Abstract

The relic gravitational waves (RGWs) originating from the early stages of the universe represent one of the most significant and highly focused targets for future gravitational wave (GW) detections, due to that these waves contain crucial information about the evolution of the cosmos and serve as key evidence for various cosmological models such as the big bang. RGWs cover exceptionally broad frequency bands encompassing the gigahertz (GHz) range (109 Hz), and the schemes based on electromagnetic (EM) response to GWs have been long and widely studied for such GHz band. Differently to previous works, we work out analytical and numerical forms of EM signals (with acquired novel characteristics and distinctive behaviors) caused by relic high-frequency GWs (RHFGWs) in simulated resonant cavity. By joint application of constructed effective and targeted deep learning neural networks, we successfully identify these EM signals amidst noise, and for the first time distinguish the different oscillating factors in focused model of RGW; also, we estimate typical parameters of corresponding RHFGWs and associated cosmological models, and establish a new scheme to explore the possible extra polarizations of RHFGWs in resonant cavity. In brief, we obtain new connections between the distinctive features of caused EM signals in cavity and corresponding parameters of cosmological models and RGWs; the results and methods would not only contribute to current theoretical investigation but also could provide valuable insights and preparation for potential experiments aimed at detecting such RHFGWs in the future, or may placing constraints on relevant GW parameters and theories of gravity.

Full Text
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