5 papers
Parameter Estimation Horizon of Core-Collapse Supernovae with a Network of Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Solange Nunes +3
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…
Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Daniil Orel +8
Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova cent…
Toward More Realistic Machine-Learning Inference of the Dense-Matter Equation of State from Supernova Gravitational Waves
Almat Akhmetali, Y. Sultan Abylkairov, Marat Zaidyn +6
Gravitational waves from core-collapse supernovae offer a unique probe of the equation of state (EOS) of dense nuclear matter. For rapidly rotating stars, previous machine-learning…
Assessing the Distance for Probing the Nuclear Equation of State with Supernova Gravitational Waves
Y. Sultan Abylkairov, Matthew C. Edwards, Artyom Ostrikov +6
Gravitational waves from core-collapse supernovae provide a unique probe of the equation of state (EOS) of high density matter. In this work, we focus on the bounce signal from num…
Evaluating Machine Learning Models for Supernova Gravitational Wave Signal Classification
Y. Sultan Abylkairov, Matthew C. Edwards, Daniil Orel +3
We investigate the potential of using gravitational wave (GW) signals from rotating core-collapse supernovae to probe the equation of state (EOS) of nuclear matter. By generating G…