Inferring physical properties of stellar collapse by third-generation gravitational-wave detectors
Chaitanya Afle, Duncan A Brown

TL;DR
This paper demonstrates how third-generation gravitational-wave detectors can accurately infer physical properties of stellar core collapse supernovae, such as rotation and oscillation frequency, using simulated waveform analysis and Bayesian inference.
Contribution
It introduces a method combining principal component analysis and Bayesian inference to extract progenitor properties from gravitational-wave signals, improving parameter estimation for future detectors.
Findings
Advanced LIGO can estimate core rotation with 0.004 credible interval at 8.1 kpc
Cosmic Explorer can measure post-bounce oscillation frequency within 5 Hz
Detection in Magellanic Clouds is feasible with Cosmic Explorer but not with Advanced LIGO
Abstract
Galactic core-collapse supernovae are among the possible sources of gravitational waves. We investigate the ability of gravitational-wave observatories to extract the properties of the collapsing progenitor from the gravitational waves radiated. We use simulations of supernovae that explore a variety of progenitor core rotation rates and nuclear equations of state and examine the ability of current and future observatories to determine these properties using gravitational-wave parameter estimation. We use principal component analysis of the simulation catalog to determine the dominant features of the waveforms and create a map between the measured properties of the waveform and the physical properties of the progenitor. We use Bayesian parameter inference and the parameter map to calculate posterior probabilities for the physical properties given a gravitational-wave observation. We…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Stellar, planetary, and galactic studies · Gamma-ray bursts and supernovae
