Machine Learning in Gravitational Wave Data Analysis and Heirarchical Mergers of Compact Binaries
ORAL · G13 · ID: 2275336
Presentations
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A machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences
ORAL
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Presenters
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William Benoit
University of Minnesota
Authors
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William Benoit
University of Minnesota
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Ethan J Marx
Massachusetts Institute of Technology
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Alec M Gunny
Massachusetts Institute of Technology
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Rafia Omer
University of Minnesota
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Deep Chatterjee
Massachusetts Institute of Technology
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Muhammed Saleem
University of Minnesota
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Eric Moreno
Massachusetts Institute of Technology
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Ryan J Raikman
Carnegie Mellon University
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Ekaterina Govorkova
Massachusetts Institute of Technology
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Michael W Coughlin
University of Minnesota
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Erik Katsavounidis
MIT
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Abstract Withdrawn
ORAL Withdrawn
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Gravitational-Wave Searches for Cosmic String Cusps in Einstein Telescope Data using Deep Learning
ORAL
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Publication: Preprint submitted to arXiv (2308.12323v1 [astro-ph.IM]), accepted for publication in Physical Review D
Presenters
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Quirijn Meijer
Utrecht University
Authors
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Quirijn Meijer
Utrecht University
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Melissa Lopez
Utrecht University
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Daichi Tsuna
California Institute of Technology
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Sarah Caudill
University of Massachusetts Dartmouth
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Neural network enhanced rapid interpolation of gravitational-waveforms
ORAL
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Presenters
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Richard George
University of Texas at Austin
Authors
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Richard George
University of Texas at Austin
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RYAN MAGEE
LIGO Laboratory, Caltech
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Alvin Ka Yue Li
LIGO Laboratory, Caltech
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Ritwick Sharma
University of Delhi
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Identifying Correlations in Precessing Gravitational-Wave Signals with Machine Learning
ORAL
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Presenters
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Karen Kang
Amherst College
Authors
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Karen Kang
Amherst College
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Simona J Miller
Caltech
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Deborah Ferguson
University of Illinois Urbana-Champaign
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Katerina Chatziioannou
Caltech
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Abstract Withdrawn
ORAL Withdrawn
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Abstract Withdrawn
ORAL Withdrawn
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Abstract Withdrawn
ORAL Withdrawn
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"Birth kick" estimates of second-generation black holes observed by LIGO-Virgo: implications for formation channels and host environments
ORAL
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Presenters
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Anna Liu
The Chinese University of Hong Kong
Authors
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Anna Liu
The Chinese University of Hong Kong
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Juan Calderón Bustillo
University of Santiago de Compostela, Instituto Galego de F´ısica de Altas Enerx´ıas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Galicia, Spain
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Carlos Araujo-Alvarez
University of Santiago de Compostela and University of La Laguna
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Henry W. Y. Wong
The Chinese University of Hong Kong
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