A Constrained Metropolis-Hastings Search for EMRIs in the Mock LISA Data Challenge 1B

Abstract

We describe a search for the extreme-mass-ratio inspiral sources in the Round 1B Mock LISA Data Challenge data sets. The search algorithm is a Monte-Carlo search based on the Metropolis-Hastings algorithm, but also incorporates simulated, thermostated and time annealing, plus a harmonic identification stage designed to reduce the chance of the chain locking onto secondary maxima. In this paper, we focus on describing the algorithm that we have been developing. We give the results of the search of the Round 1B data, although parameter recovery has improved since that deadline. Finally, we describe several modifications to the search pipeline that we are currently investigating for incorporation in future searches.

13 pages, 3 figures, to be published in proceedings of the 12th Gravitational Wave Data Analysis Workshop; v2 has minor changes for consistency with accepted version

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Cited by in corpus (13)

• The Mock LISA Data Challenges: from Challenge 3 to Challenge 4
• The Mock LISA Data Challenges: from Challenge 1B to Challenge 3
• Probing black holes at low redshift using LISA EMRI observations
• A Bayesian Approach to the Detection Problem in Gravitational Wave Astronomy
• An algorithm for detection of extreme mass ratio inspirals in LISA data
• Observing white dwarfs orbiting massive black holes in the gravitational wave and electro-magnetic window
• Degeneracies in Sky Localisation Determination from a Spinning Coalescing Binary through Gravitational Wave Observations: a Markov-Chain Monte-Carlo Analysis for two Detectors
• Separating Gravitational Wave Signals from Instrument Artifacts
• Improved time-frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data
• A LISA Data-Analysis Primer
• Delayed rejection schemes for efficient Markov-Chain Monte-Carlo sampling of multimodal distributions
• Verifying black hole orbits with gravitational spectroscopy
• Markov chain Monte Carlo searches for Galactic binaries in Mock LISA Data Challenge 1B data sets