195 citations · 445 across the 11 of their papers we have counts for
11 papers · 1 filter
A Bayesian method to set upper limits on the strength of a periodic gravitational wave signal from the remnant of SN1987A: possible applications in LIGO searches
Richard Umstaetter, Renate Meyer, Nelson Christensen
We present a method that assesses the theoretical detection limit of a Bayesian Markov chain Monte Carlo search for a periodic gravitational wave signal emitted by a neutron star.…
Report on the second Mock LISA Data Challenge
Stanislav Babak, John G. Baker, Matthew J. Benacquista +40
The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of several data set…
Inference on inspiral signals using LISA MLDC data
Christian Röver, Alexander Stroeer, Ed Bloomer +11
In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Chal…
Coherent Bayesian analysis of inspiral signals
Christian Röver, Renate Meyer, Gianluca M. Guidi +2
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 d…
Searching for Gravitational Waves from Binary Inspirals with LIGO
Duncan A. Brown, Stanislav Babak, Patrick R. Brady +9
We describe the current status of the search for gravitational waves from inspiralling compact binary systems in LIGO data. We review the result from the first scientific run of LI…
Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets
Alexander Stroeer, John Veitch, Christian Roever +11
We report on the analysis of selected single source data sets from the first round of the Mock LISA Data Challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pi…