Reconciling Early and Late Time Tensions with Reinforcement Learning

2024/08/08 by Mohit Kumar Sharma, Sharma, Mohit K., M. Sami +1 · 2 citations
Computer Science · Neuroscience · #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #EEG and Brain-Computer Interfaces #FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #Reinforcement Learning in Robotics

paper · pdf · doi:10.48550/arxiv.2408.04204

openalex publication_date 2024/08/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We study the possibility of accommodating both early and late-time tensions using a novel reinforcement learning technique. By applying this technique, we aim to optimize the evolution of the Hubble parameter from recombination to the present epoch, addressing both tensions simultaneously. To maximize the goodness of fit, our learning technique achieves a fit that surpasses even the ΛCDM model. Our results demonstrate a tendency to weaken both early and late time tensions in a completely model-independent manner.

Cited by

• Role of dynamical early dark energy in Hubble tension through warm inflation
• Unraveling the Hubble tension with warm inflation

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