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Recent progress in matter in extreme states created by laser

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Matter and Radiation at Extremes 2022年第1期7卷 1-4页

作者： K.Batani D.Batani X.T.He K.Shigemori Institute of Plasma Physics and Laser Micro Fusion WarsawPoland University of Bordeaux CEACNRSUMR 510733405 TalenceFrance Plasma Physics Department National Research Nuclear University MEPhIMoscowRussia Center for Applied Physics and Technology Peking UniversityBeijingChina Institute of Applied Physics and Computational Mathematics BeijingChina Institute of Laser Engineering Osaka UniversityOsakaJapan

*** Strong interest in the modeling of planetary interiors,dwarf stars,and the physical conditions necessary to achieve inertial confinement fusion(ICF)have driven attention to the properties of matter at high density,temperature,and pressure(beyond the megabar limit).Extreme states of matter have been studied using gas guns,explosives,and Z-pinches,among other methods(see,e.g.,Refs.1–4).However in recent years,lasers have become the most reliable standard tool for creating extreme states of matter.

关键词： extreme laser states

A Compact X-Ray Laser with Ion Source and Crystal Cavity

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arXiv 2024年

作者： Li, Shuang School of Electrical and Optoelectronic Engineering West Anhui University Luan237012 China Institute of Applied Physics and Computational Mathematics Beijing100088 China Shanghai EBIT Lab Institute of Modern Physics Department of Nuclear Science and Technology Fudan University Shanghai200433 China

X-ray free-electron lasers (XFELs) are renowned for their high brightness, significantly impacting biology, chemistry, and nonlinear X-ray optics. However, current XFELs are large, expensive, and exhibit significant shot-to-shot instability. Here, we propose a novel compact apparatus for generating X-ray lasers. The setup integrates an ion source to produce highly charged ions as the gain medium. The X-ray optical cavity employs crystal Bragg diffraction for high reflectivity at large angles, and two parabolic compound refractive lenses (CRLs) focus the X-rays. Pumping is achieved through electron collision excitations. This X-ray laser offers compact dimensions, reduced costs, and enhanced coherence, positioning it as a promising seed for XFELs. With further optimization, this device has the potential to rival XFELs and revolutionize both scientific research and industrial applications. © 2024, CC BY-NC-ND.

关键词： X ray lasers

Hessian-free force-gradient integrators and their application to lattice QCD simulations

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arXiv 2025年

作者： Schäfers, Kevin Finkenrath, Jacob Günther, Michael Knechtli, Francesco Chair of Applied and Computational Mathematics Bergische Universität Wuppertal Gaußstraße 20 Wuppertal Germany Department of Physics Bergische Universität Wuppertal Gaußstraße 20 Wuppertal Germany Department of Theoretical Physics European Organization for Nuclear Research CERN Genève1211 Switzerland

We present initial results on Hessian-free force-gradient integrators for lattice field theories. Integrators of this framework promise to provide substantial performance enhancements, particularly for larger lattice volumes where higher-order integrators demonstrate greater efficiency. Numerical results demonstrate the superior efficiency of the proposed integrators compared to commonly employed non-gradient schemes, particularly due to enhanced stability properties. It is anticipated that the advantages of the Hessian-free framework will become even more pronounced in nested integration approaches and for smaller fermion masses, where the numerical stability properties of the integrators become increasingly important. © 2025, CC BY-NC-ND.

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Intermolecular Charge Transfer Induced Fragmentation of Formic Acid Dimers

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Physical Review Letters 2023年第23期130卷 233001-233001页

作者： Jiaqi Zhou Shaokui Jia Xiaoqing Hu Enliang Wang Xiaorui Xue Yong Wu Jianguo Wang Alexander Dorn Xueguang Ren School of Physics Xi’an Jiaotong University Xi’an 710049 China Institute of Applied Physics and Computational Mathematics Beijing 100088 China Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics University of Science and Technology of China Hefei 230026 China Max-Planck-Institut für Kernphysik Saupfercheckweg 1 69117 Heidelberg Germany

We investigate the intermolecular nonradiative charge transfer process in a double hydrogen-bonded formic acid (FA) dimer, initiated by electron-collision induced double ionization of one FA molecule. Through fragment ions and electron coincident momentum measurements and ab initio calculations, we obtain direct evidence that electron transfer from the neighboring FA molecule to fill one of the two vacancies occurs by a potential energy curve crossing of FA+++FA with FA++FA+* curves, forming an electronic excited state of dicationic dimers. This process causes the breaking of two hydrogen bonds and subsequently the cleavage of C─H and C─O covalent bonds in the dimers, which is expected to be a general phenomenon occurring in molecular complexes and can have important implications for radiation damage to biological matter.

关键词： Atomic & molecular structure Electronic excitation & ionization Interatomic & molecular potentials Molecular dynamics

Charge transfer and excitation processes in low energy collisions of He ions with Li atoms

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Research in Astronomy and Astrophysics 2021年第8期21卷 275-284页

作者： Xiao-Xia Wang Kun Wang Yi-Geng Peng Chun-Hua Liu Ling Liu Yong Wu Heinz-Peter Liebermann Robert J.Buenker Yi-Zhi Qu College of Material Sciences and Optoelectronic Technology University of Chinese Academy of SciencesBeijing 100049China Institute of Environmental Science Shanxi UniversityTaiyuan 030006China Department of Applied Physics Nanjing University of Science and TechnologyNanjing 210094China School of Physics Southeast UniversityNanjing 210094China Data Center for High Energy Density Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Fachbereich C-Mathematik und Naturwissenschaften Bergische Universitat WuppertalD-42097 WuppertalGermany

Electron capture between solar wind ions and neutral species has contributed to the understanding of X-ray production from solar system *** charge transfer and excitation processes in solar wind ions of He^(+)(1 s) colliding with Li(1 s^(2)2 s) atoms are studied by utilizing the full quantum-mechanical molecular-orbital close-coupling(QMOCC) method with impact energies of 0.003-2 keV *** of cross sections from single-and multi-configurational calculations for a selfconsistent field(SCF and MCSCF) process are carried *** show that the dominant reaction channels are He(1 s2 l ^(1,3) L)+Li^(+)(1 s^(2) ^(1) S).Good consistency is found among present total and state-selective charge transfer and excitation cross sections with other theoretical and experimental data in the same energy *** to the differences between coupling matrix elements in high-energy states,the charge transfer cross sections calculated from SCF and MCSCF split slightly as E> 0.4 keV *** Stueckelberg oscillations for charge transfer appear in the present *** addition,the differences of cross sections for electron excitation to Li(ls^(2)2 p) in the singlet/triplet molecular states with He+(1 s) are much smaller than those of charge transfer processes because of the similar energy gaps from Li(ls^(2)2 p) to the ground state in singlet/triplet states in the large R region.

关键词： Sun:solar wind ISM:molecules ISM:kinematics and dynamics molecular processes

Numerical evidence against advantage with quantum fidelity kernels on classical data

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Physical Review A 2023年第6期107卷 062417-062417页

作者： Lucas Slattery Ruslan Shaydulin Shouvanik Chakrabarti Marco Pistoia Sami Khairy Stefan M. Wild Department of Physics University of Illinois Urbana-Champaign Champaign Illinois 61820 USA Mathematics and Computer Science Division Argonne National Laboratory Lemont Illinois 60439 USA Global Technology Applied Research JPMorgan Chase New York New York 10017 USA Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA

Quantum machine learning techniques are commonly considered one of the most promising candidates for demonstrating practical quantum advantage. In particular, quantum kernel methods have been demonstrated to be able to learn certain classically intractable functions efficiently if the kernel is well aligned with the target function. In the more general case, quantum kernels are known to suffer from exponential “flattening” of the spectrum as the number of qubits grows, preventing generalization and necessitating the control of the inductive bias by hyperparameters. We show that the general-purpose hyperparameter-tuning techniques proposed to improve the generalization of quantum kernels lead to the kernel becoming well approximated by a classical kernel, removing the possibility of quantum advantage. We provide extensive numerical evidence for this phenomenon utilizing multiple previously studied quantum feature maps and both synthetic and real data. Our results show that unless novel techniques are developed to control the inductive bias of quantum kernels, they are unlikely to provide a quantum advantage on classical data that lacks special structure.

关键词： Machine learning Quantum computation

A Neural Network-Based Approach to Normality Testing for Dependent Data

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arXiv 2023年

作者： Kim, Minwoo Genton, Marc G. Huser, Raphaël Castruccio, Stefano Department of Statistics Pusan National University Korea Republic of Statistics program King Abdullah University of Science and Technology Saudi Arabia Department of Applied and Computational Mathematics and Statistics University of Notre Dame United States

There is a wide availability of methods for testing normality under the assumption of independent and identically distributed data. When data are dependent in space and/or time, however, assessing and testing the marginal behavior is considerably more challenging, as the marginal behavior is impacted by the degree of dependence. We propose a new approach to assess normality for dependent data by non-linearly incorporating existing statistics from normality tests as well as sample moments such as skewness and kurtosis through a neural network. We calibrate (deep) neural networks by simulated normal and non-normal data with a wide range of dependence structures and we determine the probability of rejecting the null hypothesis. We compare several approaches for normality tests and demonstrate the superiority of our method in terms of statistical power through an extensive simulation study. A real world application to global temperature data further demonstrates how the degree of spatio-temporal aggregation affects the marginal normality in the data. © 2023, CC BY.

关键词： Higher order statistics

Finite-difference least square methods for solving Hamilton-Jacobi equations using neural networks

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arXiv 2024年

作者： Esteve-Yagüe, Carlos Tsai, Richard Massucco, Alex Departamento de Matemáticas Universidad de Alicante San Vicente del Raspeig Alicante03690 Spain Department of Mathematics Oden Institute for Computational Engineering and Sciences The University of Texas at Austin Austin United States Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom

We present a simple algorithm to approximate the viscosity solution of Hamilton-Jacobi (HJ) equations using an artificial deep neural network. The algorithm uses a stochastic gradient descent-based method to minimize the least square principle defined by a monotone, consistent numerical scheme. We analyze the least square principle’s critical points and derive conditions that guarantee that any critical point approximates the sought viscosity solution. Using a deep artificial neural network lifts the restriction of conventional finite difference methods that rely on computing functions on a fixed grid. This feature makes it possible to solve HJ equations posed in higher dimensions where conventional methods are infeasible. We demonstrate the efficacy of our algorithm through numerical studies on various canonical HJ equations across different dimensions, showcasing its potential and *** Codes 49L25, 35A15, 68T07, 49K20, 65N06 Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

Ab Initio Generalized Langevin Equation

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arXiv 2022年

作者： Xie, Pinchen Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States AI for Science Institute Beijing China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing China

We introduce a machine learning-based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables in materials and molecules. In this scheme, the parameters are learned from atomistic simulations based on ab initio quantum mechanical models. Force field, memory kernel, and noise generator are constructed in the context of the Mori-Zwanzig formalism, under the constraint of the fluctuation-dissipation theorem. Combined with deep potential molecular dynamics and electronic density functional theory, this approach opens the way to multi-scale modeling in a variety of situations. Here, we demonstrate this capability with a study of two mesoscale processes in crystalline lead titanate, namely the field-driven dynamics of a planar ferroelectric domain wall, and the dynamics of an extensive lattice of coarse-grained electric dipoles. In the first case, AIGLE extends the reach of ab initio simulations to a regime of noise-driven motions not accessible to molecular dynamics. In the second case, AIGLE deals with an extensive set of collective variables by adopting a local approximation for the memory kernel and retaining only short-range noise correlations. The scheme is computationally more efficient than molecular dynamics by several orders of magnitude, and mimics the microscopic dynamics at low frequencies where it reproduces accurately the dominant far-infrared absorption frequency. © 2022, CC BY.

关键词： Molecular dynamics