Related papers: Lightning-Fast Gravitational Wave Parameter Infere…
Since the first detection of gravitational waves in 2015 by LIGO from the binary black hole merger GW150914, gravitational-wave astronomy has developed significantly, with over 200 compact binary merger events cataloged. The use of neural…
We present in this paper a Bayesian parameter estimation method for the analysis of interferometric gravitational wave observations of an inspiral of binary compact objects using data recorded simultaneously by a network of several…
In this study, we employ a convolutional neural network to classify gravitational waves originating from core-collapse supernovae. Training is conducted using spectrograms derived from three-dimensional numerical simulations of waveforms,…
Coalescing compact binary systems consisting of neutron stars and/or black holes should be detectable with upcoming advanced gravitational-wave detectors such as LIGO, Virgo, GEO and {KAGRA}. Gravitational-wave experiments to date have been…
Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave…
Gravitational waves carry unique information about high-energy astrophysical events such as the inspiral and merger of neutron stars and black holes, core collapse in massive stars, and other sources. Large gravitational wave (GW) detectors…
The Advanced LIGO and Virgo gravitational wave observatories have opened a new window with which to study the inspiral and mergers of binary compact objects. These observations are most powerful when coordinated with multi-messenger…
Weakly-modelled searches for gravitational waves are essential for ensuring that all potential sources are accounted for in detection efforts, as they make minimal assumptions regarding source morphology. While these searches primarily…
Based on the prior O1-O2 observing runs, about 30% of the data collected by Advanced LIGO and Virgo in the next observing runs are expected to be single-interferometer data, i.e., they will be collected at times when only one detector in…
A yet undetected class of GW signals is represented by the close encounters between compact objects in highly-eccentric e~1 orbits, that can occur in binary systems formed in dense environments such as globular clusters. The expected…
Mergers of stellar-mass black holes on highly eccentric orbits are among the targets for ground-based gravitational-wave detectors, including LIGO, VIRGO, and KAGRA. These sources may commonly form through gravitational-wave emission in…
Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for conducting coherent parameter estimation for interferometric gravitational wave observations of an inspiral of binary compact objects using data from multiple…
Inspiraling binary neutron stars are expected to be one of the most significant sources of gravitational-wave signals for the new generation of advanced ground-based detectors. We investigate how well we could hope to measure properties of…
Faster likelihood evaluation enhances the efficiency of gravitational wave signal analysis. We present Mode-by-mode Relative Binning (MRB), a new method designed for obtaining fast and accurate likelihoods for advanced waveform models that…
We simulate the response of a Storage Ring Gravitational-Wave Observatory (SRGO) to astrophysical millihertz (mHz) gravitational waves (GWs), numerically obtaining its sensitivity curve and optimal choices for some controllable experiment…
A common technique for detection of gravitational-wave signals is searching for excess power in frequency-time maps of gravitational-wave detector data. In the event of a detection, model selection and parameter estimation will be performed…
The recent detection of the binary-neutron-star merger associated with GW170817 by both LIGO-Virgo and the network of electromagnetic-spectrum observing facilities around the world has made the multi-messenger detection of…
Gravitational wave Bayesian parameter inference involves repeated comparisons of GW data to generic candidate predictions. Even with algorithmically efficient methods like RIFT or reduced-order quadrature, the time needed to perform these…
We show that gravitational-wave signals from compact binary mergers may be better distinguished from instrumental noise transients by using Bayesian models that look for signal coherence across a detector network. This can be achieved even…
We introduce an efficient and straightforward technique for rapidly detecting gravitational waves from compact binary mergers. We show that this method achieves the low latencies required to alert electromagnetic partners of candidate…