Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

2001/02/05 by N. Christensen, Nelson Christensen, Renate Meyer · 6 citations
Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #Geophysics and Gravity Measurements #Pulsars and Gravitational Waves Research #Target Tracking and Data Fusion in Sensor Networks #gr-qc

paper · pdf · doi:10.1103/physrevd.64.022001

published as Phys.Rev. D64 (2001) 022001 · 21 pages, 10 figures

arxiv created 2001/02/05 · openalex publication_date 2001/05/31 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.

Citations

• Equation of State Calculations by Fast Computing Machines

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