No three-body encounter signatures detected in GW170817, GW190814, and GW230627_015337, constraining intermediate-mass black holes above 100 solar masses within roughly 0.1 AU of these binaries.
Garc ´ıa-Bellido, S
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Numerical relativity in the decoupling limit reveals dynamical scalarization and spin-induced (de)scalarization during hyperbolic black hole encounters for both signs of the coupling.
Scattering black holes gain spin and mass by absorbing emitted gravitational radiation, with spin-up up to 0.3 and mass gain up to 15% in near-threshold encounters.
Reanalysis finds GW190521 prefers hyperbolic waveforms over quasi-circular precessing ones with ln Bayes factor 3.71, while other high-mass events and GW231123 favor the latter; mock signals indicate distinguishability challenges for high-mass precessing cases.
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
citing papers explorer
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How lonely are the Binary Compact Objects Detected by the LIGO-Virgo-KAGRA Collaboration?
No three-body encounter signatures detected in GW170817, GW190814, and GW230627_015337, constraining intermediate-mass black holes above 100 solar masses within roughly 0.1 AU of these binaries.
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Scalarization and descalarization in hyperbolic encounters of black holes
Numerical relativity in the decoupling limit reveals dynamical scalarization and spin-induced (de)scalarization during hyperbolic black hole encounters for both signs of the coupling.
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Spin-up and mass-gain in hyperbolic encounters of spinning black holes
Scattering black holes gain spin and mass by absorbing emitted gravitational radiation, with spin-up up to 0.3 and mass gain up to 15% in near-threshold encounters.
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Gravitational Wave Hyperbolic Catalog: Reanalyzing High-Mass Gravitational Wave Signals Using Hyperbolic Waveforms
Reanalysis finds GW190521 prefers hyperbolic waveforms over quasi-circular precessing ones with ln Bayes factor 3.71, while other high-mass events and GW231123 favor the latter; mock signals indicate distinguishability challenges for high-mass precessing cases.
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Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.