Computational Framework for White Hole Detection in Gravitational Waves and CMB Data

This study presents a computational framework for evaluating the detectability of white hole-induced gravitational wave signals and their imprints on the cosmic microwave background (CMB). The approach integrates stochastic gravitational wave background (SGWB) polarization data from LISA with CMB-S4 B-mode anisotropies, utilizing Monte Carlo simulations, Bayesian inference, and signal-to-noise ratio (SNR) estimations to determine detection feasibility.

Publication Details

Journal
ArXiv.org
Published
2025-03-17
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
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article

Computational Framework for White Hole Detection in Gravitational Waves and CMB Data

ArXiv.org
Pulsars and Gravitational Waves Research
article

Computational Framework for White Hole Detection in Gravitational Waves and CMB Data

article en

Abstract

This study presents a computational framework for evaluating the detectability of white hole-induced gravitational wave signals and their imprints on the cosmic microwave background (CMB). The approach integrates stochastic gravitational wave background (SGWB) polarization data from LISA with CMB-S4 B-mode anisotropies, utilizing Monte Carlo simulations, Bayesian inference, and signal-to-noise ratio (SNR) estimations to determine detection feasibility.

ArXiv.org
Openalex Percentile: Top 56%
Pulsars and Gravitational Waves Research
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Computational Framework for White Hole Detection in Gravitational Waves and CMB Data · ArXiv.org (2025) | TGRS Research Map | TGRS