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Self-consistent treatment of thermal effects in neutron-star post-mergers: observational implications for third-generation gravitational-wave detectors
Verónica Villa-Ortega, Ana Lorenzo-Medina, Juan Calderón Bustillo +4
We assess the impact of accurate, self-consistent modelling of thermal effects in neutron-star merger remnants in the context of third-generation gravitational-wave detectors. This…
Impact of Bayesian Priors on the Inferred Masses of Quasi-Circular Intermediate-Mass Black Hole Binaries
Koustav Chandra, Archana Pai, Samson H. W. Leong +1
Observation of gravitational waves from inspiralling binary black holes has offered a unique opportunity to study the physical parameters of the component black holes. To infer the…
A Joint Fermi-GBM and Swift-BAT Analysis of Gravitational-Wave Candidates from the Third Gravitational-wave Observing Run
C. Fletcher, J. Wood, R. Hamburg +1696
We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational wave (GW) candidate even…
Impact of ringdown higher-order modes on black-hole mergers in dense environments: the scalar field case, detectability and parameter biases
Samson H. W. Leong, Juan Calderón Bustillo, Miguel Gracia-Linares +1
Dense environments hosting compact binary mergers can leave an imprint on the gravitational-wave emission which, in turn, can be used to identify the characteristics of the environ…
Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo
The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration +1772
Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Or…
Comparison of neural network architectures for feature extraction from binary black hole merger waveforms
Osvaldo Gramaxo Freitas, Juan Calderón Bustillo, José A. Font +3
We evaluate several neural-network architectures, both convolutional and recurrent, for gravitational-wave time-series feature extraction by performing point parameter estimation o…