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arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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The graph limit of the minimizer of the onsager-machlup functional and its computation

arXiv

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arXiv 2020年

作者： Du, Qiang Li, Tiejun Li, Xiaoguang Ren, Weiqing Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States LMAM and School of Mathematical Sciences Peking University Beijing100871 China Beijing Computational Science Research Center Beijing100193 China MOE-LCSM School of Mathematics and Statistics Hunan Normal University Changsha Hunan410081 China Department of Mathematics National University of Singapore Singapore119076 Singapore

The Onsager-Machlup (OM) functional is well-known for characterizing the most probable transition path of a diffusion process with non-vanishing noise. However, it suffers from a notorious issue that the functional is unbounded below when the specified transition time T goes to infinity. This hinders the interpretation of the results obtained by minimizing the OM functional. We provide a new perspective on this issue. Under mild conditions, we show that although the infimum of the OM functional becomes unbounded when T goes to infinity, the sequence of minimizers does contain convergent subsequences on the space of curves. The graph limit of this minimizing subsequence is an extremal of the abbreviated action functional, which is related to the OM functional via the Maupertuis principle with an optimal energy. We further propose an energy-climbing geometric minimization algorithm (EGMA) which identifies the optimal energy and the graph limit of the transition path simultaneously. This algorithm is successfully applied to several typical examples in rare event studies. Some interesting comparisons with the Freidlin-Wentzell action functional are also made. Copyright © 2020, The Authors. All rights reserved.

关键词： Optimization

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Quality of internal representation shapes learning performance in feedback neural networks

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Physical Review Research 2021年第1期3卷 013176-013176页

作者： Lee Susman Francesca Mastrogiuseppe Naama Brenner Omri Barak Interdisciplinary Program in Applied Mathematics Technion Israel Institute of Technology Haifa 32000 Israel Network Biology Research Laboratories Technion Israel Institute of Technology Haifa 32000 Israel Gatsby Computational Neuroscience Unit University College London London W1T 4JG United Kingdom Department of Chemical Engineering Technion Israel Institute of Technology Haifa 32000 Israel Rappaport Faculty of Medicine Technion Israel Institute of Technology Haifa 32000 Israel

A fundamental feature of complex biological systems is the ability to form feedback interactions with their environment. A prominent model for studying such interactions is reservoir computing, where learning acts on low-dimensional bottlenecks. Despite the simplicity of this learning scheme, the factors contributing to or hindering the success of training in reservoir networks are in general not well understood. In this work, we study nonlinear feedback networks trained to generate a sinusoidal signal, and analyze how learning performance is shaped by the interplay between internal network dynamics and target properties. By performing exact mathematical analysis of linearized networks, we predict that learning performance is maximized when the target is characterized by an optimal, intermediate frequency which monotonically decreases with the strength of the internal reservoir connectivity. At the optimal frequency, the reservoir representation of the target signal is high-dimensional, desynchronized, and thus maximally robust to noise. We show that our predictions successfully capture the qualitative behavior of performance in nonlinear networks. Moreover, we find that the relationship between internal representations and performance can be further exploited in trained nonlinear networks to explain behaviors which do not have a linear counterpart. Our results indicate that a major determinant of learning success is the quality of the internal representation of the target, which in turn is shaped by an interplay between parameters controlling the internal network and those defining the task.

关键词： Learning theory Artificial neural networks Dynamical systems Neuronal network models

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Multipartite Entanglement in Rabi Driven Superconducting Qubits

arXiv

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arXiv 2022年

作者： Lu, Marie Ville, Jean-Loup Cohen, Joachim Petrescu, Alexandru Schreppler, Sydney Chen, Larry Jüenger, Christian Pelletti, Chiara Marchenkov, Alexei Banerjee, Archan Livingston, William P. Kreikebaum, John Mark Santiago, David I. Blais, Alexandre Siddiqi, Irfan Department of Physics University of California BerkeleyCA94720 United States Institut Quantique Département de Physique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory University of California BerkeleyCA94720 United States Bleximo Corp. 701 Heinz Ave BerkeleyCA94710 United States Canadian Institute for Advanced Research TorontoONM5G1M1 Canada

Exploring highly connected networks of qubits is invaluable for implementing various quantum algorithms and simulations as it allows for entangling qubits with reduced circuit depth. Here, we demonstrate a multi-qubit STAR (Sideband Tone Assisted Rabi driven) gate. Our scheme is inspired by the ion qubit Mølmer-Sørensen gate and is mediated by a shared photonic mode and Rabi-driven superconducting qubits, which relaxes restrictions on qubit frequencies during fabrication and supports scalability. We achieve a two-qubit gate with maximum state fidelity of 95% in 310 ns, a three-qubit gate with state fidelity 90.5% in 217 ns, and a four-qubit gate with state fidelity 66% in 200 ns. Furthermore, we develop a model of the gate that show the four-qubit gate is limited by shared resonator losses and the spread of qubit-resonator couplings, which must be addressed to reach high-fidelity operations. Copyright © 2022, The Authors. All rights reserved.

关键词： Qubits

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STRICHARTZ ESTIMATES FOR 2D-SCALING INVARIANT ELECTROMAGNETIC WAVES

arXiv

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arXiv 2020年

作者： Fanelli, Luca Zhang, Junyong Zheng, Jiqiang Dipartimento di Matematica Università di Roma - La Sapienza P.le A. Moro 5 Rome00185 Italy Beijing Institute of Technology Department of Mathematics Cardiff University 100081 United Kingdom Institute of Applied Physics and Computational Mathematics Beijing100088 China

We prove Strichartz estimates for the 2D-wave equation with a scaling-critical electromagnetic potential. This problem is doubly critical, because of the scaling invariance of the model and the singularities of the potentials, which are not locally integrable. In particular, the diamagnetic phenomenon allows to consider negative electric potential which can be singular in the same fashion as the inverse-square potential. Copyright © 2020, The Authors. All rights reserved.

关键词： Wave equations

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De Haas–van Alphen study on three-dimensional topological semimetal pyrite PtBi2

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Science Bulletin 2019年第20期64卷 1496-1501页

作者： Wenshuai Gao Xiangde Zhu Jin Hu Shujing Li Fawei Zheng Hongwei Zhang Min Wu Guolin Zheng Ning Hao Ping Zhang Wei Ning Mingliang Tian Institute of Physical Science and Information Technology School of Physics and Materials ScienceAnhui UniversityHefei230601China Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field LaboratoryChinese Academy of SciencesHefei230031China Department of Physics University of Science and Technology of ChinaHefei230026China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing210093China Department of Physics Institute for Nanoscience and EngineeringUniversity of ArkansasFayettevilleAR72701USA Institute of Applied Physics and Computational Mathematics Beijing100088China Schoo of Science RMIT UniversityMelbourneVIC3001Australia

We present the systematic de Haas–van Alphen(d Hv A) quantum oscillations studies on the recently discovered topological Dirac semimetal pyrite PtBi2 single crystals. Remarkable d Hv A oscillations are emerged at a low field about 1.5 T. From the analyses of the d Hv A oscillations, we extract the high quantum mobilities, light effective masses and phase shift factors for the Dirac fermions in pyrite PtBi2. From the angular dependence of the d Hv A oscillations, we map out the topology of the Fermi ***, we identify two additional oscillation frequencies that are not probed by the Sd H oscillations, which provides us with opportunities to further understand its Fermi surface topology.

关键词： Topological semimetal Pyrite PtBi2 De Haas–van Alphen effect Fermi surface topology

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Realizable Hyperuniform and Nonhyperuniform Particle Configurations with Targeted Spectral Functions via Effective Pair Interactions

arXiv

引用

arXiv 2020年

作者： Zhang, Ge Torquato, Salvatore Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The capacity to identify realizable many-body configurations associated with targeted functional forms for the pair correlation function g2(r) or its corresponding structure factor S(k) is of great fundamental and practical importance. While there are obvious necessary conditions that a prescribed structure factor at number density ρ must satisfy to be configurationally realizable, sufficient conditions are generally not known due to the infinite degeneracy of configurations with different higher-order correlation functions. A major aim of this paper is to expand our theoretical knowledge of the class of pair correlation functions or structure factors that are realizable by classical disordered ensembles of particle configurations, including exotic "hyperuniform" varieties. We first introduce a theoretical formalism that provides a means to draw classical particle configurations from canonical ensembles with certain pairwise-additive potentials that could correspond to targeted analytical functional forms for the structure factor. This formulation enables us to devise an improved algorithm to construct systematically canonical-ensemble particle configurations with such targeted pair statistics, whenever realizable. As a proof-of-concept, we test the algorithm by targeting several different structure factors across dimensions that are known to be realizable and one hyperuniform target that is known to be nontrivially unrealizable. Our algorithm succeeds for all realizable targets and appropriately fails for the unrealizable target, demonstrating the accuracy and power of the method to numerically investigate the realizability problem. Subsequently, we also target several families of structure-factor functions that meet the known necessary realizability conditions but were heretofore not known to be realizable by disordered hyperuniform point configurations, including d-dimensional Gaussian structure factors, d-dimensional generalizations of the 2D one-component plasm

关键词：

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Diversity Improves Speed and Accuracy in Social Networks

arXiv

引用

arXiv 2020年

作者： Karamched, Bhargav Stickler, Megan Ott, William Lindner, Benjamin Kilpatrick, Zachary P. Josić, Krešimir Department of Mathematics University of Houston HoustonTX77004 United States Physics Department Humboldt University Berlin Germany Bernstein Center for Computational Neuroscience Berlin Germany Department of Applied Mathematics University of Colorado Boulder BoulderCO80309 United States Department of Biology and Biochemistry University of Houston HoustonTX77004 United States

How does temporally structured private and social information shape collective decisions? To address this question we consider a network of rational agents who independently accumulate private evidence that triggers a decision upon reaching a threshold. When seen by the whole network, the first agent’s choice initiates a wave of new decisions;later decisions have less impact. In heterogeneous networks, first decisions are made quickly by impulsive individuals who need little evidence to make a choice, but, even when wrong, can reveal the correct options to nearly everyone else. We conclude that groups comprised of diverse individuals can make more efficient decisions than homogenous *** Codes 60G70, 60H30, 92F05. Copyright © 2020, The Authors. All rights reserved.

关键词： Heterogeneous networks

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Constraining reionization with the first measurement of the cross-correlation between the CMB optical-depth fluctuations and the Compton y-map

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Physical Review D 2021年第6期104卷 063514-063514页

作者： Toshiya Namikawa Anirban Roy Blake D. Sherwin Nicholas Battaglia David N. Spergel Department of Applied Mathematics and Theoretical Physics University of Cambridge Wilberforce Road Cambridge CB3 0WA United Kingdom Department of Astronomy Cornell University Ithaca New York 14853 USA Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 OHA United Kingdom Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New York New York 10010 USA Department of Astrophysical Sciences Princeton University Peyton Hall Princeton New Jersey 08544 USA

We propose a new reionization probe that uses cosmic microwave background (CMB) observations; the cross-correlation between fluctuations in the CMB optical depth which probes the integrated electron density, δτ, and the Compton y-map which probes the integrated electron pressure. This cross-correlation is much less contaminated than the y-map power spectrum by late-time cluster contributions. In addition, this cross-correlation can constrain the temperature of ionized bubbles while the optical-depth fluctuations and kinetic Sunyaev Zel’dvich effect can not. We measure this new observable using a Planck y-map as well as a map of optical-depth fluctuations that we reconstruct from Planck CMB temperature data. We use our measurements to derive a first CMB only upper limit on the temperature inside ionized bubbles, Tb≲7.0×105 K (2σ). We also present future forecasts, assuming a fiducial model with characteristic reionization bubble size Rb=5 Mpc and Tb=5×104 K. The signal-to-noise ratio of the fiducial cross-correlation using a signal dominated y-map from the Probe of Inflation and Cosmic Origins (PICO) becomes ≃7 with CMB-S4 δτ and ≃13 with CMB-HD δτ. For the fiducial model, we predict that the CMB-HD—PICO cross-correlation should achieve an accurate measurement of the reionization parameters; Tb≃49800−5100+4500 K and Rb≃5.09−0.79+0.66 Mpc. Since the power spectrum of the electron density fluctuations is constrained by the δτ autospectrum, the temperature constraints should be only weakly model dependent on the details of the electron distributions and should be statistically representative of the temperature in ionized bubbles during reionization. This cross-correlation could, therefore, become an important observable for future CMB experiments.

关键词： Cosmic microwave background

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Imaging the spin chirality of ferrimagnetic Néel skyrmions stabilized on topological antiferromagnetic Mn3Sn

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Physical Review Materials 2021年第8期5卷 084406-084406页

作者： Teng Xu Zhen Chen Heng-An Zhou Zidong Wang Yiqing Dong Lucia Aballe Michael Foerster Pierluigi Gargiani Manuel Valvidares David M. Bracher Tatiana Savchenko Armin Kleibert Riccardo Tomasello Giovanni Finocchio Soong-Guen Je Mi-Young Im David A. Muller Wanjun Jiang State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics and Tsinghua University Beijing 100084 China Frontier Science Center for Quantum Information Tsinghua University Beijing 100084 China School of Applied and Engineering Physics Cornell University Ithaca New York 14853 USA ALBA Synchrotron Light Source Cerdanyola del Vallès 08290 Barcelona Spain Paul Scherrer Institut 5232 Villigen PSI Switzerland Institute of Applied and Computational Mathematics Foundation for Research and Technology—Hellas (FORTH) GR-70013 Heraklion Crete Greece Department of Mathematical and Computer Sciences Physical Sciences and Earth Sciences University of Messina Messina 98166 Italy Center for X-ray Optics Materials Science Division Lawrence Berkeley National Laboratory Cyclotron Road Berkeley California 94720 USA Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca New York 14853 USA

Néel skyrmions are generally realized in asymmetric multilayers made of heavy metals (HMs) and ultrathin ferromagnets possessing strong interfacial Dzyaloshinskii-Moriya interactions (iDMIs). Depending on the relative strengths of iDMIs at the interfaces, various types of Néel skyrmions have been suggested, which are typified with characteristically different topological properties and current-driven dynamics. This suggests the importance of a precise quantification of their spin chiralities. In this paper, we explore the possibility of realizing Néel skyrmions in magnetic multilayers without the direct usage of standard HMs. Specifically, through depositing a thin layer of ferrimagnetic (FIM) CoTb layer on top of an antiferromagnetic (AFM) quantum material of composition Mn3Sn, the AFM exchange interaction at the asymmetric interface provides an equivalent iDMI for stabilizing FIM Néel skyrmions. Secondly, through using advanced four-dimensional Lorentz scanning transmission electron microscopy (4D LSTEM), in combination with x-ray magnetic circular dichroism photoemission electron microscopy (XMCD-PEEM), we can directly determine the spin chirality of FIM Néel skyrmions. The present findings not only broaden the phase space for chiral interfacial magnetism but also provide a possibility for future applications of heavy-metal-free skyrmionic devices.

关键词： Magnetic texture Magnetism Spintronics

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