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astro-ph.CO2026
MadEvolve: Evolutionary Optimization of Cosmological Algorithms with Large Language Models
Tianyi Li, Shihui Zang, Moritz Münchmeyer
We develop a general framework to discover scientific algorithms and apply it to three problems in computational cosmology. Our code, MadEvolve, is similar to Google's AlphaEvolve,…
astro-ph.CO2025
Reconstruction of Dark Matter and Baryon Density From Galaxies: A Comparison of Linear, Halo Model and Machine Learning-Based Methods
Jordan Krywonos, Yurii Kvasiuk, Matthew C. Johnson +1
For many analyses in cosmology it is necessary to reconstruct the likely distribution of unobserved fields, such as dark matter or non-luminous baryons, from observed luminous trac…