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38th International Cosmic Ray Conference, ICRC 2023

作者： Bertaina, Mario Zotov, Mikhail Anzhiganov, Dmitry Barghini, Dario Blaksley, Carl Coretti, Antonio Giulio Kryazhenkov, Aleksandr Montanaro, Antonio Olivi, Leonardo Abe, S. Adams, J.H. Allard, D. Alldredge, P. Aloisio, R. Anchordoqui, L. Anzalone, A. Arnone, E. Bagheri, M. Baret, B. Barghini, D. Battisti, M. Bellotti, R. Belov, A.A. Bertaina, M. Bertone, P.F. Bianciotto, M. Bisconti, F. Blaksley, C. Blin-Bondil, S. Bolmgren, K. Briz, S. Burton, J. Cafagna, F. Cambié, G. Campana, D. Capel, F. Caruso, R. Casolino, M. Cassardo, C. Castellina, A. Černý, K. Christl, M.J. Colalillo, R. Conti, L. Cotto, G. Crawford, H.J. Cremonini, R. Creusot, A. Cummings, A. de Castro Gónzalez, A. de la Taille, C. Diesing, R. Dinaucourt, P. Di Nola, A. Ebisuzaki, T. Eser, J. Fenu, F. Ferrarese, S. Filippatos, G. Finch, W.W. Flaminio, F. Fornaro, C. Fuehne, D. Fuglesang, C. Fukushima, M. Gadamsetty, S. Gardiol, D. Garipov, G.K. Gazda, E. Golzio, A. Guarino, F. Guépin, C. Haungs, A. Heibges, T. Isgrò, F. Judd, E.G. Kajino, F. Kaneko, I. Kim, S.-W. Klimov, P.A. Krizmanic, J.F. Kungel, V. Kuznetsov, E. López Martínez, F. Mandát, D. Manfrin, M. Marcelli, A. Marcelli, L. Marszal, W. Matthews, J.N. Mese, M. Meyer, S.S. Mimouni, J. Miyamoto, H. Mizumoto, Y. Monaco, A. Nagataki, S. Nachtman, J.M. Naumov, D. Neronov, A. Nonaka, T. Ogawa, T. Ogio, S. Ohmori, H. Olinto, A.V. Onel, Y. Osteria, G. Otte, A.N. Pagliaro, A. Panico, B. Parizot, E. Park, I.H. Paul, T. Pech, M. Perfetto, F. Picozza, P. Piotrowski, L.W. Plebaniak, Z. Posligua, J. Potts, M. Prevete, R. Prévôt, G. Przybylak, M. Reali, E. Reardon, P. Reno, M.H. Ricci, M. Romero Matamala, O.F. Romoli, G. Sagawa, H. Sakaki, N. Saprykin, O.A. Sarazin, F. Sato, M. Schovánek, P. Scotti, V. Selmane, S. Sharakin, S.A. Shinozaki, K. Stepanoff, S. Soriano, J.F. Szabelski, J. Tajima, N. Tajima, T. Takahashi, Y. Takeda, M. Takizawa, Y. Thomas, S.B. Tkachev, L.G. Tomida, T. Toscano, S. Dipartimento di Fisica Università di Torino Torino Italy INFN Sezione di Torino Torino Italy Skobeltsyn Institute of Nuclear Physics Lomonosov Moscow State University Moscow Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russia INAF Osservatorio astrofisico di Torino Torino Italy Department of Electronics and Telecommunications Polytechnic University of Turin Corso Duca degli Abruzzi 24 Turin10129 Italy Algiers Algeria Univ. Constantine I Constantine Algeria Joint Laboratory of Optics Faculty of Science Palacký University Olomouc Czech Republic Institute of Physics The Czech Academy of Sciences Prague Czech Republic Omega Ecole Polytechnique CNRS IN2P3 Palaiseau France Université de Paris CNRS AstroParticule et Cosmologie ParisF-75013 France France Germany Max Planck Institute for Physics Munich Germany Istituto Nazionale di Fisica Nucleare - Sezione di Bari Italy Università degli Studi di Bari Aldo Moro Italy Dipartimento di Fisica e Astronomia "Ettore Majorana" Università di Catania Italy Istituto Nazionale di Fisica Nucleare - Sezione di Catania Italy Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali di Frascati Italy Istituto Nazionale di Fisica Nucleare - Sezione di Napoli Italy Università di Napoli Federico II Dipartimento di Fisica "Ettore Pancini" Italy INAF - Istituto di Astrofisica Spaziale e Fisica Cosmica di Palermo Italy Istituto Nazionale di Fisica Nucleare - Sezione di Roma Tor Vergata Italy Università di Roma Tor Vergata - Dipartimento di Fisica Roma Italy Istituto Nazionale di Fisica Nucleare - Sezione di Torino Italy Dipartimento di Fisica Università di Torino Italy Osservatorio Astrofisico di Torino Istituto Nazionale di Astrofisica Italy Uninettuno University Rome Italy Agenzia Spaziale Italiana Via del Politecnico Roma00133 Italy Gran Sasso Science Institute L’Aquila Italy Institute for Cosmic Ray Research University of Tokyo Kashiwa Japan Konan Universi

Neural networks as well as other methods of machine learning (ML) are known to be highly efficient in different classification tasks, including classification of images and videos. Mini-EUSO is a wide-field-of-view imaging telescope that operates onboard the International Space Station since 2019 collecting data on miscellaneous processes that take place in the atmosphere of Earth in the UV range. Here we briefly present our results on the development of ML-based approaches for recognition and classification of track-like signals in the Mini-EUSO data, among them meteors, space debris and signals the light curves and kinematics of which are similar to those expected from extensive air showers generated by ultra-high-energy cosmic rays. We show that even simple neural networks demonstrate impressive performance in solving these tasks. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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RUBIES: Evolved Stellar Populations with Extended Formation Histories at z ∼ 7 − 8 in Candidate Massive Galaxies Identified with JWST/NIRSpec

arXiv

引用

arXiv 2024年

作者： Wang, Bingjie Leja, Joel de Graaff, Anna Brammer, Gabriel B. Weibel, Andrea van Dokkum, Pieter Baggen, Josephine F.W. Suess, Katherine A. Greene, Jenny E. Bezanson, Rachel Cleri, Nikko J. Hirschmann, Michaela Labbé, Ivo Matthee, Jorryt McConachie, Ian Naidu, Rohan P. Nelson, Erica Oesch, Pascal A. Setton, David J. Williams, Christina C. Department of Astronomy & Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational & Data Sciences The Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Max-Planck-Institut für Astronomie Königstuhl 17 HeidelbergD-69117 Germany Copenhagen Denmark Niels Bohr Institute University of Copenhagen Jagtvej 128 Copenhagen Denmark Department of Astronomy University of Geneva Chemin Pegasi 51 Versoix1290 Switzerland Department of Astronomy Yale University New HavenCT06511 United States Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States Department of Physics & Astronomy PITT PACC University of Pittsburgh PittsburghPA15260 United States Department of Physics and Astronomy Texas A&M University College StationTX77843-4242 United States George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy Texas A&M University College StationTX77843-4242 United States Institute of Physics Lab for Galaxy Evolution EPFL Observatoire de Sauverny Chemin Pegasi 51 Versoix1290 Switzerland Centre for Astrophysics and Supercomputing Swinburne University of Technology MelbourneVIC3122 Australia Am Campus 1 Klosterneuburg3400 Austria Department of Physics and Astronomy University of California Riverside RiversideCA92521 United States MIT Kavli Institute for Astrophysics and Space Research CambridgeMA02139 United States Department for Astrophysical and Planetary Science University of Colorado BoulderCO80309 United States NSF's National Optical-Infrared Astronomy Research Laboratory TucsonAZ85719 United States Steward Observatory University of Arizona TucsonAZ85721 United States

The identification of red, apparently massive galaxies at z > 7 in early James Webb Space Telescope (JWST) photometry suggests a strongly accelerated timeline compared to standard models of galaxy growth. A major uncertainty in the interpretation is whether the red colors are caused by evolved stellar populations, dust, or other effects such as emission lines or AGN. Here we show that three of the massive galaxy candidates at z = 6.7 − 8.4 have prominent Balmer breaks in JWST/NIRSpec spectroscopy from the RUBIES program. The Balmer breaks demonstrate unambiguously that stellar emission dominates at λrest = 0.4 µm, and require formation histories extending hundreds of Myr into the past in galaxies only 600-800 Myr after the Big Bang. Two of the three galaxies also show broad Balmer lines, with Hβ FWHM > 2500 km s−1, suggesting that dust-reddened AGN contribute to, or even dominate, the SEDs of these galaxies at λrest 0.6 µm. All three galaxies have relatively narrow [O iii] lines, seemingly ruling out a high-mass interpretation if the lines arise in dynamically-relaxed, inclined disks. Yet, the inferred masses also remain highly uncertain. We model the high-quality spectra using Prospector to decompose the continuum into stellar and AGN components, and explore limiting cases in stellar/AGN contribution. This produces a wide range of possible stellar masses, spanning M* ∼ 109 − 1011 M☉. Nevertheless, all fits suggest a very early and rapid formation, most of which follow with a truncation in star formation. Potential origins and evolutionary tracks for these objects are discussed, from the cores of massive galaxies to low-mass galaxies with over-massive black holes. Intriguingly, we find all of these explanations to be incomplete;deeper and redder data are needed to understand the physics of these systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Stars

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Exploring higher order images with Fe Ka-lines from relativistic disks: Black hole spin determination and bias

arXiv

引用

arXiv 2021年

作者： Falanga, M. Bakala, P. La Placa, R. De Falco, V. De Rosa, A. Stella, L. Hallerstrasse 6 Bern3012 Switzerland Research Centre for Computational Physics and Data Processing Silesian University in Opava Bezrucovo nám. 13 OpavaCZ-746 01 Czech Republic M. R. Stefánik Observatory and Planetarium Sládkovicova 41 Hlohovec920 01 Slovakia 00078 Italy Dipartimento di Fisica Università di Roma Tor Vergata Via della Ricerca Scientifica Roma00133 Italy Dipartimento di Fisica Università La Sapienza Piazzale Aldo Moro 5 Roma00185 Italy INAF - Istituto di Astrofisica e Planetologie Spaziali Via Fosso del Cavaliere Roma00133 Italy

We study the contributions to the relativistic Fe Kaline profile from higher order images (HOIs) produced by strongly deflected rays from the disk which cross the plunging region, located between the innermost stable circular orbit (ISCO) radius and the event horizon of a Kerr black hole. We investigate the characteristics features imprinted by the HOIs in the line profile for different black hole spins, disk emissivity laws and inclinations. We find that they extend from the red wing of the profile up to energies slightly lower than those of the blue peak, adding - 0.4-1.3% to the total line flux. The contribution to the specific flux is often in the - 1% to 7% range, with the highest values attained for low and negative spin (α ≥ 0.3) black holes surrounded by intermediate inclination angle (i - 40°) disks. We simulate future observations of a black hole X-ray binary system with the Large Area Detector of the planned X-ray astronomy enhanced X-ray Timing and Polarimetry Mission (eXTP) and find that the Fe Kaline profiles of systems accreting at ≥ 1% the Eddington rate are affected by the HOI features for a range of parameters. This would provide evidence of the extreme gravitational lensing of HOI rays. Our simulations show also that not accounting for HOI contributions to the Fe Kaline profile may systematically bias measurements of the black hole spin parameter towards values higher by up to - 0.3 than the inputted ones. Copyright © 2021, The Authors. All rights reserved.

关键词： Stars

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The need to implement FAIR principles in biomolecular simulations

arXiv

引用

arXiv 2024年

作者： Amaro, R. Åqvist, J. Bahar, I. Battistini, F. Bellaiche, A. Beltran, D. Biggin, P.C. Bonomi, M. Bowman, G.R. Bryce, R. Bussi, G. Carloni, P. Case, D. Cavalli, A. Chang, C.A. Cheatham, T.E. Cheung, M.S. Chipot, C. Chong, L.T. Choudhary, P. Cisneros, G.A. Clementi, C. Collepardo-Guevara, R. Coveney, P. Covino, R. Crawford, T.D. Dal Peraro, M. de Groot, B. Delemotte, L. De Vivo, M. Essex, J. Fraternali, F. Gao, J. Gelpí, J.L. Gervasio, F.L. Gonzalez-Nilo, F.D. Grubmüller, H. Guenza, M.G. Guzman, H.V. Harris, S. Head-Gordon, T. Hernandez, R. Hospital, A. Huang, N. Huang, X. Hummer, G. Iglesias-Fernández, J. Jensen, J.H. Jha, S. Jiao, W. Jorgensen, W.L. Kamerlin, S.C.L. Khalid, S. Laughton, C. Levitt, M. Limongelli, V. Lindahl, E. Lindorff-Larsen, K. Loverde, S. Lundborg, M. Luo, Y.L. Luque, F.J. Lynch, C.I. MacKerell, A. Magistrato, A. Marrink, S.J. Martin, H. McCammon, J.A. Merz, K. Moliner, V. Mulholland, A. Murad, S. Naganathan, A.N. Nangia, S. Noe, F. Noy, A. Oláh, J. O'Mara, M. Ondrechen, M.J. Onuchic, J.N. Onufriev, A. Osuna, S. Palermo, G. Panchenko, A.R. Pantano, S. Parish, C. Parrinello, M. Perez, A. Perez-Acle, T. Perilla, J.R. Pettitt, B.M. Pietropaolo, A. Piquemal, J.-P. Poma, A. Praprotnik, M. Ramos, M.J. Ren, P. Reuter, N. Roitberg, A. Rosta, E. Rovira, C. Roux, B. Röthlisberger, U. Sanbonmatsu, K. Schlick, T. Shaytan, A.K. Simmerling, C. Smith, J.C. Sugita, Y. Świderek, K. Taiji, M. Tao, P. Tikhonova, I.G. Tirado-Rives, J. Tuñón, I. Van Der Kamp, M.W. Van der Spoel, D. Velankar, S. Voth, G.A. Wade, R. Warshel, A. Welborn, V.V. Wetmore, S. Wong, C.F. Yang, L.-W. Zacharias, M. Orozco, M. Department of Molecular Biology University of California San DiegoCA United States Department of Cell and Molecular Biology Uppsala University Uppsala Sweden Laufer Center for Physical and Quantitative Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Department of Biochemistry and Cell Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Barcelona Spain European Molecular Biology Laboratory European Bioinformatics Institute Hinxton United Kingdom Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford Oxford United Kingdom Institut Pasteur Université Paris Cité CNRS UMR 3528 Computational Structural Biology Unit Paris France Department of Biochemistry and Biophysics University of Pennsylvania PhiladelphiaPA United States Division of Pharmacy and Optometry University of Manchester Manchester United Kingdom Scuola Internazionale Superiore di Studi Avanzati-SISSA Trieste Italy Computational Biomedicine Institute of Advanced Simulations IAS-5 Institute for Neuroscience and Medicine INM-9 Forschungszentrum Jülich GmbH Jülich Germany Department of Physics and Universitätsklinikum RWTH Aachen University Aachen Germany Department of Chemistry & Chemical Biology Rutgers University PiscatawayNJ United States Istituto Italiano di Tecnologia Drug Discovery and Development Bologna Italy Lausanne Switzerland Department of Chemistry University of California RiversideCA United States Department of Medicinal Chemistry College of Pharmacy University of Utah Salt Lake CityUT United States Department of Physics University of Washington SeattleWA United States Pacific Northwest National Laboratory RichlandWA United States LIA CNRS-UIUC UMR n°7019 Université de Lorraine Vandœuvre-lès-Nancy France Department of Physics University of Illinois at Urbana-Champaign UrbanaIL United States Department of Biochemistry and Molecular Biol

The communities that embraced data archiving efforts decades ago are now, in the era of data-driven biology, those gaining the most from the AI revolution. The structural biology community was a pioneer in this regard by establishing the Protein data Bank (PDB) in 1971 and making data accessible using the FAIR (Findable, Accessible, Interoperable and Reusable) principles even before these were articulated [1, 2]. The genomics/bioinformatics community has followed the example, establishing many widely used databases [3, 4]. By contrast, molecular simulation has been anchored in usage paradigms dating back to the seventies, when molecular dynamics (MD) simulation was first applied to study biomacromolecules [5]. At that time, MD was used by theoretical physicists and chemists in "proof of concept" simulations. Still, fifty years later, MD has evolved into a cornerstone molecular biology technique that can provide accurate quantitative analysis and property prediction. MD is now employed by tens of thousands of researchers worldwide, accounting for roughly 15% of global supercomputer usage. Unfortunately, these rich and costly data are not systematically maintained, and when further analyses are required, simulations have to be rerun-an unacceptable situation from scientific, environmental and sustainability standpoints. In this letter, we argue for a collaborative endeavor to archive MD simulation data and describe ongoing efforts to establish cost-effective and sustainable data archiving strategies. © 2024, CC BY-NC-SA.

关键词： Biotic

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NANOGrav 15-year gravitational-wave background methods

引用

Physical Review D 2024年第10期109卷 103012-103012页

作者： Aaron D. Johnson Patrick M. Meyers Paul T. Baker Neil J. Cornish Jeffrey S. Hazboun Tyson B. Littenberg Joseph D. Romano Stephen R. Taylor Michele Vallisneri Sarah J. Vigeland Ken D. Olum Xavier Siemens Justin A. Ellis Rutger van Haasteren Sophie Hourihane Gabriella Agazie Akash Anumarlapudi Anne M. Archibald Zaven Arzoumanian Laura Blecha Adam Brazier Paul R. Brook Sarah Burke-Spolaor Bence Bécsy J. Andrew Casey-Clyde Maria Charisi Shami Chatterjee Katerina Chatziioannou Tyler Cohen James M. Cordes Fronefield Crawford H. Thankful Cromartie Kathryn Crowter Megan E. DeCesar Paul B. Demorest Timothy Dolch Brendan Drachler Elizabeth C. Ferrara William Fiore Emmanuel Fonseca Gabriel E. Freedman Nate Garver-Daniels Peter A. Gentile Joseph Glaser Deborah C. Good Kayhan Gültekin Ross J. Jennings Megan L. Jones Andrew R. Kaiser David L. Kaplan Luke Zoltan Kelley Matthew Kerr Joey S. Key Nima Laal Michael T. Lam William G. Lamb T. Joseph W. Lazio Natalia Lewandowska Tingting Liu Duncan R. Lorimer Jing Luo Ryan S. Lynch Chung-Pei Ma Dustin R. Madison Alexander McEwen James W. McKee Maura A. McLaughlin Natasha McMann Bradley W. Meyers Chiara M. F. Mingarelli Andrea Mitridate Cherry Ng David J. Nice Stella Koch Ocker Timothy T. Pennucci Benetge B. P. Perera Nihan S. Pol Henri A. Radovan Scott M. Ransom Paul S. Ray Shashwat C. Sardesai Carl Schmiedekamp Ann Schmiedekamp Kai Schmitz Brent J. Shapiro-Albert Joseph Simon Magdalena S. Siwek Ingrid H. Stairs Daniel R. Stinebring Kevin Stovall Abhimanyu Susobhanan Joseph K. Swiggum Jacob E. Turner Caner Unal Haley M. Wahl Caitlin A. Witt Olivia Young Center for Gravitation Cosmology and Astrophysics Department of Physics University of Wisconsin-Milwaukee P.O. Box 413 Milwaukee Wisconsin 53201 USA Division of Physics Mathematics and Astronomy California Institute of Technology Pasadena California 91125 USA Department of Physics and Astronomy Widener University One University Place Chester Pennsylvania 19013 USA Department of Physics Montana State University Bozeman Montana 59717 USA Department of Physics Oregon State University Corvallis Oregon 97331 USA NASA Marshall Space Flight Center Huntsville Alabama 35812 USA Department of Physics Texas Tech University Box 41051 Lubbock Texas 79409 USA Department of Physics and Astronomy Vanderbilt University 2301 Vanderbilt Place Nashville Tennessee 37235 USA Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena California 91109 USA Institute of Cosmology Department of Physics and Astronomy Tufts University Medford Massachusetts 02155 USA Department of Astronomy University of Maryland College Park Maryland 20742 Center for Research and Exploration in Space Science and Technology NASA/GSFC Greenbelt Maryland 20771 NASA Goddard Space Flight Center Greenbelt Maryland 20771 USA Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut) Callinstrasse 38 D-30167 Hannover Germany Newcastle University NE1 7RU Newcastle United Kingdom X-Ray Astrophysics Laboratory NASA Goddard Space Flight Center Code 662 Greenbelt Maryland 20771 USA Physics Department University of Florida Gainesville Florida 32611 USA Cornell Center for Astrophysics and Planetary Science and Department of Astronomy Cornell University Ithaca New York 14853 USA Cornell Center for Advanced Computing Cornell University Ithaca New York 14853 USA Institute for Gravitational Wave Astronomy and School of Physics and Astronomy University of Birmingham Edgbaston Birmingham B15 2TT United Kingdom Department of Physics and Astronomy West

Pulsar timing arrays (PTAs) use an array of millisecond pulsars to search for gravitational waves in the nanohertz regime in pulse time of arrival data. This paper presents rigorous tests of PTA methods, examining their consistency across the relevant parameter space. We discuss updates to the 15-year isotropic gravitational-wave background analyses and their corresponding code representations. Descriptions of the internal structure of the flagship algorithms enterprise and ptmcmcsampler are given to facilitate understanding of the PTA likelihood structure, how models are built, and what methods are currently used in sampling the high-dimensional PTA parameter space. We introduce a novel version of the PTA likelihood that uses a two-step marginalization procedure that performs much faster in gravitational wave searches, reducing the required resources facilitating the computation of Bayes factors via thermodynamic integration and sampling a large number of realizations for computing Bayesian false-alarm probabilities. We perform stringent tests of consistency and correctness of the Bayesian and frequentist analysis methods. For the Bayesian analysis, we test prior recovery, simulation recovery, and Bayes factors. For the frequentist analysis, we test that the optimal statistic, when modified to account for a non-negligible gravitational-wave background, accurately recovers the amplitude of the background. We also summarize recent advances and tests performed on the optimal statistic in the literature from both gravitational wave background detection and parameter estimation perspectives. The tests presented here validate current analyses of PTA data.

关键词： Gravitational waves Gravitational wave detection

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Mass of the active galactic nucleus black hole XMMUJ134736.6+173403

arXiv

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arXiv 2019年

作者： Goluchová, K. Török, G. Šrámková, E. Abramowicz, Marek A. Stuchlík, Z. Horák, Jiří Institute of Physics Research Centre for Computational Physics and Data Processing Research Centre for Theoretical Physics and Astrophysics Faculty of Philosophy & Science Silesian University in Opava Bezručovo nám. 13 OpavaCZ-746 01 Czech Republic Astronomical Institute Boční II 1401/2a Praha 4-SpořilovCZ-14131 Czech Republic

A recent study of the X-ray source XMMUJ134736.6+173403 has revealed a strong quasi-periodic modulation of the X-ray flux. The observation of two quasiperiodic oscillations (QPOs) that occur on a daily timescale and exhibit a 3:1 frequency ratio strongly supports the evidence for the presence of an active galactic nucleus black hole (AGN BH). Assuming an orbital origin of QPOs, we calculated the upper and lower limit on AGN BH mass M and found M ≈ 107 − 109 Mo. When we compare this to mass estimates of other sources, XMMUJ134736.6+173403 appears to be the most massive source with commensurable QPO frequencies, and its mass represents the current observational upper limit on AGN BH mass based on QPO observations. We note that it will be crucial for the falsification of particular resonance models of QPOs whether only a single QPO with a frequency that completes the harmonic sequence 3: 2: 1 is found in this source, or if a new different pair of QPOs with frequencies in the 3: 2 ratio is found. The former case would agree with the prediction of the 3: 2 epicyclic resonance model and BH mass M ≈ (5a2 + 8a + 8) × 107 Mo, where a is a dimensionless BH spin. Copyright © 2019, The Authors. All rights reserved.

关键词： Stars

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

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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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Measurement of the 2νββ decay rate and spectral shape of 100Mo from the CUPID-Mo experiment

arXiv

引用

arXiv 2023年

作者： Augier, C. Barabash, A.S. Bellini, F. Benato, G. Beretta, M. Bergé, L. Billard, J. Borovlev, Yu.A. Cardani, L. Casali, N. Cazes, A. Celi, E. Chapellier, M. Chiesa, D. Dafinei, I. Danevich, F.A. De Jesus, M. Dixon, T. Dumoulin, L. Eitel, K. Ferri, F. Fujikawa, B.K. Gascon, J. Gironi, L. Giuliani, A. Grigorieva, V.D. Gros, M. Helis, D.L. Huang, H.Z. Huang, R. Imbert, L. Johnston, J. Juillard, A. Khalife, H. Kleifges, M. Kobychev, V.V. Kolomensky, Yu.G. Konovalov, S.I. Kotila, J. Loaiza, P. Ma, L. Makarov, E.P. de Marcillac, P. Mariam, R. Marini, L. Marnieros, S. Navick, X.-F. Nones, C. Norman, E.B. Olivieri, E. Ouellet, J.L. Pagnanini, L. Pattavina, L. Paul, B. Pavan, M. Peng, H. Pessina, G. Pirro, S. Poda, D.V. Polischuk, O.G. Pozzi, S. Previtali, E. Redon, Th. Rojas, A. Rozov, S. Sanglard, V. Scarpaci, J.A. Schmidt, B. Shen, Y. Shlegel, V.N. Šimkovic, F. Singh, V. Tomei, C. Tretyak, V.I. Umatov, V.I. Vagneron, L. Velázquez, M. Ware, B. Welliver, B. Winslow, L. Xue, M. Yakushev, E. Zarytskyy, M. Zolotarova, A.S. Univ Lyon Université Lyon 1 CNRS IN2P3 IP2I-Lyon VilleurbanneF-69622 France National Research Centre "Kurchatov Institute" Kurchatov Complex of Theoretical and Experimental Physics Moscow117218 Russia Dipartimento di Fisica Sapienza Università di Roma P.le Aldo Moro 2 RomeI-00185 Italy INFN Sezione di Roma P.le Aldo Moro 2 RomeI-00185 Italy INFN Laboratori Nazionali del Gran Sasso AQ AssergiI-67100 Italy INFN Gran Sasso Science Institute L’AquilaI-67100 Italy University of California BerkeleyCA94720 United States Université Paris-Saclay CNRS IN2P3 IJCLab Orsay91405 France Nikolaev Institute of Inorganic Chemistry Novosibirsk630090 Russia Dipartimento di Fisica Università di Milano-Bicocca MilanoI-20126 Italy INFN Sezione di Milano-Bicocca MilanoI-20126 Italy Institute for Nuclear Research of NASU Kyiv03028 Ukraine INFN Sezione di Roma Tor Vergata Via della Ricerca Scientifica 1 RomeI-00133 Italy IRFU CEA Université Paris-Saclay Gif-sur-YvetteF-91191 France Karlsruhe Institute of Technology Institute for Astroparticle Physics Karlsruhe76021 Germany Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Fudan University Shanghai200433 China Massachusetts Institute of Technology CambridgeMA02139 United States Karlsruhe Institute of Technology Institute for Data Processing and Electronics Karlsruhe76021 Germany National Research Centre Kurchatov Institute Institute of Theoretical and Experimental Physics Moscow117218 Russia Department of Physics University of Jyväskylä PO Box 35 JyväskyläFI-40014 Finland Finnish Institute for Educational Research University of Jyväskylä P.O. Box 35 JyvaäskyläFI-40014 Finland Center for Theoretical Physics Sloane Physics Laboratory Yale University New HavenCT06520-8120 United States Physik Department Technische Universität München GarchingD-85748 Germany Department of Modern Physics University of Science and Technology of China Hefei230027 China LSM Laboratoir

Neutrinoless double beta decay (0νββ) is a yet unobserved nuclear process which would demonstrate Lepton Number violation, a clear evidence of beyond Standard Model physics. The process two neutrino double beta decay (2νββ) is allowed by the Standard Model and has been measured in numerous experiments. In this letter, we report a measurement of 2νββ decay half-life of 100Mo to the ground state of 100Ru of (7.07 ± 0.02 (stat.) ± 0.11 (syst.)) × 1018 yr by the CUPID-Mo experiment. With a relative precision of ± 1.6 % this is the most precise measurement to date of a 2νββ decay rate in 100Mo. In addition, we constrain higher-order corrections to the spectral shape which provides complementary nuclear structure information. We report a novel measurement of the shape factor ξ3,1 = 0.45 ±0.03 (stat.) ±0.05 (syst.), which is compared to theoretical predictions for different nuclear models. We also extract the first value for the effective axial vector coupling constant obtained from a spectral shape study of 2νββ decay. © 2023, CC BY.

关键词： Ground state

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UNCOVER: JWST Spectroscopy of Three Cold Brown Dwarfs at Kiloparsec-scale Distances

arXiv

引用

arXiv 2023年

作者： Burgasser, Adam J. Bezanson, Rachel Labbe, Ivo Brammer, Gabriel Cutler, Sam E. Furtak, Lukas J. Greene, Jenny E. Gerasimov, Roman Leja, Joel Pan, Richard Price, Sedona H. Wang, Bingjie Weaver, John R. Whitaker, Katherine E. Fujimoto, Seiji Kokorev, Vasily Dayal, Pratika Nanayakkara, Themiya Williams, Christina C. Marchesini, Danilo Zitrin, Adi van Dokkum, Pieter Department of Astronomy & Astrophysics UC San Diego La Jolla CA92093 United States Department of Physics and Astronomy PITT PACC University of Pittsburgh PittsburghPA15260 United States Centre for Astrophysics and Supercomputing Swinburne University of Technology MelbourneVIC3122 Australia Niels Bohr Institute University of Copenhagen Jagtvej 128 København NDK-2200 Denmark Department of Astronomy University of Massachusetts AmherstMA01003 United States Physics Department Ben-Gurion University of the Negev P.O. Box 653 Be’er-Sheva84105 Israel Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Department of Physics UC San Diego La Jolla CA92093 United States Department of Physics & Astronomy University of Notre Dame Notre DameIN46556 United States Department of Astronomy & Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational & Data Sciences The Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Department of Physics and Astronomy Tufts University 574 Boston Ave. MedfordMA02155 United States Denmark Department of Astronomy The University of Texas at Austin AustinTX78712 United States Kapteyn Astronomical Institute University of Groningen Groningen9700 AV Netherlands Centre for Astrophysics and Supercomputing Swinburne University of Technology PO Box 218 HawthornVIC3122 Australia NSF’s National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Avenue TucsonAZ85719 United States Department of Physics & Astronomy Tufts University MA02155 United States

We report JWST/NIRSpec spectra of three distant T-type brown dwarfs identified in the Ultradeep NIRSpec and NIRCam ObserVations before the Epoch of Reionization (UNCOVER) survey of the Abell 2744 lensing field. One source was previously reported as a candidate T dwarf on the basis of NIRCam photometry, while two sources were initially identified as candidate active galactic nuclei. Low-resolution 1–5 µm spectra confirm the presence of molecular features consistent with T dwarf atmospheres, and comparison to spectral standards infers classifications of sdT1, T6, and T8–T9. The warmest source, UNCOVER-BD-1, shows evidence of subsolar metallicity, and atmosphere model fits indicates Teff = 1300 K and [M/H] ∼ −1.0, making this one of the few spectroscopically-confirmed T subdwarfs known. The coldest source, UNCOVER-BD-3, is near the T/Y dwarf boundary with Teff = 550 K, and our analysis indicates the presence of PH3 in the 3–5 µm region, favored over CO2 and a possible indicator of subsolar metallicity. We estimate distances of 0.9–4.5 kpc from the Galactic midplane, making these the most distant brown dwarfs with spectroscopic confirmation. Population simulations indicate high probabilities of membership in the Galactic thick disk for two of these brown dwarfs, and potential halo membership for UNCOVER-BD-1. Our simulations indicate that there are approximately 5 T dwarfs and 1–2 L dwarfs in the Abell 2744 field down to F444W = 30 AB mag, roughly one-third of which are thick disk members. These results highlight the utility of deep JWST/NIRSpec spectroscopy for identifying and characterizing the oldest metal-poor brown dwarfs in the Milky Way. © 2023, CC BY.

关键词： Astrophysics

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ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -XXI. A Large-sample Observational Study of Ethanol and Dimethyl Ether in Hot Cores

arXiv

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arXiv 2025年

作者： Kou, Zhiping Li, Xiaohu Qin, Sheng-Li Liu, Tie Mannfors, E. Tang, Xindi Gorai, Prasanta Garay, Guido Das, Swagat R. García, Pablo Bronfman, Leonardo Juvela, M. Chen, Li Liu, Xunchuan Sanhueza, Patricio Peng, Yaping Chen, Long-Fei Zou, Jiahang Yang, Dongting Tóth, L. Viktor Dewangan, Lokesh Liu, Hong-Li Chibueze, James O. Li, Ziyang Xinjiang Astronomical Observatory Chinese Academy of Sciences 150 Science 1-Stree Urumqi Xinjiang830011 China University of Chinese Academy of Sciences Beijing100049 China School of Physics and Astronomy Yunnan University Kunming650091 China Xinjiang Key Laboratory of Radio Astrophysics 150 Science 1-Street Urumqi Xinjiang830011 China Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Department of Physics University of Helsinki PO Box 64 Helsinki00014 Finland Rosseland Centre for Solar Physics University of Oslo PO Box 1029 Blindern Oslo0315 Norway Institute of Theoretical Astrophysics University of Oslo PO Box 1029 Blindern Oslo0315 Norway Departamento de Astronomía Universidad de Chile Las Condes Santiago7591245 Chile Chinese Academy of Sciences South America Center for Astronomy National Astronomical Observatories CAS Beijing100101 China Department of Earth and Planetary Sciences Institute of Science Tokyo Meguro Tokyo152-8551 Japan National Astronomical Observatory of Japan National Institutes of Natural Sciences 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Astronomical Science SOKENDAI The Graduate University for Advanced Studies 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Physics Faculty of Science Kunming University of Science and Technology Kunming650500 China School of Physics and Electronic Science Guizhou Normal University Guiyang550025 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guiyang550025 China Department of Astronomy Eötvös Loránd University Pázmány Péter sétány 1/A BudapestH-1117 Hungary University of Debrecen Faculty of Science and Technology Egyetemtér 1 DebrecenH-4032 Hungary Physical Research Laboratory Navrangpura Ahmedabad380 009 India Department of Mathematical Sciences University of South Africa Cnr Christian de Wet Rd and Pioneer Avenue Florida Park Roodepoort1709 South Africa Centre for Sp

Hot cores, as a stage of massive star formation, exhibit abundant line emissions of COMs. We present a deep line survey of two isomers of C2H6O: ethanol (C2H5OH;EA), and dimethyl ether (CH3OCH3;DE) as well as their possible precursor CH3OH towards 60 hot cores by using the ALMA 3 mm line observations. EA is detected in 40 hot cores and DE is detected in 59 hot cores. Of these, EA and DE are simultaneously detected in 39 hot cores. We calculate rotation temperatures and column densities of EA and DE by using the XCLASS software. The average rotation temperature of EA is higher than that of DE, whereas the average column density of EA is lower than that of DE. Combined with previous studies of hot cores and hot corinos, we find strong column density correlations among EA and DE (ρ = 0.92), EA and CH3OH (ρ = 0.82), as well as DE and CH3OH (ρ = 0.80). The column density ratios of EA/DE versus the column densities of CH3OH remain nearly constant with values within ~1 order of magnitude. These strong correlations and the stable ratios, suggest that EA, DE, and CH3OH could be chemically linked, with CH3OH potentially serving as a precursor for EA and DE. Compared with chemical models, the three different warm-up timescale models result in the systematic overproduction of EA and the systematic underproduction of DE. Therefore, our large sample observations can provide crucial constraints on chemical models. Copyright © 2025, The Authors. All rights reserved.

关键词： Giant stars

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