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Fast and Accurate Sensitivity Estimation for Continuous-Gravitational-Wave Searches

MPS-Authors
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Dreißigacker,  Christoph
Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Prix,  Reinhard
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

/persons/resource/persons4307

Wette,  Karl
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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1808.02459.pdf
(Preprint), 2MB

PRD.98.084058.pdf
(Publisher version), 844KB

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Citation

Dreißigacker, C., Prix, R., & Wette, K. (2018). Fast and Accurate Sensitivity Estimation for Continuous-Gravitational-Wave Searches. Physical Review D, 98: 084058. doi:10.1103/PhysRevD.98.084058.


Cite as: https://hdl.handle.net/21.11116/0000-0001-FA25-C
Abstract
This paper presents an efficient numerical sensitivity-estimation method and
implementation for continuous-gravitational-wave searches, extending and
generalizing an earlier analytic approach by Wette [1]. This estimation
framework applies to a broad class of F-statistic-based search meth- ods,
namely (i) semi-coherent StackSlide F-statistic (single-stage and hierarchical
multi-stage), (ii) Hough number count on F-statistics, as well as (iii)
Bayesian upper limits on (coherent or semi-coherent) F-statistic search
results. We test this estimate against results from Monte-Carlo simulations
assuming Gaussian noise. We find the agreement to be within a few % at high
(i.e. low false-alarm) detection thresholds, with increasing deviations at
decreasing (i.e. higher false- alarm) detection thresholds, which can be
understood in terms of the approximations used in the estimate. We also provide
an extensive summary of sensitivity depths achieved in past continuous-
gravitational-wave searches (derived from the published upper limits). For the
F-statistic-based searches where our sensitivity estimate is applicable, we
find an average relative deviation to the published upper limits of less than
10%, which in most cases includes systematic uncertainty about the noise-floor
estimate used in the published upper limits.