Generic predictions for primordial perturbations and their implications
Sharma M.K. Sami M. Mota D.F.
September 2024Elsevier B.V.
Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics
2024#856
We introduce a novel framework for studying small-scale primordial perturbations and their cosmological implications. The framework uses a deep reinforcement learning to generate scalar power spectrum profiles that are consistent with current observational constraints. The framework is shown to predict the abundance of primordial black holes and the production of secondary induced gravitational waves. We demonstrate that the set up under consideration is capable of generating predictions that are beyond the traditional model-based approaches.
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Centre For Cosmology and Science Popularization (CCSP), SGT University, Haryana, Gurugram, 122505, India
Eurasian International Centre for Theoretical Physics, Astana, Kazakhstan
Chinese Academy of Sciences, 52 Sanlihe Rd, Xicheng District, Beijing, China
Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, Oslo, N-0315, Norway
Centre For Cosmology and Science Popularization (CCSP)
Eurasian International Centre for Theoretical Physics
Chinese Academy of Sciences
Institute of Theoretical Astrophysics
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