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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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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

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Evidence of mini-jet emission in a large emission zone from a magnetically-dominated gamma-ray burst jet

arXiv

引用

arXiv 2023年

作者： Yi, S.-X. Wang, C.-W. Shao, X. Moradi, R. Gao, H. Zhang, B. Xiong, S.-L. Zhang, S.-N. Tan, W.-J. Liu, J.-C. Xue, W.-C. Zhang, Y.-Q. Zheng, C. Wang, Y. Zhang, P. An, Z.-H. Cai, C. Feng, P.-Y. Gong, K. Guo, D.-Y. Huang, Y. Li, B. Li, X.-B. Li, X.-Q. Liu, X.-J. Liu, Y.-Q. Ma, X. Peng, W.-X. Qiao, R. Song, L.-M. Wang, J. Wang, P. Wang, Y. Wen, X.-Y. Xiao, S. Xu, Y.-B. Yang, S. Yi, Q.-B. Zhang, D.-L. Zhang, F. Zhang, H.-M. Zhang, J.-P. Zhang, Z. Zhao, X.-Y. Zhao, Y. Zheng, S.-J. Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100049 China Department of Astronomy Beijing Normal University Beijing100875 China Nevada Center for Astrophysics University of Nevada Las Vegas NV89154 United States Department of Physics and Astronomy University of Nevada Las Vegas NV89154 United States ICRANet Piazza della Repubblica 10 PescaraI-65122 Italy ICRA Dipartamento di Fisica Sapienza Università di Roma Piazzale Aldo Moro 5 RomeI-00185 Italy INAF Osservatorio Astronomico d’Abruzzo Via M. Maggini snc TeramoI-64100 Italy College of Electronic and Information Engineering Tongji University Shanghai201804 China College of Physics Hebei Key Laboratory of Photophysics Research and Application Hebei Normal University Hebei Shijiazhuang050024 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang550001 China School of Physics and Optoelectronics Xiangtan University Yuhu District Hunan411105 China School of Computer and Information Dezhou University Dezhou253023 China

The second brightest GRB in history, GRB230307A, provides an ideal laboratory to study the mechanism of GRB prompt emission thanks to its extraordinarily high photon statistics and its single episode activity. Here we demonstrate that the rapidly variable components of its prompt emission compose an overall broad single pulse-like profile. Although these individual rapid components are aligned in time across all energy bands, this overall profile conspires to show a well-defined energy-dependent behavior which is typically seen in single GRB pulses. Such a feature demonstrates that the prompt emission of this burst is from many individual emitting units that are casually linked in a emission site at a large distance from the central engine. Such a scenario is in natural consistency with the internal-collision-induced magnetic reconnection and turbulence framework, which invokes many mini-jets due to local magnetic reconnection that constantly appear and disappear in a global magnetically-dominated jet. © 2023, CC BY.

关键词： Gamma rays

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Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

arXiv

引用

arXiv 2023年

作者： de Santi, Natalí S.M. Villaescusa-Navarro, Francisco Abramo, L. Raul Shao, Helen Perez, Lucia A. Castro, Tiago Ni, Yueying Lovell, Christopher C. Hernández-Martínez, Elena Marinacci, Federico Spergel, David N. Dolag, Klaus Hernquist, Lars Vogelsberger, Mark Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Instituto de Física Universidade de São Paulo R. do Matão 1371 São Paulo05508-900 Brazil Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States INAF Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34143 Italy INFN Sezione di Trieste TriesteI-34100 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy ICSC - Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States McWilliams Center for Cosmology Department of Physics Carnegie Mellon University PittsburghPA15213 United States Institute of Cosmology and Gravitation University of Portsmouth Burnaby Road PortsmouthPO1 3FX United Kingdom Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstr. 1 München81679 Germany Department of Physics and Astronomy Augusto Righi University of Bologna via Gobetti 93/2 Bologna40129 Italy Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching85741 Germany Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA United States Kavli Institute for Astrophysics and Space Research Department of Physics MIT CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Massachusetts Institute of Technology CambridgeMA02139 United States

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. [58] developed models that could accurately infer the value of Ωm from catalogs that only contain the positions and radial velocities of galaxies that are robust to different astrophysics and subgrid models. However, observations are affected by many effects, including 1) masking, 2) uncertainties in peculiar velocities and radial distances, and 3) different galaxy population selections. Moreover, observations only allow us to measure redshift, which entangles the galaxy radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that while such effects degrade the precision and accuracy of the models, the fraction of galaxy catalogs for which the models retain high performance and robustness is over 90%, demonstrating the potential for applying them to real data. Copyright © 2023, The Authors. All rights reserved.

关键词： Cosmology

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Density Fluctuations in the Intracluster Medium: An Attempt to Constrain Viscosity with Cosmological Simulations

arXiv

引用

arXiv 2024年

作者： Marin-Gilabert, Tirso Steinwandel, Ulrich P. Valentini, Milena Vallés-Pérez, David Dolag, Klaus Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstr.1 München81679 Germany Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Astronomy Unit Department of Physics University of Trieste via Tiepolo 11 TriesteI-34131 Italy INAF - Osservatorio Astronomico di Trieste via Tiepolo 11 TriesteI-34131 Italy INFN Instituto Nazionale di Fisica Nucleare Via Valerio 2 TriesteI-34127 Italy ICSC - Italian Research Center on High Performance Computing Big Data and Quantum Computing via Magnanelli 2 Casalecchio di Reno40033 Italy Departament d'Astronomia i Astrofísica Universitat de València C/Doctor Moliner 50 València BurjassotE-46100 Spain Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching85741 Germany

The impact of viscosity in the Intracluster Medium (ICM) is still an open question in astrophysics. To address this problem, we have run a set of cosmological simulations of three galaxy clusters with a mass larger than MVir > 1015M☉ at z = 0 using the SPMHD-code OpenGadget3. We aim to quantify the influence of viscosity and constrain its value in the ICM. Our results show significant morphological differences at small scales, temperature variations, and density fluctuations induced by viscosity. We observe a suppression of instabilities at small scales, resulting in a more filamentary structure and a larger amount of small structures due to the lack of mixing with the medium. The conversion of kinetic to internal energy leads to an increase of the virial temperature of the cluster of ∼5% - 10%, while the denser regions remain cold. The amplitude of density and velocity fluctuations are found to increase with viscosity. However, comparison with observational data indicates that the simulations, regardless of the viscosity, match the observed slope of the amplitude of density fluctuations, challenging the direct constraint of viscosity solely through density fluctuations. Furthermore, the ratio of density to velocity fluctuations remains close to 1 regardless of the amount of viscosity, in agreement with the theoretical expectations. Our results show for the first time in a cosmological simulation of a galaxy cluster the effect of viscosity in the ICM, a study that is currently missing in the literature. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

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Unveiling the Multifaceted GRB 200613A: Prompt Emission Dynamics, Afterglow Evolution, and the Host Galaxy’s Properties

arXiv

引用

arXiv 2024年

作者： Fu, Shao-Yu Xu, Dong Lei, Wei-Hua de Ugarte Postigo, Antonio Kann, D. Alexander Thöne, Christina C. Fernández, José Feliciano Agüí Shuang-Xi, Yi Xie, Wei Zou, Yuan-Chuan Liu, Xing Jiang, Shuai-Qing Lu, Tian-Hua An, Jie Zhu, Zi-Pei Zheng, Jie Tang, Qing-Wen Zhao, Peng-Wei Xin, Li-Ping Wei, Jian-Yan Key Laboratory of Space Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Astronomy and Space Science University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100049 China Department of Astronomy School of Physics Huazhong University of Science and Technology Wuhan430074 China Université de la Côte d’Azur Observatoire de la Côte d’Azur CNRS Artemis Nice06304 France Aix Marseille Univ. CNRS LAM Marseille France Hessian Research Cluster ELEMENTS Giersch Science Center Goethe University Frankfurt Max-von-Laue-Straße 12 Campus Riedberg Frankfurt am MainD-60438 Germany Astronomical Institute Czech Academy of Sciences Fričova Ondřejov298 Czech Republic Centro Astronómico Hispano en Andalucía Observatorio de Calar Alto Sierra de los Filabres Gérgal Almería04550 Spain School of Physics and Physical Engineering Qufu Normal University Qufu273165 China Department of Astronomy School of Physics and Electronic Science Guizhou Normal University Guiyang550001 China Guizhou Provincial Key Laboratory of Radio Astronomy Data Processing Guizhou Normal University Guiyang550001 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Department of Physics School of Science Nanchang University Nanchang330031 China

We present our optical observations and multi-wavelength analysis of the GRB 200613A detected by Fermi satellite. Time-resolved spectral analysis of the prompt γ-ray emission was conducted utilizing the Bayesian block method to determine statistically optimal time bins. Based on the Bayesian Information Criterion (BIC), the data generally favor the Band+Blackbody (short as BB) model. We speculate that the main Band component comes from the Blandford-Znajek mechanism, while the additional BB component comes from the neutrino annihilation process. The BB component becomes significant for a low-spin, high-accretion rate black hole central engine, as evidenced by our model comparison with the data. The afterglow light curve exhibits typical power-law decay, and its behavior can be explained by the collision between the ejecta and constant interstellar medium (ISM). Model fitting yields the following parameters: EK,iso = (2.04+11.8-1.50) × 1053 erg, Γ0 = 354+578-217, p = 2.09+0.02-0.03, n18 = (2.04+9.71-1.87)×102 cm-3, θj = 24.0-5.54+6.50 degree, ϵe = 1.66+4.09-1.39)×10-1 and ϵB = (7.76+48.5-5.9)×10-6. In addition, we employed the public Python package Prospector perform a spectral energy distribution (SED) modeling of the host galaxy. The results suggest that the host galaxy is a massive galaxy (log(M∗/M☉) = 11.75-0.09+0.10) with moderate star formation rate (SFR = 22.58+13.63-7.22 M☉/yr). This SFR is consistent with the SFR of ∼ 34.2M☉ yr-1 derived from the [OII] emission line in the observed spectrum. © 2024, CC0.

关键词： Gamma rays

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基于MeerKAT和FAST探索球状星团:脉冲星偏振研究（英文）

引用

Science Bulletin 2025年第10期 1568-1571页

作者：张蕾 Federico Abbate 李菂 Andrea Possenti Matthew Bailes Alessandro Ridolfi Paulo C.C.Freire Scott M.Ransom 张永坤郭猛尼盟萌胡佳乐冯毅王培张洁支启军 National Astronomical Observatories Chinese Academy of Sciences Centre for Astrophysics and Supercomputing Swinburne University of Technology INAF-Osservatorio Astronomico di Cagliari Max-Planck-Institut für Radioastronomie New Cornerstone Science Laboratory Department of AstronomyTsinghua University ARC Center of Excellence for Gravitational Wave Discovery (OzGrav) Swinburne University of Technology Faculty of Physics University of Bielefeld National Radio Astronomy Observatory National Supercomputing Center in Jinan Qilu University of Technology Jinan Institute of Supercomputing Technology Research Center for Intelligent Computing Platforms Zhejiang Laboratory Institute for Astronomy School of PhysicsZhejiang University College of Physics and Electronic Engineering Qilu Normal University Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University

Magnetic fields are pervasive throughout the Universe. They are integral to a wide array of astrophysical processes that span various physical scales and field strengths. The Galactic magnetic field,in particular, holds significant importance in shaping the evolution of our Galaxy. However, our understanding of its behavior on small scales remains poor, especially when considering its penetration into the Galactic halo [1].

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Model-independent searches of new physics in DARWIN with a semi-supervised deep learning pipeline

arXiv

引用

arXiv 2024年

作者： Aalbers, J. Abe, K. Adrover, M. Ahmed Maouloud, S. Althueser, L. Amaral, D.W.P. Andrieu, B. Angelino, E. Antón Martin, D. Antunovic, B. Aprile, E. Babicz, M. Bajpai, D. Balzer, M. Barberio, E. Baudis, L. Bazyk, M. Bell, N.F. Bellagamba, L. Biondi, R. Biondi, Y. Bismark, A. Boehm, C. Boese, K. Braun, R. Breskin, A. Brommer, S. Brown, A. Bruni, G. Budnik, R. Cai, C. Capelli, C. Chauvin, A. Cimental Chavez, A.P. Colijn, A.P. Conrad, J. Cuenca-García, J.J. D'Andrea, V. Daniel Garcia, L.C. Decowski, M.P. Deisting, A. Di Donato, C. Di Gangi, P. Diglio, S. Doerenkamp, M. Drexlin, G. Eitel, K. Elykov, A. Engel, R. Ferella, A.D. Ferrari, C. Fischer, H. Flehmke, T. Flierman, M. Fujikawa, K. Fulgione, W. Fuselli, C. Gaemers, P. Gaior, R. Galloway, M. Gao, F. Garroum, N. Giacomobono, R. Girard, F. Glade-Beucke, R. Glück, F. Grandi, L. Grigat, J. Größle, R. Guan, H. Guida, M. Gyorgy, P. Hammann, R. Hannen, V. Hansmann-Menzemer, S. Hargittai, N. Higuera, A. Hils, C. Hiraoka, K. Hoetzsch, L. Hoferichter, M. Hood, N.F. Iacovacci, M. Itow, Y. Jakob, J. James, R.S. Joerg, F. Kahlert, F. Kaminaga, Y. Kara, M. Kavrigin, P. Kazama, S. Keller, M. Kharbanda, P. Kilminster, B. Kleifges, M. Klute, M. Kobayashi, M. Koke, D. Kopec, A. von Krosigk, B. Kuger, F. LaCascio, L. Landsman, H. Lang, R.F. Levinson, L. Li, I. Li, A. Li, S. Liang, S. Liang, Z. Lin, Y.-T. Lindemann, S. Lindner, M. Liu, K. Loizeau, J. Lombardi, F. Long, J. Lopes, J.A.M. Lucchetti, G.M. Luce, T. Ma, Y. Macolino, C. Mahlstedt, J. Maier, B. Mancuso, A. Manenti, L. Marignetti, F. Martens, K. Masbou, J. Masson, E. Mastroianni, S. Melchiorre, A. Menéndez, J. Messina, M. Milosovic, B. Milutinovic, S. Miuchi, K. Miyata, R. Molinario, A. Monteiro, C.M.B. Morå, K. Moriyama, S. Morteau, E. Mosbacher, Y. Müller, J. Murra, M. Newstead, J.L. Ni, K. O'Hare, C. Oberlack, U. Obradovic, M. Ostrowskiy, I. Ouahada, S. Paetsch, B. Pan, Y. Pandurovic, M. Pellegrini, Q. Nikhef The University of Groningen Van Swinderen Institute Groningen9747AG Netherlands University of Tokyo Higashi-Mozumi Kamioka Gifu Hida506-1205 Japan Physik-Institut University of Zürich Zürich8057 Switzerland LPNHE Sorbonne Université CNRS IN2P3 Paris75005 France Institute for Nuclear Physics University of Münster Münster48149 Germany Department of Physics and Astronomy Rice University HoustonTX77005 United States INAF-Astrophysical Observatory of Torino Department of Physics University of Torino INFN-Torino Torino10125 Italy INFN-Laboratori Nazionali del Gran Sasso Gran Sasso Science Institute L'Aquila67100 Italy Department of Physics Enrico Fermi Institute Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Vinca Institute of Nuclear Science University of Belgrade Mihajla Petrovica Alasa 12-14 Belgrade Serbia Physics Department Columbia University New YorkNY10027 United States Department of Physics & Astronomy University of Alabama TuscaloosaAL34587-0324 United States Institute for Data Processing and Electronics Karlsruhe Institute of Technology Karlsruhe76021 Germany ARC Centre of Excellence for Dark Matter Particle Physics School of Physics The University of Melbourne VIC3010 Australia SUBATECH IMT Atlantique CNRS IN2P3 Nantes Université Nantes44307 France Department of Physics and Astronomy University of Bologna INFN-Bologna Bologna40126 Italy Max-Planck-Institut für Kernphysik Heidelberg69117 Germany Institute for Astroparticle Physics Karlsruhe Institute of Technology Karlsruhe76021 Germany School of Physics The University of Sydney Camperdown SydneyNSW2006 Australia Department of Particle Physics and Astrophysics Weizmann Institute of Science Rehovot7610001 Israel Institute of Experimental Particle Physics Karlsruhe Institute of Technology Karlsruhe76021 Germany Physikalisches Institut Universität Freiburg Freiburg79104 Germany Department of Physics and

We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment, DARWIN. We train an anomaly detector comprising a variational autoencoder and a classifier on extensive, high-dimensional simulated detector response data and construct a one-dimensional anomaly score optimised to reject the background only hypothesis in the presence of an excess of non-background-like events. We benchmark the procedure with a sensitivity study that determines its power to reject the background-only hypothesis in the presence of an injected WIMP dark matter signal, outperforming the classical, likelihood-based background rejection test. We show that our neural networks learn relevant energy features of the events from low-level, high-dimensional detector outputs, without the need to compress this data into lower-dimensional observables, thus reducing computational effort and information loss. For the future, our approach lays the foundation for an efficient end-to-end pipeline that eliminates the need for many of the corrections and cuts that are traditionally part of the analysis chain, with the potential of achieving higher accuracy and significant reduction of analysis time. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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Can we constrain warm dark matter masses with individual galaxies?

arXiv

引用

arXiv 2024年

作者： Lin, Shurui Villaescusa-Navarro, Francisco Rose, Jonah Torrey, Paul Farahi, Arya Kollmann, Kassidy E. Garcia, Alex M. Roy, Sandip Kallivayalil, Nitya Vogelsberger, Mark Cai, Yi-Fu Luo, Wentao Department of Astronomy School of Physical Sciences University of Science and Technology of China Anhui Hefei230026 China CAS Key Laboratory for Researches in Galaxies and Cosmology School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Center for Computational Astrophysics 162 5th Avenue New YorkNY10010 United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Department of Astronomy University of Florida GainesvilleFL32611 United States Department of Astronomy University of Virginia 530 McCormick Road CharlottesvilleVA22903 United States Departments of Statistics and Data Science University of Texas at Austin AustinTX78757 United States Department of Physics Princeton University PrincetonNJ08544 United States Department of Astronomy University of Virginia 530 McCormick Road CharlottesvilleVA22904 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Massachusetts Institute of Technology CambridgeMA02139 United States

We study the impact of warm dark matter mass on the internal properties of individual galaxies using a large suite of 1,024 state-of-the-art cosmological hydrodynamic simulations from the DREAMS project. We take individual galaxies’ properties from the simulations, which have different cosmologies, astrophysics, and warm dark matter masses, and train normalizing flows to learn the posterior of the parameters. We find that our models cannot infer the value of the warm dark matter mass, even when the values of the cosmological and astrophysical parameters are given explicitly. This result holds for galaxies with stellar mass larger than 2 × 108M☉/h at both low and high redshifts. We calculate the mutual information and find no significant dependence between the WDM mass and galaxy properties. On the other hand, our models can infer the value of Ωm with a ∼ 10% accuracy from the properties of individual galaxies while marginalizing astrophysics and warm dark matter masses. © 2024, CC BY.

关键词： Galaxies

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FAST Observations of Four Comets to Search for the Molecular Line Emissions between 1.0 and 1.5 GHz Frequencies

arXiv

引用

arXiv 2024年

作者： Chen, Long-Fei Tsai, Chao-Wei Li, Jian-Yang Yang, Bin Li, Di Duan, Yan Hsia, Chih-Hao Pan, Zhichen Qian, Lei Quan, Donghui Jiang, Xue-Jian Li, Xiaohu Zhao, Ruining Zuo, Pei School of Physics and Electronic Science Guizhou Normal University Guiyang550025 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guiyang550025 China Research Center for Astronomical Computing Zhejiang Laboratory Hangzhou311100 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University Beijing102206 China Key Laboratory of Radio Astronomy and Technology Chinese Academy of Sciences A20 Datun Road Chaoyang District Beijing100101 China School of Atmospheric Sciences Sun Yat-sen University Guangdong Zhuhai China Núcleo de Astronomía Facultad de Ingenieríay Ciencias Universidad Diego Portales Chile Department of Astronomy College of Physics and Electronic Engineering Qilu Normal University 2 Wenbo Road Zhangqiu District Jinan250200 China Department of Electronic and Optical Engineering Space Engineering University Beijing China Laboratory for Space Research Faculty of Science The University of Hong Kong Hong Kong Xinjiang Astronomical Observatory Chinese Academy of Sciences No. 150 Science 1-Street Urumqi830011 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Astronomy and Space Sciences University of Chinese Academy of Sciences Beijing100049 China

We used the Five-hundred-meter Aperture Spherical radio Telescope (FAST) to search for the molecular emissions in the L-band between 1.0 and 1.5 GHz toward four comets, C/2020 F3 (NEOWISE), C/2020 R4 (ATLAS), C/2021 A1 (Leonard), and 67P/Churyumov-Gerasimenko during or after their perihelion passages. Thousands of molecular transition lines fall in this low-frequency range, many attributed to complex organic or prebiotic molecules. We conducted a blind search for the possible molecular lines in this frequency range in those comets and could not identify clear signals of molecular emissions in the data. Although several molecules have been detected at high frequencies of great than 100 GHz in comets, our results confirm that it is challenging to detect molecular transitions in the L-band frequency ranges. The non-detection of L-band molecular lines in the cometary environment could rule out the possibility of unusually strong lines, which could be caused by the masers or non-LTE effects. Although the line strengths are predicted to be weak, for FAST, using the ultra-wide bandwidth receiver and improving the radio frequency interference environments would enhance the detectability of those molecular transitions at low frequencies in the future. Copyright © 2024, The Authors. All rights reserved.

关键词： Molecules

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