LISA Data Analysis
ORAL · G05 · ID: 2275334
Presentations
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Quasimonochromatic LISA Sources in the Frequency Domain
ORAL
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Publication: arXiv.org: 2312.00121
Presenters
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Vladimir Strokov
Johns Hopkins University
Authors
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Vladimir Strokov
Johns Hopkins University
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Emanuele Berti
Johns Hopkins University
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Identifying loud gravitational-wave bursts from galactic black hole binaries with LISA
ORAL
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Presenters
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Alan M Knee
University of British Columbia
Authors
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Alan M Knee
University of British Columbia
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Jessica McIver
University of British Columbia
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Smadar Naoz
UCLA
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Bao-Minh Hoang
UCLA
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Isobel M Romero-Shaw
Cambridge University
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Searches for Gravitational Waves in LISA Data
ORAL
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Presenters
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Matthew C Digman
Vanderbilt University
Authors
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Matthew C Digman
Vanderbilt University
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Discovering neutron stars with LISA via measurements of orbital eccentricity in Galactic binaries
ORAL
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Publication: Moore C. J., et al., 2023, arXiv e-prints, arXiv:2310.06568
Presenters
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Eliot Finch
California Institute of Technology
Authors
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Eliot Finch
California Institute of Technology
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Christopher J Moore
University of Birmingham
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Antoine Klein
University of Birmingham
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Valeriya Korol
Max Planck Institute for Astrophysics
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Nhat Pham
University of Birmingham
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Daniel Robins
University of Birmingham
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Incorporating distance information to a LISA Ultra-Compact Binary data pipeline
ORAL
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Presenters
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Michael Tauraso
University of Washington
Authors
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Michael Tauraso
University of Washington
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Towards an Early Warning Search for LISA Massive Black Holes
ORAL
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Publication: Planned paper: "Low-latency search and early warning alerts for LISA massive black holes"
Presenters
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Debnandini Mukherjee
University of Alabama Huntsville (NASA-MSFC)
Authors
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Debnandini Mukherjee
University of Alabama Huntsville (NASA-MSFC)
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Tyson Littenberg
NASA Marshall Space Flight Center
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Neil J Cornish
Montana State University
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The Gravitational Wave Peep and Its Implication for LISA Signal Confusion Noise
ORAL
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Publication: Daniel J Oliver, Aaron D Johnson, Joel Berrier, Kostas Glampedakis, Daniel Kennefick. (preprint - https://arxiv.org/abs/2305.05793)
Presenters
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Daniel J Oliver
University of Arkansas
Authors
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Daniel J Oliver
University of Arkansas
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Aaron D Johnson
Caltech
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Lena Janssen
University of Nebraska-Kearney
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Joel Berrier
University of Nebraska-Kearney
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Kostas Glampedakis
University of Murcia
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Daniel Kennefick
University of Arkansas
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A weakly-parametric approach to stochastic background inference in LISA
ORAL
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Publication: F. Pozzoli, R. Buscicchio, C. J. Moore, F. Haardt, and A. Sesana, arXiv e-prints (2023), arXiv:2311.12111 [astro-<br>ph.CO].
Presenters
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Federico Pozzoli
University of Insubria
Authors
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Federico Pozzoli
University of Insubria
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Riccardo Buscicchio
Università degli studi di Milano-Bicocca
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Christopher J Moore
University of Birmingham
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Francesco Haardt
University of Insubria
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Alberto Sesana
Università degli studi di Milano-Bicocca
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Resolving Structure in the Stochastic Gravitational-Wave Power Spectrum with LISA Using Non-parametric Methods
ORAL
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Presenters
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Guangyi Zhang
Reed College
Authors
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Guangyi Zhang
Reed College
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Sharan Banagiri
Northwestern University
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Katelyn Breivik
Department of Physics, McWilliams Center for Cosmology and Astrophysics, Carnegie Mellon University
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