3 papers
gr-qc2026
From the Early Slope to Curvature: Future Prospects and challenges for Astrophysical Parameter Estimation Using the Core-Collapse Supernova High-Frequency Feature
Alejandro Casallas-Lagos, Marek SzczepaÅczyk, Michele Zanolin +1
Gravitational-wave (GW) signals from core-collapse supernovae (CCSNe) contain both stochastic and deterministic components. Among these, the High-Frequency Feature (HFF), associate…
gr-qc2026
Classifying the nuclear equation of state in LVK interferometric noise through core-collapse supernova gravitational-wave signatures using convolutional neural networks
Alejandro Casallas-Lagos, Marek J. SzczepaÅczyk, Michele Zanolin +4
This paper presents a convolutional neural network (CNN) approach to classifying the nuclear equation of state (EOS). As illustrative examples, we use five two-dimensional core-col…
gr-qc2026
The impact of physically motivated calibration errors on search pipeline detection parameters for broadband burst Signals
Milan Wils, Brad Ratto, Jeffrey S. Kissel +4
Imperfections in the calibration of gravitational wave observatories introduce frequency dependent amplitude and phase errors on the measured GW signal. Previous unmodelled burst s…