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Machine learning interatomic potential for molecular dynamics simulation of the ferroelectric KNbO3 perovskite

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Physical Review B 2023年第1期107卷 014101-014101页

作者： Hao-Cheng Thong XiaoYang Wang Jian Han Linfeng Zhang Bei Li Ke Wang Ben Xu State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 People's Republic of China Graduate School China Academy of Engineering Physics Beijing 100193 People's Republic of China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 People's Republic of China Beijing Institute of Big Data Research Beijing 100871 People's Republic of China School of Materials Science and Engineering Research Center for Materials Genome Engineering Wuhan University of Technology Wuhan 430070 People's Republic of China

Ferroelectric perovskites have been ubiquitously applied in piezoelectric devices for decades, among which ecofriendly lead-free (K,Na)NbO3−based materials have been recently demonstrated to be an excellent candidate for sustainable development. Molecular dynamics is a versatile theoretical calculation approach for the investigation of the dynamical properties of ferroelectric perovskites. However, molecular dynamics simulation of ferroelectric perovskites has been limited to simple systems, since the conventional construction of interatomic potential is rather difficult and inefficient. In the present study, we construct a machine-learning interatomic potential of KNbO3 [as a representative system of (K,Na)NbO3] by using a deep neural network model. Including first-principles calculation data into the training data set ensures the quantum-mechanics accuracy of the interatomic potential. The molecular dynamics based on machine-learning interatomic potential shows good agreement with the first-principles calculations, which can accurately predict multiple fundamental properties, e.g., atomic force, energy, elastic properties, and phonon dispersion. In addition, the interatomic potential exhibits satisfactory performance in the simulation of domain wall and temperature-dependent phase transition. The construction of interatomic potential based on machine learning could potentially be transferred to other ferroelectric perovskites and consequently benefit the theoretical study of ferroelectrics.

关键词： Domain walls Elasticity Ferroelectricity First-principles calculations Phase transitions Phonons Piezoelectricity Machine learning Molecular dynamics

General Relativistic Magnetohydrodynamic Simulations of Accreting Tori: Resolution Study

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arXiv 2024年

作者： Karakonstantakis, Angelos Lančová, Debora Čemeljić, Miljenko Nicolaus Copernicus Astronomical Centre Polish Academy of Sciences ul. Bartycka 18 Warsaw00-716 Poland Research Centre for Computational Physics and Data Processing Institute of Physics Silesian University in Opava Bezručovo nám. 13 OpavaCZ-746 01 Czech Republic Academia Sinica Institute of Astronomy and Astrophysics P.O. Box 23-141 Taipei106 Taiwan

We present two-dimensional general relativistic radiative magnetohydrodynamical simulations of accretion disks around non-rotating stellar-mass black hole. We study the evolution of an equilibrium accreting torus in different grid resolutions to determine an adequate resolution to produce a stable turbulent disk driven by magneto-rotational instability. We evaluate the quality parameter, Qθ, from the ratio of MRI wavelength to the grid zone size and examine the effect of resolution in various quantitative values such as the accretion rate, magnetisation, fluxes of physical quantities and disk scale-height. We also analyse how the resolution affects the formation of plasmoids produced in the magnetic reconnection events. © 2024, CC BY.

关键词： Magnetos

A Survey of Classical And Quantum Sequence Models

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arXiv 2023年

作者： Chen, I-Chi Singh, Harshdeep Anukruti, V.L. Quanz, Brian Yogaraj, Kavitha Department of Physics and Astronomy Iowa State University AmesIA United States Centre for Computational and Data Sciences IIT Kharagpur India CQST IIIT Hyderabad India IBM Quantum IBM Research United States IBM Quantum IBM Research India

关键词： Recurrent neural networks

Optimal neural summarization for full-field weak lensing cosmological implicit inference

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Astronomy and Astrophysics 2025年 697卷

作者： Lanzieri, Denise Zeghal, Justine Lucas Makinen, T. Boucaud, Alexandre Starck, Jean-Luc Lanusse, François Université Paris Cité Université Paris-Saclay CEA CNRS AIM Gif-sur-Yvette F-91191 France Université Paris Cité CNRS Paris F-75013 France Imperial Centre for Inference and Cosmology (ICIC) & Astrophysics Group Imperial College London Blackett Laboratory Prince Consort Road London SW7 2AZ United Kingdom Université Paris-Saclay Université Paris Cité CEA CNRS AIM Gif-sur-Yvette 91191 France Sony Computer Science Laboratories - Rome Joint Initiative CREF-SONY Centro Ricerche Enrico Fermi Via Panisperna 89/A Rome 00184 Italy Institutes of Computer Science and Astrophysics Foundation for Research and Technology Hellas (FORTH) Heraklion 70013 Greece Center for Computational Astrophysics Flatiron Institute 162 5th Ave New York 10010 NY United States Department of Physics Université de Montréal Montréal H2V 0B3 Canada Mila - Quebec Artificial Intelligence Institute Montréal H2S 3H1 Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal H2V 0B3 Canada

Context. Traditionally, weak lensing cosmological surveys have been analyzed using summary statistics that were either motivated by their analytically tractable likelihoods (e.g., power spectrum) or by their ability to access some higher-order information (e.g., peak counts), but at the cost of requiring a simulation-based inference approach. In both cases, even if the statistics can be very informative, they are not designed nor guaranteed to be statistically sufficient (i.e., to capture all the cosmological information content of the data). With the rise of deep learning, however, it has becomes possible to create summary statistics that are specifically optimized to extract the full cosmological information content of the data. Yet, a fairly wide range of loss functions have been used in practice in the weak lensing literature to train such neural networks, leading to the natural question of whether a given loss should be preferred and whether sufficient statistics can be achieved in theory and in practice under these different choices. Aims. We compare different neural summarization strategies that have been proposed in the literature to identify the loss function that leads to theoretically optimal summary statistics for performing full-field cosmological inference. In doing so, we aim to provide guidelines and insights to the community to help guide future neural network-based cosmological inference analyses. Methods. We designed an experimental setup that allows us to isolate the specific impact of the loss function used to train neural summary statistics on weak lensing data at fixed neural architecture and simulation-based inference pipeline. To achieve this, we developed the sbi_lens JAX package, which implements an automatically differentiable lognormal weak lensing simulator and the tools needed to perform explicit full-field inference with a Hamiltonian Monte Carlo (HMC) sampler over this model. Using sbi_lens, we simulated a wCDM LSST Year 10 weak lens

关键词： Gravitational lensing: weak Large-scale structure of Universe Methods: statistical

The Cosmic Evolution Early Release Science Survey (CEERS)

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arXiv 2025年

作者： Finkelstein, Steven L. Bagley, Micaela B. Haro, Pablo Arrabal Dickinson, Mark Ferguson, Henry C. Kartaltepe, Jeyhan S. Kocevski, Dale D. Koekemoer, Anton M. Lotz, Jennifer M. Papovich, Casey Pérez-González, Pablo G. Pirzkal, Nor Somerville, Rachel S. Trump, Jonathan R. Yang, Guang Yung, L.Y. Aaron Fontana, Adriano Grazian, Andrea Grogin, Norman A. Kewley, Lisa J. Kirkpatrick, Allison Larson, Rebecca L. Pentericci, Laura Ravindranath, Swara Wilkins, Stephen M. Almaini, Omar Amorín, Ricardo O. Barro, Guillermo Bhatawdekar, Rachana Bisigello, Laura Brooks, Madisyn Buitrago, Fernando Calabrò, Antonello Castellano, Marco Cheng, Yingjie Cleri, Nikko J. Cole, Justin W. Cooper, M.C. Cooper, Olivia R. Costantin, Luca Cox, Isa G. Croton, Darren Daddi, Emanuele Davis, Kelcey Dekel, Avishai Elbaz, David Fernández, Vital Fujimoto, Seiji Gandolfi, Giovanni Gardner, Jonathan P. Gawiser, Eric Giavalisco, Mauro Gómez-Guijarro, Carlos Guo, Yuchen Gupta, Ansh R. Hathi, Nimish P. Harish, Santosh Henry, Aurélien Hirschmann, Michaela Hu, Weida Hutchison, Taylor A. Iyer, Kartheik G. Jaskot, Anne E. Jha, Saurabh W. Jung, Intae Kokorev, Vasily Kurczynski, Peter Leung, Gene C.K. Llerena, Mario Long, Arianna S. Lucas, Ray A. Lu, Shiying McGrath, Elizabeth J. McIntosh, Daniel H. Merlin, Emiliano Morales, Alexa M. Napolitano, Lorenzo Pacucci, Fabio Pandya, Viraj Rafelski, Marc Rodighiero, Giulia Rose, Caitlin Santini, Paola Seillé, Lise-Marie Simons, Raymond C. Shen, Lu Straughn, Amber N. Tacchella, Sandro Vanderhoof, Brittany N. Vega-Ferrero, Jesús Weiner, Benjamin J. Willmer, Christopher N.A. Zhu, Peixin Bell, Eric F. Wuyts, Stijn Holwerda, Benne W. Wang, Xin Wang, Weichen Zavala, Jorge A. Department of Astronomy The University of Texas at Austin AustinTX United States Astrophysics Science Division NASA Goddard Space Flight Center 8800 Greenbelt Rd GreenbeltMD20771 United States NSF’s National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Ave. TucsonAZ85719 United States Space Telescope Science Institute BaltimoreMD United States Laboratory for Multiwavelength Astrophysics School of Physics and Astronomy Rochester Institute of Technology 84 Lomb Memorial Drive RochesterNY14623 United States Department of Physics and Astronomy Colby College WatervilleME04901 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Gemini Observatory NSF’s National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Ave. TucsonAZ85719 United States George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy Department of Physics and Astronomy Texas A&M University College StationTX United States Ctra. de Ajalvir km 4 Torrejón de Ardoz MadridE-28850 Spain ESA/AURA Space Telescope Science Institute Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Physics University of Connecticut 196A Auditorium Road Unit 3046 StorrsCT06269 United States Nanjing Institute of Astronomical Optics and Technology Nanjing210042 China INAF - Osservatorio Astronomico di Roma via di Frascati 33 Monte Porzio Catone00078 Italy INAF–Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States Department of Physics and Astronomy University of Kansas LawrenceKS66045 United States Astronomy Centre University of Sussex Falmer BrightonBN1 9QH United Kingdom Institute of Space Sciences and Astronomy University of Malta MsidaMSD 2080 Malta School of Physics and Astronomy University of Notting

We present the Cosmic Evolution Early Release Science (CEERS) Survey, a 77.2 hour Director’s Discretionary Early Release Science Program. CEERS demonstrates, tests, and validates efficient extragalactic surveys using coordinated, overlapping parallel observations with the JWST instrument suite, including NIRCam and MIRI imaging, NIRSpec low (R∼100) and medium (R∼1000) resolution spectroscopy, and NIRCam slitless grism (R∼1500) spectroscopy. CEERS targets the Hubble Space Telescope-observed region of the Extended Groth Strip (EGS) field, supported by a rich set of multiwavelength data. CEERS facilitated immediate community science in both of the extragalactic core JWST science drivers "First Light" and "Galaxy Assembly," including: 1) The discovery and characterization of large samples of galaxies at z 10 from ∼90 arcmin2 of NIRCam imaging, constraining their abundance and physical nature;2) Deep spectra of >1000 galaxies, including dozens of galaxies at 6 3;and 4) Characterizing galaxy mid-IR emission with MIRI to study dust-obscured star-formation and supermassive black hole growth at z ∼ 1–3. As a legacy product for the community, the CEERS team has provided several data releases, accompanied by detailed notes on the data reduction procedures and notebooks to aid in reproducibility. In addition to an overview of the survey and quality of the data, we provide science highlights from the first two years with CEERS data. Copyright © 2025, The Authors. All rights reserved.

关键词： Cosmology

Evolution of cooperation under a generalized death-birth process

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arXiv 2023年

作者： Wang, Chaoqian Szolnoki, Attila Department of Computational and Data Sciences George Mason University FairfaxVA22030 United States Institute of Technical Physics and Materials Science Centre for Energy Research P.O. Box 49 BudapestH-1525 Hungary

According to the evolutionary death-birth protocol, a player is chosen randomly to die and neighbors compete for the available position proportional to their fitness. Hence, the status of the focal player is completely ignored and has no impact on the strategy update. In this work, we revisit and generalize this rule by introducing a weight factor to compare the payoff values of the focal and invading neighbors. By means of evolutionary graph theory, we analyze the model on joint transitive graphs to explore the possible consequences of the presence of a weight factor. We find that focal weight always hinders cooperation under weak selection strength. Surprisingly, the results show a non-trivial tipping point of the weight factor where the threshold of cooperation success shifts from positive to negative infinity. Once focal weight exceeds this tipping point, cooperation becomes unreachable. Our theoretical predictions are confirmed by Monte Carlo simulations on a square lattice of different sizes. We also verify the robustness of the conclusions to arbitrary two-player prisoner's dilemmas, to dispersal graphs with arbitrary edge weights, and to interaction and dispersal graphs overlapping arbitrarily. © 2023, CC BY.

关键词： Monte Carlo methods

Two-neutron halo structure of F31 and a novel pairing antihalo effect

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Physical Review C 2020年第4期101卷 041303(R)-041303(R)页

作者： H. Masui W. Horiuchi M. Kimura Information Processing Center Kitami Institute of Technology Kitami 090-8507 Japan Department of Physics Hokkaido University Sapporo 060-0810 Japan Nuclear Reaction Data Centre Hokkaido University Sapporo 060-0810 Japan and Research Center for Nuclear Physics (RCNP) Osaka University Ibaraki 567-0047 Japan

Background: A newly identified drip-line nucleus F31 offers a unique opportunity to study the two-neutron (2n) correlation at the east shore of the island of inversion where the N=28 shell closure is lost.

关键词： Cluster models Nuclear binding Nuclear forces Nucleon distribution Unstable nuclei induced nuclear reactions 20 ≤ A ≤ 38

Competition between self- and other-regarding preferences in resolving social dilemmas

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arXiv 2024年

Evolutionary game theory assumes that individuals maximize their benefits when choosing strategies. However, an alternative perspective proposes that individuals seek to maximize the benefits of others. To explore the relationship between these perspectives, we develop a model where self- and other-regarding preferences compete in public goods games. We find that other-regarding preferences are more effective in promoting cooperation, even when self-regarding preferences are more productive. Cooperators with different preferences can coexist in a new phase where two classic solutions invade each other, resulting in a dynamical equilibrium. As a consequence, a lower productivity of self-regarding cooperation can provide a higher cooperation level. Our results, which are also valid in a well-mixed population, may explain why other-regarding preferences could be a viable and frequently observed attitude in human society. © 2024, CC BY.

关键词：

Three-dimensional general relativistic Poynting-Robertson effect. III. Static and nonspherical quadrupolar massive source

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Physical Review D 2020年第12期101卷 124031-124031页

作者： Vittorio De Falco Pavel Bakala Maurizio Falanga M. R. Štefánik Observatory and Planetarium Sládkovičova 41 920 01 Hlohovec Slovak Republic Research Centre for Computational Physics and Data Processing Faculty of Philosophy & Science Silesian University in Opava Bezručovo nám. 13 CZ-74601 Opava Czech Republic International Space Science Institute Hallerstrasse 6 3012 Bern Switzerland

We investigate the three-dimensional (3D) motion of a test particle in the gravitational field generated by a nonspherical compact object endowed with a mass quadrupole moment, described by the Erez-Rosen metric, and a radiation field, including the general relativistic Poynting-Robertson (PR) effect, coming from a rigidly rotating spherical emitting source located outside of the compact object. We derive the equations of motion for test particles influenced by such radiation field, recovering the two-dimensional (2D) description, and the weak-field approximation. This dynamical system admits the existence of a critical hypersurface, region where gravitational and radiation forces balance. Selected test particle orbits for different set of input parameters are displayed. The possible configurations on the critical hypersurfaces can be either latitudinal drift toward the equatorial ring or suspended orbits. We discuss about the existence of multiple hypersurface solutions through a simple method to perform the calculations. We graphically prove also that the critical hypersurfaces are stable configurations within the Lyapunov theory.

关键词： General relativity Gravitation Classical black holes Astrophysical electromagnetic fields Numerical simulations in gravitation & astrophysics