3 papers
astro-ph.CO2026
A Measurement of the Thermal and Ionization State of the IGM at
Teng Hu, Vikram Khaire, Joseph F. Hennawi +4
We apply a machine-learning-based inference method that exploits the joint Doppler parameter-column density (b-NHI) distribution from Lya forest decomposition to measure the therma…
astro-ph.IM2025
LyαNNA II: Field-level inference with noisy Lyα forest spectra
Parth Nayak, Michael Walther, Daniel Gruen
Deep learning (DL) has been shown to outperform traditional, human-defined summary statistics of the Lyα forest in constraining key astrophysical and cosmological parameters owing…
astro-ph.CO2025
Human vs. machine -- 1:3. Joint analysis of classical and ML-based summary statistics of the Lyman- forest
S. Chang, P. Nayak, M. Walther +1
In order to compress and more easily interpret Lyman- forest (LyF) datasets, summary statistics, e.g. the power spectrum, are commonly used. However, such summaries unavoid…