Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data

Abstract

Presented is a description of a Markov chain Monte Carlo (MCMC) parameter estimation routine for use with interferometric gravitational radiational data in searches for binary neutron star inspiral signals. Five parameters associated with the inspiral can be estimated, and summary statistics are produced. Advanced MCMC methods were implemented, including importance resampling and prior distributions based on detection probability, in order to increase the efficiency of the code. An example is presented from an application using realistic, albeit fictitious, data.

submitted to Classical and Quantum Gravity. 14 pages, 5 figures

Cited by in corpus (47)

• GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs
• Properties of the binary neutron star merger GW170817
• Properties of the Binary Black Hole Merger GW150914
• Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library
• Physics, Astrophysics and Cosmology with Gravitational Waves
• Bayesian inference for compact binary coalescences with BILBY: Validation and application to the first LIGO--Virgo gravitational-wave transient catalogue
• Gravitational Wave Tests of General Relativity with Ground-Based Detectors and Pulsar Timing Arrays
• A guide to LIGO-Virgo detector noise and extraction of transient gravitational-wave signals
• PyCBC Inference: A Python-based parameter estimation toolkit for compact binary coalescence signals
• Bayesian coherent analysis of in-spiral gravitational wave signals with a detector network
• Compact Binary Coalescences in the Band of Ground-based Gravitational-Wave Detectors
• Source localization with an advanced gravitational wave detector network
• Parameter estimation for binary neutron-star coalescences with realistic noise during the Advanced LIGO era
• Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project
• Gravitational-Wave Astronomy with Inspiral Signals of Spinning Compact-Object Binaries
• Gravitational waves from intermediate-mass-ratio inspirals for ground-based detectors
• A Solution to the Galactic Foreground Problem for LISA
• Parameter estimation with gravitational waves
• Bayesian reconstruction of gravitational wave burst signals from simulations of rotating stellar core collapse and bounce
• Estimating parameters of coalescing compact binaries with proposed advanced detector networks
• Estimating parameters of coalescing compact binaries with a detector network including LIGO Australia
• Estimating the parameters of non-spinning binary black holes using ground-based gravitational-wave detectors: Statistical errors
• Constraining the Inclination of Binary Mergers from Gravitational-wave Observations
• Black-hole ringdown as a probe of higher-curvature gravity theories
• Inferring the population properties of binary neutron stars with gravitational-wave measurements of spin
• Parameter estimation on gravitational waves from neutron-star binaries with spinning components
• The Search for Massive Black Hole Binaries with LISA
• Coherent Bayesian inference on compact binary inspirals using a network of interferometric gravitational wave detectors
• A Bayesian approach to the follow-up of candidate gravitational wave signals
• Measuring the eccentricity of GW170817 and GW190425
• Degeneracies in Sky Localisation Determination from a Spinning Coalescing Binary through Gravitational Wave Observations: a Markov-Chain Monte-Carlo Analysis for two Detectors
• Tests of general relativity in the nonlinear regime: a parametrized plunge-merger-ringdown gravitational waveform model
• Catching Super Massive Black Hole Binaries Without a Net
• Hierarchical multi-stage MCMC follow-up of continuous gravitational wave candidates
• Reconstructing gravitational wave signals from binary black hole mergers with minimal assumptions
• The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte-Carlo analysis of gravitational-wave signals
• Coherent Bayesian analysis of inspiral signals
• Bayesian parameter estimation of core collapse supernovae using gravitational wave simulations
• Inference on inspiral signals using LISA MLDC data
• Eccentricity signatures in LIGO-Virgo-KAGRA's BNS and NSBH binaries
• Posterior samples of the parameters of binary black holes from Advanced LIGO, Virgo's second observing run
• A Bayesian approach to the study of white dwarf binaries in LISA data: The application of a reversible jump Markov chain Monte Carlo method
• Nonorthogonal wavelet transformation for reconstructing gravitational wave signals
• Detection Confidence Tests for Burst and Inspiral Candidate Events
• Computational Techniques for Parameter Estimation of Gravitational Wave Signals
• Bayesian comparison of Post-Newtonian approximations of gravitational wave chirp signals
• Data Analysis Challenges for the Einstein Telescope