10 papers
Gravitational-wave surrogate models powered by artificial neural networks: The ANN-Sur for waveform generation
Sebastian Khan, Rhys Green
Inferring the properties of black holes and neutron stars is a key science goal of gravitational-wave (GW) astronomy. To extract as much information as possible from GW observation…
MADMAX Status Report
S. Beurthey, N. Böhmer, P. Brun +42
In this report we present the status of the MAgnetized Disk and Mirror Axion eXperiment (MADMAX), the first dielectric haloscope for the direct search of dark matter axions in the…
Modeling the gravitational wave signature of neutron star black hole coalescences: PhenomNSBH
Jonathan E. Thompson, Edward Fauchon-Jones, Sebastian Khan +4
Accurate gravitational-wave (GW) signal models exist for black hole binary (BBH) and neutron-star binary (BNS) systems, which are consistent with all of the published GW observatio…
Including higher order multipoles in gravitational-wave models for precessing binary black holes
Sebastian Khan, Frank Ohme, Katerina Chatziioannou +1
Estimates of the source parameters of gravitational-wave (GW) events produced by compact binary mergers rely on theoretical models for the GW signal. We present the first frequency…
Multi-waveform inference of gravitational waves
Gregory Ashton, Sebastian Khan
Bayesian inference of gravitational wave signals is subject to systematic error due to modelling uncertainty in waveform signal models, coined approximants. A growing collection of…
Improving the NRTidal model for binary neutron star systems
Tim Dietrich, Anuradha Samajdar, Sebastian Khan +3
Accurate and fast gravitational waveform (GW) models are essential to extract information about the properties of compact binary systems that generate GWs. Building on previous wor…