Parameter Estimation Horizon of Core-Collapse Supernovae with a Network of Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Solange Nunes, José Antonio Font, Michele Zanolin, Ernazar Abdikamalov
astro-ph.HE, astro-ph.CO, astro-ph.IM
Submitted: 2026-08-03
Comments: Submitted to PRD. Comments are welcome
License: http://creativecommons.org/licenses/by/4.0/
The gist: Core-collapse supernovae are among the most promising yet still undetected sources of gravitational waves.
Terminology
Abstract
Core-collapse supernovae are among the most promising yet still undetected sources of gravitational waves. A future detection would provide a direct view of the physical processes occurring deep inside a collapsing star. In this work, we investigate how networks of current and future gravitational-wave detectors can constrain the properties of rapidly rotating core-collapse supernovae using their characteristic core-bounce and early post-bounce signals. Using deep-learning techniques, we estimate the peak frequency, rotation rate, and signal amplitude from noisy detector data and compare the performance of different detector-network configurations. We find that detector networks improve both parameter recovery and sky coverage. For current-generation networks, estimation of the peak frequency is possible out to about 30 kpc, while the rotation rate and signal amplitude remain recoverable out to distances exceeding 100 kpc. Third-generation observatories extend these distances by nearly an order of magnitude.
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