Efficient parameter estimation is critical for Gravitational-Wave astronomy. In the case of compact binary coalescence, the high dimensional parameter space demands efficient sampling techniques - such as Markov chain Monte Carlo (MCMC). A number of
degeneracies effectively reduce the dimensionality of the parameter space and, when known, can render sampling algorithms more efficient with problem-specific improvements. We present in this paper an analytical description of a degeneracy involving the extrinsic parameters of a compact binary coalescence gravitational-wave signal, when data from a three detector network (such as Advanced LIGO/Virgo) is available. We use this new formula to construct a jump proposal, a framework for a generic sampler to take advantage of the degeneracy. We show the gain in efficiency for a MCMC sampler in the analysis of the gravitational-wave signal from a compact binary coalescence.
Gravitational-wave signals from inspirals of binary compact objects (black holes and neutron stars) are primary targets of the ongoing searches by ground-based gravitational-wave (GW) interferometers (LIGO, Virgo, and GEO-600). We present parameter-e
stimation results from our Markov-chain Monte-Carlo code SPINspiral on signals from binaries with precessing spins. Two data sets are created by injecting simulated GW signals into either synthetic Gaussian noise or into LIGO detector data. We compute the 15-dimensional probability-density functions (PDFs) for both data sets, as well as for a data set containing LIGO data with a known, loud artefact (glitch). We show that the analysis of the signal in detector noise yields accuracies similar to those obtained using simulated Gaussian noise. We also find that while the Markov chains from the glitch do not converge, the PDFs would look consistent with a GW signal present in the data. While our parameter-estimation results are encouraging, further investigations into how to differentiate an actual GW signal from noise are necessary.
Gravitational-wave signals from inspirals of binary compact objects (black holes and neutron stars) are primary targets of the ongoing searches by ground-based gravitational-wave interferometers (LIGO, Virgo, and GEO-600). We present parameter-estima
tion simulations for inspirals of black-hole--neutron-star binaries using Markov-chain Monte-Carlo methods. As a specific example of the power of these methods, we consider source localisation in the sky and analyse the degeneracy in it when data from only two detectors are used. We focus on the effect that the black-hole spin has on the localisation estimation. We also report on a comparative Markov-chain Monte-Carlo analysis with two different waveform families, at 1.5 and 3.5 post-Newtonian order.
