Artificial Intelligence for Harvesting the Untapped Cosmological Information in the Lyman-Α Forest
MCML Authors
Parth Nayak
Dr.
Abstract
Parth Nayak
Dr.
Abstract
This dissertation develops deep learning methods for cosmological parameter inference from the Lyα forest, enabling more efficient extraction of information from large spectroscopic sky surveys. By training neural networks on cosmological simulations, it demonstrates substantially improved parameter estimation over traditional statistical methods while addressing the challenges of applying deep learning to realistic astronomical data. (Shortened.)
BibTeXKey: Nay25