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检索条件"机构=Ciela—Montreal Institute for Astrophysical Data Analysis and Machine Learning"
35 条 记 录,以下是1-10 订阅
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IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors
arXiv
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arXiv 2025年
作者: Dia, Noé Yantovski-Barth, M.J. Adam, Alexandre Bowles, Micah Perreault-Levasseur, Laurence Hezaveh, Yashar Scaife, Anna Université de Montréal Montréal Canada Mila - Quebec Artificial Intelligence Institute Montréal Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Department of Astrophysics University of Oxford Oxford United Kingdom Flatiron Institute Center for Computational Astrophysics New York United States Perimeter Institute Waterloo Canada Trottier Space Institute McGill University Montréal Canada University of Manchester Manchester United Kingdom The Alan Turing Institute United Kingdom
Inferring sky surface brightness distributions from noisy interferometric data in a principled statistical framework has been a key challenge in radio astronomy. In this work, we introduce Imaging for Radio Interferom... 详细信息
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Sharpening the dark matter signature in gravitational waveforms. II. Numerical simulations
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Physical Review D 2025年 第6期111卷 063071-063071页
作者: Bradley J. Kavanagh Theophanes K. Karydas Gianfranco Bertone Pierfrancesco Di Cintio Mario Pasquato Instituto de Física de Cantabria (IFCA UC-CSIC) Avenue de Los Castros s 39005 Santander Spain Gravitation Astroparticle Physics Amsterdam (GRAPPA) Institute for Theoretical Physics Amsterdam and Delta Institute for Theoretical Physics University of Amsterdam Science Park 904 1098 XH Amsterdam The Netherlands Consiglio Nazionale delle Ricerche Istituto dei Sistemi Complessi (CNR-ISC) via Madonna del Piano 17 50022 Sesto Fiorentino (FI) Italy INAF-Osservatorio Astronomico di Arcetri Largo Enrico Fermi 5 50125 Firenze Italy INFN-Sezione di Firenze Via Giovanni Sansone 1 50022 Sesto Fiorentino Italy Département de Physique Université de Montréal 1375 Avenue Thérèse-Lavoie-Roux Montréal Canada Mila—Quebec Artificial Intelligence Institute 6666 Rue Saint-Urbain Montréal Canada Ciela—Montréal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Dipartimento di Fisica e Astronomia Università di Padova Vicolo dell’Osservatorio 5 Padova Italy Istituto Nazionale di Fisica Nucleare Padova Via Marzolo 8 Padova Italy
Future gravitational wave observatories can probe dark matter by detecting the dephasing in the waveform of binary black hole mergers induced by dark matter overdensities. Such a detection hinges on the accurate model...
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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 t... 详细信息
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Beyond Gaussian Noise: A Generalized Approach to Likelihood analysis with non-Gaussian Noise
arXiv
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arXiv 2023年
作者: Legin, Ronan Adam, Alexandre Hezaveh, Yashar Levasseur, Laurence Perreault Department of Physics Université de Montréal Montréal Canada Ciela Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Mila Quebec Artificial Intelligence Institute Montréal Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States
Likelihood analysis is typically limited to normally distributed noise due to the difficulty of determining the probability density function of complex, high-dimensional, non-Gaussian, and anisotropic noise. This is a... 详细信息
来源: 评论
Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference machines
arXiv
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arXiv 2023年
作者: Adam, Alexandre Perreault-Levasseur, Laurence Hezaveh, Yashar Welling, Max Department of Physics Université de Montréal Montréal Canada Mila - Quebec Artificial Intelligence Institute Montréal Canada Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Microsoft Research AI4Science
Modeling strong gravitational lenses in order to quantify the distortions in the images of background sources and to reconstruct the mass density in the foreground lenses has been a difficult computational challenge. ... 详细信息
来源: 评论
Active learning meets fractal decision boundaries: a cautionary tale from the Sitnikov three-body problem
arXiv
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arXiv 2023年
作者: Payot, Nicolas Pasquato, Mario Trani, Alessandro Alberto Hezaveh, Yashar Perreault-Levasseur, Laurence Département de Physique Université de Montréal Mila Quebec Artificial Intelligence Institute Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Canada Dipartimento di Fisica e Astronomia Università di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Niels Bohr Institute Copenhagen Denmark Research Center for the Early Universe School of Science The University of Tokyo Tokyo Japan Okinawa Institute of Science and Technology Okinawa Japan
Chaotic systems such as the gravitational N-body problem are ubiquitous in astronomy. machine learning (ML) is increasingly deployed to predict the evolution of such systems, e.g. with the goal of speeding up simulati... 详细信息
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learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies
arXiv
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arXiv 2023年
作者: Payot, Nicolas Lemos, Pablo Perreault-Levasseur, Laurence Cuesta-Lazaro, Carolina Modi, Chirag Hezaveh, Yashar Département de Physique Université de Montréal Mila Quebec Artificial Intelligence Institute Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Canada Center for Computational Astrophysics Flatiron Institute NY United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions Massachusetts Institute of Technology CambridgeMA United States Center for Astrophysics Harvard & Smithsonian CambridgeMA United States Center for Computational Mathematics Flatiron Institute NY United States
Particle-mesh simulations trade small-scale accuracy for speed compared to traditional, computationally expensive N-body codes in cosmological simulations. In this work, we show how a data-driven model could be used t... 详细信息
来源: 评论
Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization
arXiv
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arXiv 2024年
作者: Legin, Ronan Isi, Maximiliano Wong, Kaze W.K. Hezaveh, Yashar Perreault-Levasseur, Laurence Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning MontréalQC Canada Department of Physics Université de Montréal MontréalQC Canada Mila - Quebec Artificial Intelligence Institute MontréalQC Canada Center for Computational Astrophysics Flatiron Institute New YorkNY United States Department of Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD United States Trottier Space Institute MontréalQC Canada Perimeter Institute for Theoretical Physics WaterlooON Canada
Gravitational-wave (GW) parameter estimation typically assumes that instrumental noise is Gaussian and stationary. Obvious departures from this idealization are typically handled on a case-by-case basis, e.g., through... 详细信息
来源: 评论
Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations
arXiv
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arXiv 2024年
作者: Stone, Connor Adam, Alexandre Coogan, Adam Yantovski-Barth, M.J. Filipp, Andreas Setiawan, Landung Core, Cordero Legin, Ronan Wilson, Charles Barco, Gabriel Missael Hezaveh, Yashar Perreault-Levasseur, Laurence Ciela Institute Montréal Institute for Astrophysical Data Analysis and Machine Learning MontréalQC Canada Department of Physics Université de Montréal MontréalQC Canada Mila Québec Artificial Intelligence Institute MontréalQC Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States eScience Institute Scientific Software Engineering Center 1410 NE Campus Pkwy SeattleWA98195 United States
Gravitational lensing is the deflection of light rays due to the gravity of intervening masses. This phenomenon is observed in a variety of scales and configurations, involving any non-uniform mass such as planets, st... 详细信息
来源: 评论
The Nearly Universal Disk Galaxy Rotation Curve
arXiv
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arXiv 2024年
作者: Patel, Raj Arora, Nikhil Courteau, Stephane Stone, Connor Frosst, Matthew Widrow, Lawrence Department of Physics Engineering Physics & Astronomy Queen’s University KingstonONK7L 3N6 Canada Department of Physics Université de Montréal MontréalQC Canada Mila Québec Artificial Intelligence Institute MontréalQC Canada Ciela Montréal Institute for Astrophysical Data Analysis and Machine Learning MontréalQC Canada ICRAR M468 University of Western Australia CrawleyWA6009 Australia
The Universal Rotation Curve (URC) of disk galaxies was originally proposed to predict the shape and amplitude of any rotation curve (RC) based solely on photometric data. Here, the URC is investigated with an extensi... 详细信息
来源: 评论