Discriminating between a stochastic gravitational wave background and instrument noise

Adams, M.; Cornish, N.

doi:10.1103/physrevd.82.022002

Cited by 118 publications

(141 citation statements)

References 24 publications

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“…Note that the minimum value of Ω(f ) shown in this plot is about a factor of 10 times smaller than the value of Ω gw (f ) ≈ 2 × 10 −13 reported in [20,21]. Part of this difference is due to our use of ρ = 1 for the sensitivity curve, while their value of Ω gw (f ) corresponds to a strong (several σ) detection having a Bayes factor ≥ 30.…”

Section: Lisamentioning

confidence: 69%

“…It is possible, however, to construct a combination of the LISA data whose response to gravitational waves is highly suppressed at these frequencies, and hence can be used as a real-time noise monitor for LISA [18,19]. It is also possible to exploit the differences between the transfer function and spectral shape of a gravitational-wave background and that due to instrumental noise and/or an astrophysical foreground (e.g., from galactic white-dwarf binaries) to discriminate a gravitational-wave background from these other noise contributions [20,21].…”

Section: Lisamentioning

confidence: 99%

“…Part of this difference is due to our use of ρ = 1 for the sensitivity curve, while their value of Ω gw (f ) corresponds to a strong (several σ) detection having a Bayes factor ≥ 30. The remaining factor can probably be attributed to the marginalization over the instrumental noise and galactic foreground parameters in [20,21], while Eq. 36 assumes that we know these parameters perfectly.…”

Section: Lisamentioning

confidence: 99%

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Sensitivity curves for searches for gravitational-wave backgrounds

Thrane

Romano²

2013

Phys. Rev. D

532

645

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We propose a graphical representation of detector sensitivity curves for stochastic gravitationalwave backgrounds that takes into account the increase in sensitivity that comes from integrating over frequency in addition to integrating over time. This method is valid for backgrounds that have a power-law spectrum in the analysis band. We call these graphs "power-law integrated curves." For simplicity, we consider cross-correlation searches for unpolarized and isotropic stochastic backgrounds using two or more detectors. We apply our method to construct power-law integrated sensitivity curves for second-generation ground-based detectors such as Advanced LIGO, space-based detectors such as LISA and the Big Bang Observer, and timing residuals from a pulsar timing array. The code used to produce these plots is available at https://dcc.ligo.org/LIGO-P1300115/public for researchers interested in constructing similar sensitivity curves.

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Section: Lisamentioning

confidence: 69%

Section: Lisamentioning

confidence: 99%

Section: Lisamentioning

confidence: 99%

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Sensitivity curves for searches for gravitational-wave backgrounds

Thrane

Romano²

2013

Phys. Rev. D

532

645

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“…Applying a Bayesian method, Refs. [35,36] found that the old LISA configuration over Table 1 compared with a typical GW signal. We have chosen the signal predicted in the Higgs portal scenario described in Section 4.2.2, with benchmark values T * = 59.6, α = 0.17, β/H * = 12.54, φ * /T * = 4.07 (see Table 3).…”

Section: Detection Thresholdmentioning

confidence: 99%

Science with the space-based interferometer eLISA. II: gravitational waves from cosmological phase transitions

Caprini

Hindmarsh

Huber

et al. 2016

J. Cosmol. Astropart. Phys.

837

1,311

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We investigate the potential for the eLISA space-based interferometer to detect the stochastic gravitational wave background produced by strong first-order cosmological phase transitions. We discuss the resulting contributions from bubble collisions, magnetohydrodynamic turbulence, and sound waves to the stochastic background, and estimate the total corresponding signal predicted in gravitational waves. The projected sensitivity of eLISA to cosmological phase transitions is computed in a model-independent way for various detector designs and configurations. By applying these results to several specific models, we demonstrate that eLISA is able to probe many wellmotivated scenarios beyond the Standard Model of particle physics predicting strong first-order cosmological phase transitions in the early Universe.

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“…The likelihood function (4) has the standard form used in cross-correlation analyses for stochastic signals [12,13].…”

mentioning

confidence: 99%

Towards a unified treatment of gravitational-wave data analysis

Cornish

Romano²

2013

Phys. Rev. D

Self Cite

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We present a unified description of gravitational-wave data analysis that unites the templatebased analysis used to detect deterministic signals from well-modeled sources, such as binary-blackhole mergers, with the cross-correlation analysis used to detect stochastic gravitational-wave backgrounds. We also discuss the connection between template-based analyses and those that target poorly-modeled bursts of gravitational waves, and suggest a new approach for detecting burst signals.PACS numbers: 04.80. Nn, 04.30.Db, 07.05.Kf, 95.55.Ym Gravitational-wave data analysis is conventionally divided into three classes that depend on the nature of the signal: (i) well-modeled deterministic signals, such as those from compact binary inspirals; (ii) poorly-modeled deterministic signals, such as those from core-collapse supernovae; and (iii) stochastic signals, such as those from a phase transition in the early Universe. Here we will argue that this division is rather artificial and unnecessary, and suggest that a unified treatment can yield deeper insights. The elements needed to unify cases (i) and (ii) can be found in Refs. [1][2][3][4]. Here we provide a unification of cases (i) and (iii) using hierarchical Bayesian modeling [5].The motivation for developing a unified description of gravitational-wave data analysis is two-fold. First there is the pedagogical value of a coherent picture that emphasizes the common foundation of the disparate analysis techniques found in the literature, and second, the unified picture can provide a deeper understanding that may suggest new approaches. To illustrate the latter point we conclude our discussion by proposing a novel technique for detecting un-modeled "bursts" of gravitational waves.In the conventional picture, signals for which we have waveform templates are analyzed using a matched-filter statistic [6], un-modeled signals are characterized in terms of an excess power statistic [7], and stochastic signals are analyzed using a cross-correlation statistic between pairs of detectors [8]. The connection between the various forms of analysis is not immediately apparent, especially when described in a frequentist framework.In the case of un-modeled signals, the analyses usually focus on short duration "bursts" of gravitational-wave energy that are localized in a time-frequency representation of the data. The connection between a waveform template-based search and a burst search becomes apparent in the case of fully-coherent network analyses, where it becomes possible to solve for the gravitational-wave signal by either maximizing the likelihood [2] or locating regions of high posterior density [3,4]. To obtain meaningful results these analyses require constraints or pri-

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Discriminating between a stochastic gravitational wave background and instrument noise

Cited by 118 publications

References 24 publications

Sensitivity curves for searches for gravitational-wave backgrounds

Sensitivity curves for searches for gravitational-wave backgrounds

Science with the space-based interferometer eLISA. II: gravitational waves from cosmological phase transitions

Towards a unified treatment of gravitational-wave data analysis

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