Parameter estimation for signals from compact binary inspirals injected into LIGO data

Marc Van Der Sluys*, Ilya Mandel, Vivien Raymond, Vicky Kalogera, Christian Röver, Nelson Christensen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

During the fifth science run of the Laser Interferometer Gravitational-Wave Observatory (LIGO), signals modelling the gravitational waves emitted by coalescing non-spinning compact-object binaries were injected into the LIGO data stream. We analysed the data segments into which such injections were made using a Bayesian approach, implemented as a Markov-chain Monte Carlo technique in our code SPINspiral. This technique enables us to determine the physical parameters of such a binary inspiral, including masses and spin, following a possible detection trigger. For the first time, we publish the results of a realistic parameter-estimation analysis of waveforms embedded in real detector noise. We used both spinning and non-spinning waveform templates for the data analysis and demonstrate that the intrinsic source parameters can be estimated with an accuracy of better than 1-3% in the chirp mass and 0.02-0.05 (8-20%) in the symmetric mass ratio if non-spinning waveforms are used. We also find a bias between the injected and recovered parameters, and attribute it to the difference in the post-Newtonian orders of the waveforms used for injection and analysis.

Original languageEnglish (US)
Article number204010
JournalClassical and Quantum Gravity
Volume26
Issue number20
DOIs
StatePublished - 2009

ASJC Scopus subject areas

  • Physics and Astronomy (miscellaneous)

Fingerprint Dive into the research topics of 'Parameter estimation for signals from compact binary inspirals injected into LIGO data'. Together they form a unique fingerprint.

Cite this