Gravitational Wave Populations
ORAL · J09 ·
Presentations
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Binary black hole merger rates in rapid population-synthesis codes and the impact of improved modeling of binary physics
ORAL
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Authors
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Monica Gallegos-Garcia
- Northwestern University
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Kaliroë Pappas
- Massachusetts Institute of Technology
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Pablo Marchant
- Katholieke Universiteit Leuven
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Christopher Berry
- Northwestern University
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Vicky Kalogera
- Northwestern University
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Relativistic Three-body Effects in Hierarchical Triples
ORAL
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Authors
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Halston Lim
- Massachusetts Institute of Technology MIT
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Carl Rodriguez
- Harvard
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Black Hole Coagulation: Modeling Hierarchical Mergers in Black Hole Populations
ORAL
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Authors
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Zoheyr Doctor
- The University of Oregon
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Daniel Wysocki
- RIT
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Richard O'Shaughnessy
- RIT
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Daniel Holz
- University of Chicago
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Ben Farr
- The University of Oregon
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Highly Spinning and Misaligned Binary Black Holes from the Isolated Formation Channel
ORAL
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Authors
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Nathan Steinle
- University of Texas at Dallas
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Michael Kesden
- University of Texas at Dallas
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Measuring the Peak of the Binary Black Hole Redshift Distribution
ORAL
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Authors
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Thomas Callister
- Simons Foundation
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Maya Fishbach
- University of Chicago
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Daniel Holz
- University of Chicago
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Will Farr
- Simons Foundation, Stony Brook University
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Distinguishing high-mass binary neutron stars from binary black holes
ORAL
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Authors
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Nathan Johnson-McDaniel
- University of Cambridge
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An Chen
- University College London
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Tim Dietrich
- Nikhef
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Reetika Dudi
- Albert-Einstein-Institut Potsdam-Golm
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Machine learning in gravitational wave population analysis
ORAL
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Authors
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Wang Kei Wong
- Johns Hopkins University
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Shirley Ho
- Flatiron institute
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Emanuele Berti
- Johns Hopkins University
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Properties of Select Compact Object Merger from the Advanced LIGO-Virgo Observing Run O3a and Relevant Astrophysics Implications
ORAL
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Authors
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Charlie Hoy
- Cardiff University
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Phenomenologically reconstructing properties of multiple compact binary merger populations: the small-$N$ limit
ORAL
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Authors
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Daniel Wysocki
- Rochester Institute of Technology
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Richard O'Shaughnessy
- Rochester Institute of Technology
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