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arXiv · 2502.11804

Identification of Stochastic Gravitational Wave Backgrounds from Cosmic String Using Machine Learning

Abstract

Cosmic strings play a crucial role in enhancing our understanding of the fundamental structure and evolution of the universe, unifying our knowledge of cosmology, and potentially unveiling new physical laws and phenomena. The advent and operation of space-based detectors provide an important opportunity for detecting stochastic gravitational wave backgrounds (SGWB) generated by cosmic strings. However, the intricate nature of SGWB poses a formidable challenge in distinguishing its signal from the complex noise by some traditional methods. Therefore, we attempt to identify SGWB based on machine learning. Our findings show that the joint detection of LISA and Taiji significantly outperforms individual detectors, and even in the presence of numerous low signal-to-noise ratio(SNR) signals, the identification accuracy remains exceptionally high with 95%. Although our discussion is based solely on simulated data, the relevant methods can provide data-driven analytical capabilities for future observations of SGWB.

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BibTeXRIS

Xianghe Ma, Borui Wang, Nan Yang, Jin Li, Brendan McCane, Mengfei Sun, Jie Wu, Minghui Zhang, Yan Meng. 2025-03-06. Identification of Stochastic Gravitational Wave Backgrounds from Cosmic String Using Machine Learning. https://arxiv.org/abs/2502.11804

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