Bayesian parameter estimation for targeted anisotropic gravitational-wave background

Extended sources of the stochastic gravitational backgrounds have been conventionally searched on the spherical-harmonics bases. The analysis during the previous observing runs by the ground-based gravitational-wave detectors, such as LIGO and Virgo, have yielded the constraints on the angular power spectrum Cℓ, yet it lacks the capability of estimating other parameters such as a spectral index. In this paper, we introduce an alternative Bayesian formalism to search for such stochastic signals with a particular distribution of anisotropies on the sky. This approach provides a Bayesian posterior of model parameters and also enables selection tests among different signal models. While the conventional analysis fixes the highest angular scale a priori, here we show a more systematic and quantitative way to determine the cutoff scale based on a Bayes factor, which depends on the amplitude and the angular scale of observed signals. Also, we analyze the third observing runs of LIGO and Virgo for the population of millisecond pulsars and obtain the 95% constraints of the signal amplitude, ϵ < 2.7 x 10^−8.

© American Physical Society (APS) [Bayesian parameter estimation for targeted anisotropic gravitational-wave background. Physical Review D 107, 2 (2023)]

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Work Title Bayesian parameter estimation for targeted anisotropic gravitational-wave background
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Open Access
Creators
  1. Leo Tsukada
  2. Santiago Jaraba
  3. Erik Floden
  4. Deepali Agarwal
License In Copyright (Rights Reserved)
Work Type Article
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  1. Physical Review D
Publication Date January 30, 2023
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  1. https://doi.org/10.1103/PhysRevD.107.023024
Deposited January 23, 2024

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  • Added 2208.14421-1.pdf
  • Added Creator Leo Tsukada
  • Added Creator Santiago Jaraba
  • Added Creator Erik Floden
  • Added Creator Deepali Agarwal
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    Description
    • Extended sources of the stochastic gravitational backgrounds have been conventionally searched on the spherical-harmonics bases. The analysis during the previous observing runs by the ground-based gravitational-wave detectors, such as LIGO and Virgo, have yielded the constraints on the angular power spectrum Cℓ, yet it lacks the capability of estimating other parameters such as a spectral index. In this paper, we introduce an alternative Bayesian formalism to search for such<br>stochastic signals with a particular distribution of anisotropies on the sky. This approach provides a Bayesian posterior of model parameters and also enables selection tests among different signal models. While the conventional analysis fixes the highest angular scale a priori, here we show a more systematic and quantitative way to determine the cutoff scale based on a Bayes factor, which depends on the amplitude and the angular scale of observed signals. Also, we analyze the third<br>observing runs of LIGO and Virgo for the population of millisecond pulsars and obtain the 95 % constraints of the signal amplitude, ϵ < 2.7 e−8.
    • Extended sources of the stochastic gravitational backgrounds have been conventionally searched on the spherical-harmonics bases. The analysis during the previous observing runs by the ground-based gravitational-wave detectors, such as LIGO and Virgo, have yielded the constraints on the angular power spectrum Cℓ, yet it lacks the capability of estimating other parameters such as a spectral index. In this paper, we introduce an alternative Bayesian formalism to search for such stochastic signals with a particular distribution of anisotropies on the sky. This approach provides a Bayesian posterior of model parameters and also enables selection tests among different signal models. While the conventional analysis fixes the highest angular scale a priori, here we show a more systematic and quantitative way to determine the cutoff scale based on a Bayes factor, which depends on the amplitude and the angular scale of observed signals. Also, we analyze the third observing runs of LIGO and Virgo for the population of millisecond pulsars and obtain the 95% constraints of the signal amplitude, ϵ < 2.7 x 10^−8.
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