arXiv subjects

Gang Chen

Publications and source records attributed to Gang Chen.

At least 343 records · Page 19Linked to original sources

arXiv2021

Anomalous Hall signatures of nonsymmorphic nodal lines in doped chromium chalcospinel CuCr$_2$Se$_4$

An emerging phase of matter among the class of topological materials is nodal line semimetal, possessing symmetry-protected one-dimensional gapless lines at the (or close to) the Fermi level in $k$-space. When the $k$-dispersion of the nodal line is weak, van Hove singularities generated by the almost flat nodal lines may be prone to instabilities introduced by additional perturbations such as spin-orbit coupling or magnetism. Here, we study Cr-based ferromagnetic chalcospinel compound CuCr$_2$Se$_4$ (CCS) via first-principles electronic structure methods and reveal the true origin of its dissipationless anomalous Hall conductivity, which was not well understood previously. We find that CCS hosts nodal lines protected by nonsymmorphic symmetries, located in the vicinity of Fermi level, and that such nodal lines are the origin of the previously observed distinct behavior of the anomalous Hall signature in the presence of electron doping. The splitting of nodal line via spin-orbit coupling produces a large Berry curvature, which leads to a significant response in anomalous Hall conductivity. Upon electron doping via chemical substitution or gating, or rotation of magnetization via external magnetic field, steep change of anomalous Hall behavior occurs, which makes CCS a promising compound for low energy spintronics applications.

cond-mat.mtrl-sci↗

arXiv2021

The In-Flight Realtime Trigger and Localization Software of GECAM

Realtime trigger and localization of bursts are the key functions of GECAM, which is an all-sky gamma-ray monitor launched in Dec 10, 2020. We developed a multifunctional trigger and localization software operating on the CPU of the GECAM electronic box (EBOX). This onboard software has the following features: high trigger efficiency for real celestial bursts with a suppression of false triggers caused by charged particle bursts and background fluctuation, dedicated localization algorithm optimized for short and long bursts respetively, short time latency of the trigger information which is downlinked throught the BeiDou satellite navigation System (BDS). This paper presents the detailed design and deveopment of this trigger and localization software system of GECAM, including the main functions, general design, workflow and algorithms, as well as the verification and demonstration of this software, including the on-ground trigger tests with simulated gamma-ray bursts made by a dedicated X-ray tube and the in-flight performance to real gamma-ray bursts and magnetar bursts.

astro-ph.IM↗

arXiv2021

Donnan Equilibrium Revisited: Coupling between Ion Concentrations, Osmotic Pressure, and Donnan Potential

This paper discusses the little-known fact that Donnan's equilibrium criteria established over 100 years ago neglected the coupling between ion concentrations and the osmotic pressure. Such coupling can be treated based on general thermodynamic considerations including the solvent equilibrium, leading to a membrane potential that consists of not only the classical Donnan potential term but also an additional term due to the osmotic pressure, and the existence of a membrane potential even when the impermeable species are not charged. This coupled treatment is in conflict with the well-established Poisson-Boltzmann equation and Nernst-Planck equation, but is consistent with the extension of these equations including the solvent effects by Freise and Schlogl, enables us to view the electrical double layer equilibrium as Donnan equilibrium.

physics.chem-ph↗

arXiv2021

Real-time intelligent big data processing: technology, platform, and applications

Human beings keep exploring the physical space using information means. Only recently, with the rapid development of information technologies and the increasing accumulation of data, human beings can learn more about the unknown world with data-driven methods. Given data timeliness, there is a growing awareness of the importance of real-time data. There are two categories of technologies accounting for data processing: batching big data and streaming processing, which have not been integrated well. Thus, we propose an innovative incremental processing technology named after Stream Cube to process both big data and stream data. Also, we implement a real-time intelligent data processing system, which is based on real-time acquisition, real-time processing, real-time analysis, and real-time decision-making. The real-time intelligent data processing technology system is equipped with a batching big data platform, data analysis tools, and machine learning models. Based on our applications and analysis, the real-time intelligent data processing system is a crucial solution to the problems of the national society and economy.

cs.DC↗

arXiv2021

Green's Functions of the Boltzmann Transport Equation with the Full Scattering Matrix for Phonon Nanoscale Transport beyond the Relaxation Time Approximation

The phonon Boltzmann transport equation (BTE) has been widely utilized to study thermal transport in solids. While for a number of materials the exact solution to the BTE has been obtained for a uniform heat flow, problems arising in micro/nanoscale heat transport have been analyzed within the relaxation time approximation (RTA). Since the RTA breaks down at temperatures low compared to the Debye temperature, this approximation prevents the study of an important class of high Debye temperature materials such as diamond, graphite, graphene and some other 2D materials. We present a full scattering matrix formalism that goes beyond the RTA approximation and obtain a Green's function solution for the linearized BTE, which leads to an explicit expression for the phonon distribution and temperature field produced by an arbitrary spatio-temporal distribution of heat sources in an unbounded medium. The presented formalism is capable of describing a wide range of phenomena, from heat dissipation by nanoscale hot spots to the propagation of second sound waves. We provide numerical results for graphene for a spatially sinusoidal heating profile and discuss the importance of using the full scattering matrix compared to the RTA.

cond-mat.mes-hall↗

arXiv2021

Agile Formation Control of Drone Flocking Enhanced with Active Vision-based Relative Localization

The vision-based relative localization can provide effective feedback for the cooperation of aerial swarm and has been widely investigated in previous works. However, the limited field of view (FOV) inherently restricts its performance. To cope with this issue, this letter proposes a novel distributed active vision-based relative localization framework and apply it to formation control in aerial swarms. Inspired by bird flocks in nature, we devise graph-based attention planning (GAP) to improve the observation quality of the active vision in the swarm. Then active detection results are fused with onboard measurements from Ultra-WideBand (UWB) and visual-inertial odometry (VIO) to obtain real-time relative positions, which further improve the formation control performance of the swarm. Simulations and experiments demonstrate that the proposed active vision system outperforms the fixed vision system in terms of estimation and formation accuracy.

cs.RO↗

arXiv2021

Where to Look: A Unified Attention Model for Visual Recognition with Reinforcement Learning

The idea of using the recurrent neural network for visual attention has gained popularity in computer vision community. Although the recurrent attention model (RAM) leverages the glimpses with more large patch size to increasing its scope, it may result in high variance and instability. For example, we need the Gaussian policy with high variance to explore object of interests in a large image, which may cause randomized search and unstable learning. In this paper, we propose to unify the top-down and bottom-up attention together for recurrent visual attention. Our model exploits the image pyramids and Q-learning to select regions of interests in the top-down attention mechanism, which in turn to guide the policy search in the bottom-up approach. In addition, we add another two constraints over the bottom-up recurrent neural networks for better exploration. We train our model in an end-to-end reinforcement learning framework, and evaluate our method on visual classification tasks. The experimental results outperform convolutional neural networks (CNNs) baseline and the bottom-up recurrent attention models on visual classification tasks.

cs.CV↗

arXiv2021

A study on the exotic state ${P_{c}(4312),P_{c}(4440),P_{c}(4457)}$ in $pp$ collisions at $\sqrt{s}=7$, 13 TeV

The exotic resonant state $P_{c}^{\pm}(4312)$, $P_{c}^{\pm}(4440)$, and $P_{c}^{\pm}(4457)$ are studied by using the dynamically constrained phase space coalescence DCPC model and PACIAE model in $pp$ collisions at $\sqrt{s}=7$, 13TeV, respectively. We consider exotic state $P_{c}^{\pm}(4312)$, $P_{c}^{\pm}(4440)$ and $P_{c}^{\pm}(4457)$ to be three kinds of possible structures, i.e. pentaquark state, the nucleus-like state, and the molecular state based on $P_c^\pm \to J/ψ{p}{(\bar p)}$ bound state. The yield, the transverse momentum distribution and the rapidity distribution of $P_{c}$ with three different structures are all predicted. The results indicated that the yield is on the order of $10^{-6}$, which might provide reference for experimental research.

hep-ph↗

arXiv2021

Revealing the three-component structure of water with principal component analysis (PCA) on X-ray spectrum

Combining the principal component analysis (PCA) of X-ray spectrum with MD simulations, we experimentally reveal the existence of three basic components in water. These components exhibit distinct structures, densities, and temperature dependencies. Among the three, two major components correspond to the low-density liquid (LDL) and the high-density liquid (HDL) predicted by the two-component model, and the third component exhibits a unique 5-hydrogen-bond configuration with an ultra-high local density. As the temperature increases, the LDL component decreases and the HDL component increases, while the third component varies non-monotonically with a peak around 20 $^{\circ}$C to 30 $^{\circ}$C. The 3D structure of the third component is further illustrated as the uniform distribution of five hydrogen-bonded neighbors on a spherical surface. Our study reveals experimental evidence for water's unique three-component structure, which provides a fundamental basis for understanding water's special properties and anomalies.

cond-mat.soft↗

arXiv2021

Investigation of exotic state X(3872) in $pp$ collisions at $\sqrt{s}=$7 and 13 TeV

We have used the dynamically constrained phase space coalescence model to study the production of the exotic state $X(3872)$ based on the hadronic final states generated by the parton and hadron cascade model (PACIAE) with $|y|<1$ and $p_T < 15.5$ GeV/c in $pp$ collisions at $\sqrt{s}=7$ and 13 TeV, respectively. Here the $X(3872)$ is assumed to consist of bound state $D\bar {D^*}$, which can form three possible structures for the tetraquark state, the nucleus-like state, and the molecular state. The yields of three different structures $X(3872)$ were predicted. The transverse momentum distribution and the rapidity distribution of three different structures $X(3872)$ are also presented. Sizable difference can be found in the transverse momentum and rapidity distributions for the three different $X(3872)$ structures.

hep-ph↗

arXiv2021

Sharp $L^\infty$ estimates of HDG methods for Poisson equation II: 3D

In [SIAM J. Numer. Anal., 59 (2), 720-745], we proved quasi-optimal $L^\infty$ estimates (up to logarithmic factors) for the solution of Poisson's equation by a hybridizable discontinuous Galerkin (HDG) method. However, the estimates only work in 2D. In this paper, we obtain sharp (without logarithmic factors) $L^\infty$ estimates for the HDG method in both 2D and 3D. Numerical experiments are presented to confirm our theoretical result.

math.NA↗

arXiv2021

Classical gravitational scattering from a gauge-invariant double copy

We propose a method to compute the scattering angle for classical black hole scattering directly from two massive particle irreducible diagrams in a heavy-mass effective field theory approach to general relativity, without the need of subtracting iteration terms. The amplitudes in this effective theory are constructed using a recently proposed novel colour-kinematic/double copy for tree-level two-scalar, multi-graviton amplitudes, where the BCJ numerators are gauge invariant and local with respect to the massless gravitons. These tree amplitudes, together with graviton tree amplitudes, enter the construction of the required $D$-dimensional loop integrands and allow for a direct extraction of contributions relevant for classical physics. In particular the soft/heavy-mass expansions of full integrands is circumvented, and all iterating contributions can be dropped from the get go. We use this method to compute the scattering angle up to third post-Minkowskian order in four dimensions, including radiation reaction contributions, also providing the expression of the corresponding integrand in $D$ dimensions.

hep-th↗

arXiv2021

Fusion categories containing a fusion subcategory with maximal rank

In this paper, we study fusion categories which contain a proper fusion subcategory with maximal rank. They can be viewed as generalizations of near-group fusion categories. We first prove that they admit spherical structure. We then classify those which are non-degenerate or symmetric. Finally, we classify such fusion categories of rank 4.

math.QA↗

arXiv2021

Field-Tuned Quantum Effects in a Triangular-Lattice Ising Magnet

We report thermodynamic and neutron scattering measurements of the triangular-lattice quantum Ising magnet TmMgGaO 4 in longitudinal magnetic fields. Our experiments reveal a quasi-plateau state induced by quantum fluctuations. This state exhibits an unconventional non-monotonic field and temperature dependence of the magnetic order and excitation gap. In the high field regime where the quantum fluctuations are largely suppressed, we observed a disordered state with coherent magnon-like excitations despite the suppression of the spin excitation intensity. Through detailed semi-classical calculations, we are able to understand these behaviors quantitatively from the subtle competition between quantum fluctuations and frustrated Ising interactions.

cond-mat.str-el↗

arXiv2021

Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal

Deep learning models usually require a large amount of labeled data to achieve satisfactory performance. In multimedia analysis, domain adaptation studies the problem of cross-domain knowledge transfer from a label rich source domain to a label scarce target domain, thus potentially alleviates the annotation requirement for deep learning models. However, we find that contemporary domain adaptation methods for cross-domain image understanding perform poorly when source domain is noisy. Weakly Supervised Domain Adaptation (WSDA) studies the domain adaptation problem under the scenario where source data can be noisy. Prior methods on WSDA remove noisy source data and align the marginal distribution across domains without considering the fine-grained semantic structure in the embedding space, which have the problem of class misalignment, e.g., features of cats in the target domain might be mapped near features of dogs in the source domain. In this paper, we propose a novel method, termed Noise Tolerant Domain Adaptation, for WSDA. Specifically, we adopt the cluster assumption and learn cluster discriminatively with class prototypes in the embedding space. We propose to leverage the location information of the data points in the embedding space and model the location information with a Gaussian mixture model to identify noisy source data. We then design a network which incorporates the Gaussian mixture noise model as a sub-module for unsupervised noise removal and propose a novel cluster-level adversarial adaptation method which aligns unlabeled target data with the less noisy class prototypes for mapping the semantic structure across domains. We conduct extensive experiments to evaluate the effectiveness of our method on both general images and medical images from COVID-19 and e-commerce datasets. The results show that our method significantly outperforms state-of-the-art WSDA methods.

cs.CV↗

arXiv2021

Casimir force among spheres made of Weyl semimetals breaking Lorentz reciprocity

The Casimir force and thermal Casimir force originating from quantum electromagnetic fluctuations at zero and non-zero temperatures, respectively, are significant in nano- and microscale systems and are well-understood. Less understood, however, are the Casimir and thermal Casimir forces in systems breaking Lorentz reciprocity. In this work, we derive a formalism for thermal Casimir forces between an arbitrary number of spheres based on fluctuational electrodynamics and scattering theory without the assumption of Lorentz reciprocity. We study the total Casimir force in systems of two and three Weyl semimetal spheres with time-reversal symmetry breaking for different orientations of the momentum-space separation of Weyl nodes in both thermal equilibrium and nonequilibrium. In thermal nonequilibrium, we show that a net thermal Casimir force exists not only along the center-to-center displacements of the spheres, but also in the transverse direction to it due to thermal emission with non-zero angular momentum. Different symmetries of the system drive a variety of dynamics such as global rotations, self-propulsion, and spinning of the spheres. We also show that the Casimir energy in thermal equilibrium depends on the orientations of the Weyl node directions in the spheres and that the lateral Casimir force will act between the spheres even in thermal equilibrium to relax the system into the minimum energy state without transferring net energy and momentum to the environment. The developed framework opens a way for investigating many-body dynamics by Casimir and thermal Casimir forces among arbitrary number of spheres with arbitrary dielectric function tensors in both thermal equilibrium and nonequilibrium.

cond-mat.mes-hall↗

arXiv2021

On the size of special class 1 graphs and $(P_3; k)$-co-critical graphs

A well-known theorem of Vizing states that if $G$ is a simple graph with maximum degree $Δ$, then the chromatic index $χ'(G)$ of $G$ is $Δ$ or $Δ+1$. A graph $G$ is class 1 if $χ'(G)=Δ$, and class 2 if $χ'(G)=Δ+1$; $G$ is $Δ$-critical if it is connected, class 2 and $χ'(G-e)<χ'(G)$ for every $e\in E(G)$. A long-standing conjecture of Vizing from 1968 states that every $Δ$-critical graph on $n$ vertices has at least $(n(Δ-1)+ 3)/2$ edges. We initiate the study of determining the minimum number of edges of class 1 graphs $G$, in addition, $χ'(G+e)=χ'(G)+1$ for every $e\in E(\overline{G})$. Such graphs have intimate relation to $(P_3; k)$-co-critical graphs, where a non-complete graph $G$ is $(P_3; k)$-co-critical if there exists a $k$-coloring of $E(G)$ such that $G$ does not contain a monochromatic copy of $P_3$ but every $k$-coloring of $E(G+e)$ contains a monochromatic copy of $P_3$ for every $e\in E(\overline{G})$. We use the bound on the size of the aforementioned class 1 graphs to study the minimum number of edges over all $(P_3; k)$-co-critical graphs. We prove that if $G$ is a $(P_3; k)$-co-critical graph on $n\ge k+2$ vertices, then \[e(G)\ge {k \over 2}\left(n- \left\lceil {k \over 2} \right\rceil - \varepsilon\right) + {\lceil k/2 \rceil+\varepsilon \choose 2},\] where $\varepsilon$ is the remainder of $n-\lceil k/2 \rceil $ when divided by $2$. This bound is best possible for all $k \ge 1$ and $n \ge \left\lceil {3k /2} \right\rceil +2$.

math.CO↗

arXiv2021

Collision system size scan for light (anti-)nuclei and (anti-)hypertriton production in high energy nuclear collisions

The production of light (anti-)nuclei and (anti-)hypertriton in a recent collsion system size scan program proposed for the STAR experiment at the Relativistic Heavy Ion Collider (RHIC) is investigated by using the dynamically constrained phase-space coalescence model and the parton and hadron cascade model. The collision system dependence of yield ratios for deuteron to proton, helium-3 to proton, and hypertriton to $Λ$-hyperon with the corresponding values for antiparticles is predicted. The work presents that for the yield ratios a significant difference exists between (hyper)nuclei and their anti-(hyper)nuclei. Besides, much more suppression for (anti-)hypernuclei than light (anti-)nuclei is present. We further investigate strangeness population factors $s_3$ as a function of atomic mass number $A$. Our present study can provide a reference for a upcoming collision system scan program at RHIC.

hep-ph↗