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  Optimizing StackSlide setup and data selection for continuous-gravitational-wave searches in realistic detector data

Shaltev, M. (2016). Optimizing StackSlide setup and data selection for continuous-gravitational-wave searches in realistic detector data. Physical Review D, 93: 044058. doi:10.1103/PhysRevD.93.044058.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-9046-D Version Permalink: http://hdl.handle.net/21.11116/0000-0002-FA02-2
Genre: Journal Article

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 Creators:
Shaltev, Miroslav1, 2, Author              
Affiliations:
1Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, ou_24011              
2Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, Hannover, DE, ou_2630691              

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Free keywords: General Relativity and Quantum Cosmology, gr-qc, Astrophysics, Instrumentation and Methods for Astrophysics, astro-ph.IM
 Abstract: The search for continuous gravitational waves in a wide parameter space at fixed computing cost is most efficiently done with semicoherent methods, e.g. StackSlide, due to the prohibitive computing cost of the fully coherent search strategies. Prix&Shaltev arXiv:1201.4321 have developed a semi-analytic method for finding \emph{optimal} StackSlide parameters at fixed computing cost under ideal data conditions, i.e. gap-less data and constant noise floor. In this work we consider more realistic conditions by allowing for gaps in the data and changes in noise level. We show how the sensitivity optimization can be decoupled from the data selection problem. To find optimal semicoherent search parameters we apply a numerical optimization using as example the semicoherent StackSlide search. We also describe three different data selection algorithms. Thus the outcome of the numerical optimization consists of the optimal search parameters and the selected dataset. We first test the numerical optimization procedure under ideal conditions and show that we can reproduce the results of the analytical method. Then we gradually relax the conditions on the data and find that a compact data selection algorithm yields higher sensitivity compared to a greedy data selection procedure.

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 Dates: 2015-10-212016-04-032016
 Publication Status: Published in print
 Pages: 14 pages, 6 figures
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: arXiv: 1510.06427
DOI: 10.1103/PhysRevD.93.044058
URI: http://arxiv.org/abs/1510.06427
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Title: Physical Review D
  Other : Phys. Rev. D.
Source Genre: Journal
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Publ. Info: Lancaster, Pa. : American Physical Society
Pages: - Volume / Issue: 93 Sequence Number: 044058 Start / End Page: - Identifier: ISSN: 0556-2821
CoNE: /journals/resource/111088197762258