A new code for parameter estimation in searches for gravitational waves from known pulsars

Abstract

We describe the consistency testing of a new code for gravitational wave signal parameter estimation in known pulsar searches. The code uses an implementation of nested sampling to explore the likelihood volume. Using fake signals and simulated noise we compare this to a previous code that calculated the signal parameter posterior distributions on both a grid and using a crude Markov chain Monte Carlo (MCMC) method. We define a new parameterisation of two orientation angles of neutron stars used in the signal model (the initial phase and polarisation angle), which breaks a degeneracy between them and allows more efficient exploration of those parameters. Finally, we briefly describe potential areas for further study and the uses of this code in the future.

Accepted for proceedings of Amaldi 9 meeting

Cited by in corpus (9)

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• First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data
• Hierarchical multi-stage MCMC follow-up of continuous gravitational wave candidates
• Enhancing confidence in the detection of gravitational waves from compact binaries using signal coherence
• Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up
• A targeted spectral interpolation algorithm for the detection of continuous gravitational waves