Simulation of the white dwarf–white dwarf galactic background in the LISA data

Edlund, Jeffrey A.; Tinto, Massimo; Królak, A.; Nelemans, G.

doi:10.1088/0264-9381/22/18/s05

Cited by 12 publications

(12 citation statements)

References 22 publications

(72 reference statements)

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“…Readers should see Giampieri and Polnarev (1997), Cornish (2001), Ungarelli and Vecchio (2001), Seto (2004), Seto and Cooray (2004), Kudoh and Taruya (2005), Edlund et al. (2005) and Taruya and Kudoh (2005) for details.…”

Section: Anisotropic Backgroundsmentioning

confidence: 99%

Detection methods for stochastic gravitational-wave backgrounds: a unified treatment

2017

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We review detection methods that are currently in use or have been proposed to search for a stochastic background of gravitational radiation. We consider both Bayesian and frequentist searches using ground-based and space-based laser interferometers, spacecraft Doppler tracking, and pulsar timing arrays; and we allow for anisotropy, non-Gaussianity, and non-standard polarization states. Our focus is on relevant data analysis issues, and not on the particular astrophysical or early Universe sources that might give rise to such backgrounds. We provide a unified treatment of these searches at the level of detector response functions, detection sensitivity curves, and, more generally, at the level of the likelihood function, since the choice of signal and noise models and prior probability distributions are actually what define the search. Pedagogical examples are given whenever possible to compare and contrast different approaches. We have tried to make the article as self-contained and comprehensive as possible, targeting graduate students and new researchers looking to enter this field.Electronic supplementary materialThe online version of this article (doi:10.1007/s41114-017-0004-1) contains supplementary material, which is available to authorized users.

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Section: Anisotropic Backgroundsmentioning

confidence: 99%

Detection methods for stochastic gravitational-wave backgrounds: a unified treatment

2017

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“…Such longer data segments will soon become unavoidable as the lower frequency performance of the detector improves towards design sensitivity or next generation detectors [39,40]. Similar challenges will be faced by analysis of data from the planned space-based detector LISA [41,42].…”

Section: A the Anderson-darling Statisticmentioning

confidence: 99%

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

et al. 2019

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Estimating the parameters of gravitational wave signals detected by ground-based detectors requires an understanding of the properties of the detectors' noise. In particular, the most commonly used likelihood function for gravitational wave data analysis assumes that the noise is Gaussian, stationary, and of known frequency-dependent variance. The variance of the colored Gaussian noise is used as a whitening filter on the data before computation of the likelihood function. In practice the noise variance is not known and it evolves over timescales of dozens of seconds to minutes. We study two methods for estimating this whitening filter for ground-based gravitational wave detectors with the goal of performing parameter estimation studies. The first method uses large amounts of data separated from the specific segment we wish to analyze and computes the power spectral density of the noise through the mean-median Welch method. The second method uses the same data segment as the parameter estimation analysis, which potentially includes a gravitational wave signal, and obtains the whitening filter through a fit of the power spectrum of the data in terms of a sum of splines and Lorentzians. We compare these two methods and argue that the latter is more reliable for gravitational wave parameter estimation. arXiv:1907.06540v1 [gr-qc]

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“…and X (3) , X (4) are obtained by replacing cos with sin in X (1) and X (2) respectively. In the above equation we have used: .…”

Section: Response Of the Lisa Detector To The Gravitational-wave mentioning

confidence: 99%

“…These binaries will be dominated by the population of the white dwarf binaries. The number of the observed ultra-compact binaries will be so large below 3 mHz that they are not individually resolvable and form a cyclo-stationary background which dominates over the instrumental noise above 0.1 mHz [2,3]. The number of binaries drops significantly above 7-8 mHz.…”

Section: Introductionmentioning

confidence: 99%

Mock LISA data challenge for the Galactic white dwarf binaries

2010

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We present data analysis methods used in detection and the estimation of parameters of gravitational wave signals from the white dwarf binaries in the mock LISA data challenge. Our main focus is on the analysis of challenge 3.1, where the gravitational wave signals from more than 6 × 10 7Galactic binaries were added to the simulated Gaussian instrumental noise. Majority of the signals at low frequencies are not resolved individually. The confusion between the signals is strongly reduced at frequencies above 5 mHz. Our basic data analysis procedure is the maximum likelihood detection method. We filter the data through the template bank at the first step of the search, then we refine parameters using the Nelder-Mead algorithm, we remove the strongest signal found and we repeat the procedure. We detect reliably and estimate parameters accurately of more than ten thousand signals from white dwarf binaries. PACS numbers: 95.55.Ym, 04.80.Nn, 95.75.Pq, 97.60.Gb

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Simulation of the white dwarf–white dwarf galactic background in the LISA data

Cited by 12 publications

References 22 publications

Detection methods for stochastic gravitational-wave backgrounds: a unified treatment

Detection methods for stochastic gravitational-wave backgrounds: a unified treatment

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

Mock LISA data challenge for the Galactic white dwarf binaries

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