping errors of the optical spectral shapers, and noise of the photodetector. Next, we provide a global picture quantifying the impact of different error sources on the overall system performance. Finally, we introduce feedback control to compensate the errors caused by experimental imperfections and achieve significantly improved accuracy. These results provide a guide for optimizing the accuracy of microcomb-based MWP transversal signal processors.

eess.SP↗

arXiv2023

Metallization and Spin Fluctuations in Cu-doped Lead Apatite

An electronic structure and magnetic properties analysis of the recently proposed Cu-doped lead apatite is performed. We show that electronic structures of differently Cu-substituted structures are characterized by localized molecular Cu-O bands at or near the Fermi level. The Cu substitutions can happen at both Pb1 and Pb2 sites, leading to metallic and semiconducting states differently. The electronic states in these bands are highly unstable magnetically and form clusters of rigidly ferromagnetically coupled magnetic moments on Cu and neighboring oxygen atoms with a total moment of about 1 $μ_B$. The ground state of uniformly Cu-doped lead apatite appears to be magnetic and semiconducting. The non-uniform distribution of two Cu atoms at the nearest Pb2 sites leads to an antiferromagnetic semiconducting state with formation energy close to uniformly distributed Cu configurations. The inclusion of quantum spin fluctuations confirms the stability of magnetic Cu-O clusters. Our calculations revealed the absence of the long-range magnetic order between uniformly distributed Cu-O clusters, creating the spin glass type of system.

cond-mat.supr-con↗

arXiv2023

Thermoelastic properties of bridgmanite using Deep Potential Molecular Dynamics

MgSiO_3-perovskite (MgPv) plays a crucial role in the Earth's lower mantle. This study combines deep-learning potential (DP) with density functional theory (DFT) to investigate the structural and elastic properties of MgPv under lower mantle conditions. To simulate complex systems, we developed a series of potentials capable of faithfully reproducing DFT calculations using different functionals, such as LDA, PBE, PBEsol, and SCAN meta-GGA functionals. The obtained predictions exhibit remarkable reliability and consistency, closely resembling experimental measurements. Our results highlight the superior performance of the DP-SCAN and DP-LDA in accurately predicting high-temperature equations of states and elastic properties. This hybrid computational approach offers a solution to the accuracy-efficiency dilemma in obtaining precise elastic properties at high pressure and temperature conditions for minerals like MgPv, which opens a new way to study the Earth's interior state and related processes.

physics.geo-ph↗

arXiv2023

Effect of nitrogen doping and pressure on the stability of LuH$_3$

The report on the near-ambient superconductivity in a nitrogen-doped lutetium hydride has stimulated great interest in this material (Dasenbrock-Gammon et al. 2023). While its superconductivity is still a subject of debate, the structure of the claimed cubic phase remains uncertain. In this work, we study the effect of nitrogen doping and pressure on the energetic and dynamic stability of cubic LuH3. Our findings indicate that both pressure and nitrogen doping can enhance the stability of the cubic LuH3 phase. We propose a Lu8H21N structure that exhibits stable phonon, reasonable thermodynamic stability at 1 GPa, and a similar XRD pattern to the experimental data. However, we do not observe electron-phonon coupling in the zone-center phonon modes of these crystal structures.

cond-mat.supr-con↗

arXiv2023

Structural prediction of Fe-Mg-O compounds at Super-Earth's pressures

Terrestrial exoplanets are of great interest for being simultaneously similar to and different from Earth. Their compositions are likely comparable to those of solar-terrestrial objects, but their internal pressures and temperatures can vary significantly with their masses/sizes. The most abundant non-volatile elements are O, Mg, Si, Fe, Al, and Ca, and there has been much recent progress in understanding the nature of magnesium silicates up to and beyond ~3 TPa. However, a critical element, Fe, has yet to be systematically included in materials discovery studies of potential terrestrial planet-forming phases at ultra-high pressures. Here, using the adaptive genetic algorithm (AGA) crystal structure prediction method, we predict several unreported stable crystalline phases in the binary Fe-Mg and ternary Fe-Mg-O systems up to pressures of 3 TPa. The analysis of the local packing motifs of the low-enthalpy Fe-Mg-O phases reveals that the Fe-Mg-O system favors a BCC motif under ultra-high pressures regardless of chemical composition. Besides, oxygen enrichment is conducive to lowering the enthalpies of the Fe-Mg-O phases. Our results extend the current knowledge of structural information of the Fe-Mg-O system to exoplanet pressures.

physics.geo-ph↗

arXiv2023

Ab initio melting temperatures of bcc and hcp iron under the Earth's inner core condition

There has been a long debate on the stable phase of iron under the Earth's inner core conditions. Because of the solid-liquid coexistence at the inner core boundary, the thermodynamic stability of solid phases directly relates to their melting temperatures, which remains considerable uncertainty. In the present study, we utilized a semi-empirical potential fitted to high-temperature ab initio data to perform a thermodynamic integration from classical systems described by this potential to ab initio systems. This method provides a smooth path for thermodynamic integration and significantly reduces the uncertainty caused by the finite-size effect. Our results suggest the hcp phase is the stable phase of pure iron under the inner core conditions, while the free energy difference between the hcp and bcc phases is tiny, on the order of 10s meV/atom near the melting temperature.

cond-mat.mtrl-sci↗

arXiv2023

Structure and dynamics of Fe90Si3O7 liquids close to Earth's liquid core conditions

Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of Fe90Si3O7 liquid close to the Earth's liquid core conditions. The simulation results reveal that the short-range structural order (SRO) in the Fe90Si3O7 liquid is very strong. About 80% of the atoms are arranged in crystalline-like SRO motifs. In particular, ~70% of Fe-centered clusters can be classified as either hexagonal-close-pack (HCP/HCP-like) or icosahedral (ICO/ICO-like) SRO motifs. The SRO clusters centered on Fe, Si, or O atoms are strongly intermixed and homogenously distributed throughout the liquid. The atomic structure of the liquid and the fractions of dominant SRO clusters are not sensitive to pressure/temperature used in the simulations except that the SRO of the O-centered clusters is enhanced close to inner core pressures. The O diffusion coefficient is about 2-3 times larger than the Fe and Si ions and increases more rapidly in the deeper core regions.

cond-mat.mtrl-sci↗

arXiv2023

Applications of integrated optical microcombs

Optical microcombs represent a new paradigm for generating laser frequency combs based on compact chip-scale devices, which have underpinned many modern technological advances for both fundamental science and industrial applications. Along with the surge in activity related to optical micro-combs in the past decade, their applications have also experienced rapid progress, not only in traditional fields such as frequency synthesis, signal processing, and optical communications, but also in new interdisciplinary fields spanning the frontiers of light detection and ranging (LiDAR), astronomical detection, neuromorphic computing, and quantum optics. This paper reviews the applications of optical microcombs. First, an overview of the devices and methods for generating optical microcombs is provided, which are categorized into material platforms, device architectures, soliton classes, and driving mechanisms. Second, the broad applications of optical microcombs are systematically reviewed, which are categorized into microwave photonics, optical communications, precision measurements, neuromorphic computing, and quantum optics. Finally, the current challenges and future perspectives are discussed.

physics.optics↗

arXiv2023

GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network

Identifying causal relations among multi-variate time series is one of the most important elements towards understanding the complex mechanisms underlying the dynamic system. It provides critical tools for forecasting, simulations and interventions in science and business analytics. In this paper, we proposed a graph neural network approach with score-based method aiming at learning a sparse DAG that captures the causal dependencies in a discretized time temporal graph. We demonstrate methods with graph neural network significantly outperformed other state-of-the-art methods with dynamic bayesian networking inference. In addition, from the experiments, the structural causal model can be more accurate than a linear SCM discovered by the methods such as Notears.

cs.LG↗

arXiv2022

Atlas of Nuclear Isomers -- Second Edition

We present an updated version of the 2015-Atlas of Nuclear Isomers \cite{jain2015}, compiling and evaluating experimental data for the isomers with half-life $\ge 10$ $\it{ns}$, together with their spectroscopic properties such as excitation-energies, half-lives, decay modes, spins and parities, energies and multipolarities of isomeric transitions, along with the relevant original references in literature. The current version of Atlas presents many re-evaluated half-lives as compared to the 2015 edition, where values were referred to Nuclear Data Sheets publications, when no new data existed. The ENSDF database \cite{Ensdf}, together with the XUNDL \cite{Xundl} and the NUBASE2020 \cite{Kondev2021} databases have been consulted for completeness, yet, data from original papers from journals were considered in the present evaluation, and the NSR bibliographic database \cite{Nsr} has been searched to ensure that this work is as complete and current as possible. Several useful systematic features of nuclear isomers covered in this Atlas have been discussed. Literature cutoff date for the extraction of data is October 31, 2022.

nucl-th↗

arXiv2022

Model-Based and Graph-Based Priors for Group Testing

The goal of the group testing problem is to identify a set of defective items within a larger set of items, using suitably-designed tests whose outcomes indicate whether any defective item is present. In this paper, we study how the number of tests can be significantly decreased by leveraging the structural dependencies between the items, i.e., by incorporating prior information. To do so, we pursue two different perspectives: (i) As a generalization of the uniform combinatorial prior, we consider the case that the defective set is uniform over a \emph{subset} of all possible sets of a given size, and study how this impacts the information-theoretic limits on the number of tests for approximate recovery; (ii) As a generalization of the i.i.d.~prior, we introduce a new class of priors based on the Ising model, where the associated graph represents interactions between items. We show that this naturally leads to an Integer Quadratic Program decoder, which can be converted to an Integer Linear Program and/or relaxed to a non-integer variant for improved computational complexity, while maintaining strong empirical recovery performance.

cs.IT↗

arXiv2022

PBE-GGA Predicts the B8$\leftrightarrow$B2 Phase Boundary of FeO at Earth's Core Conditions

FeO is a crucial phase of the Earth's core, and its thermodynamic properties are essential to developing more accurate core models. It is also a notorious correlated insulator in the NaCl-type (B1) phase at ambient conditions. It undergoes two polymorphic transitions at 300 K before it becomes metallic in the NiAs-type (B8) structure at $\sim$100 GPa. Although its phase diagram is not fully mapped, it is well established that the B8 phase transforms to the CsCl-type (B2) phase at core pressures and temperatures. Here we report a successful \textit{ab initio} calculation of the B8$\leftrightarrow$B2 phase boundary in FeO at Earth's core pressures. We show that fully anharmonic free energies computed with the PBE-GGA + Mermin functional reproduce the experimental phase boundary within uncertainties at $P > 240$ GPa, including the largely negative Clapeyron slope of $-52 \pm 5$ MPa/K. This study validates the applicability of a standard DFT functional to FeO under Earth's core conditions and demonstrates the theoretical framework that enables complex predictive studies of this region.

cond-mat.mtrl-sci↗

arXiv2022

Infrared Excess of a Large OB Star Sample

The infrared excess from OB stars are commonly considered as contributions from ionized stellar wind or circumstellar dust. With the newly published LAMOST-OB catalog and GOSSS data, this work steps further on understanding the infrared excess of OB stars. Based on a forward modeling approach comparing the spectral slope of observational Spectral Energy Distributions (SED) and photospheric models, 1147 stars are found to have infrared excess from 7818 stars with good-quality photometric data. After removing the objects in the sightline of dark clouds, 532 ($\sim7\%$) B-type stars and 118 ($\sim23\%$) O-type stars are identified to be true OB stars with circumstellar infrared excess emission. The ionized stellar wind model and the circumstellar dust model are adopted to explain the infrared excess, and Bayes Factors are computed to quantitatively compare the two. It is shown that the infrared excess can be accounted for by the stellar wind for about 65\% cases in which 33\% by free-free emission and 32\% by synchrotron radiation. Other 30\% sources could have and 4\% should have a dust component or other mechanisms to explain the sharply increase flux at $λ> 10μ$m. The parameters of dust model indicate a large-scale circumstellar halo structure which implies the origin of the dust from the birthplace of the OB stars. A statistical study suggests that the proportion with infrared excess in OB stars increases with stellar effective temperature and luminosity, and that there is no systematic change of the mechanism for infrared emission with stellar parameters.

astro-ph.SR↗

arXiv2022

TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge

This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER). In this challenge, we explore three kinds of typical speaker diarization systems, which are spectral clustering(SC) based diarization, target-speaker voice activity detection(TS-VAD) and end-to-end neural diarization(EEND) respectively. Our major findings are summarized as follows. First, the SC approach is more favored over the other two approaches under the new CDER metric. Second, tuning on hyperparameters is essential to CDER for all three types of speaker diarization systems. Specifically, CDER becomes smaller when the length of sub-segments setting longer. Finally, multi-system fusion through DOVER-LAP will worsen the CDER metric on the challenge data. Our submitted SC system eventually ranks the third place in the challenge.

cs.SD↗

arXiv2022

LawBreaker: An Approach for Specifying Traffic Laws and Fuzzing Autonomous Vehicles

Autonomous driving systems (ADSs) must be tested thoroughly before they can be deployed in autonomous vehicles. High-fidelity simulators allow them to be tested against diverse scenarios, including those that are difficult to recreate in real-world testing grounds. While previous approaches have shown that test cases can be generated automatically, they tend to focus on weak oracles (e.g. reaching the destination without collisions) without assessing whether the journey itself was undertaken safely and satisfied the law. In this work, we propose LawBreaker, an automated framework for testing ADSs against real-world traffic laws, which is designed to be compatible with different scenario description languages. LawBreaker provides a rich driver-oriented specification language for describing traffic laws, and a fuzzing engine that searches for different ways of violating them by maximising specification coverage. To evaluate our approach, we implemented it for Apollo+LGSVL and specified the traffic laws of China. LawBreaker was able to find 14 violations of these laws, including 173 test cases that caused accidents.

cs.SE↗

arXiv2022

Neuromorphic computing using wavelength-division multiplexing

Optical neural networks (ONNs), or optical neuromorphic hardware accelerators, have the potential to dramatically enhance the computing power and energy efficiency of mainstream electronic processors, due to their ultralarge bandwidths of up to 10s of terahertz together with their analog architecture that avoids the need for reading and writing data back and forth. Different multiplexing techniques have been employed to demonstrate ONNs, amongst which wavelength division multiplexing (WDM) techniques make sufficient use of the unique advantages of optics in terms of broad bandwidths. Here, we review recent advances in WDM based ONNs, focusing on methods that use integrated microcombs to implement ONNs. We present results for human image processing using an optical convolution accelerator operating at 11 Tera operations per second. The open challenges and limitations of ONNs that need to be addressed for future applications are also discussed.

physics.optics↗