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Once upon a time, predictions for the accuracy of inference on gravitational-wave signals relied on computationally inexpensive but often inaccurate techniques. Recently, the approach has shifted to actual inference on noisy signals with complex stochastic Bayesian methods, at the expense of significant computational cost. Here, we argue that it is often possible to have the best of both worlds: a Bayesian approach that incorporates prior information and correctly marginalizes over uninteresting parameters, providing accurate posterior probability distribution functions, but carried out on a simple grid at a low computational cost, comparable to the inexpensive predictive techniques.
A pioneering electromagnetic (EM) observation follow-up program of candidate gravitational wave (GW) triggers has been performed, Dec 17 2009 to Jan 8 2010 and Sep 4 to Oct 20 2010, during the recent LIGO/Virgo run. The follow-up program involved gro
The progenitor system(s) and the explosion mechanism(s) of Type Ia supernovae (SNe Ia) are still under debate. Non-electromagnetic observables, in particular gravitational waves and neutrino emission, of thermonuclear supernovae are a complementary w
In this paper we present the results of the first low frequency all-sky search of continuous gravitational wave signals conducted on Virgo VSR2 and VSR4 data. The search covered the full sky, a frequency range between 20 Hz and 128 Hz with a range of
The first terrestrial gravitational wave interferometers have dramatically underscored the scientific value of observing the Universe through an entirely different window, and of folding this new channel of information with traditional astronomical d
The past four years have seen a scientific revolution through the birth of a new field: gravitational-wave astronomy. The first detection of gravitational waves---recognised by the 2017 Nobel Prize in Physics---provided unprecedented tests of general