Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets

Stroeer, Alexander and Veitch, John and Röver, Christian and Bloomer, Ed and Clark, James and Christensen, Nelson and Hendry, Martin and Messenger, Chris and Meyer, Renate and Pitkin, Matthew and Toher, Jennifer and Umstätter, Richard and Vecchio, Alberto and Woan, Graham (2007) Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets. In: UNSPECIFIED.

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Abstract

We report on the analysis of selected single source data sets from the first round of the mock LISA data challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection and an automatic Markov Chain Monte Carlo (MCMC) post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest.

Item Type:
Contribution to Conference (Paper)
Subjects:
ID Code:
135881
Deposited By:
Deposited On:
30 Jul 2019 14:00
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Nov 2020 09:27