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astro-ph.CO2026
MujicÎ: Reconstructing Initial Conditions from Incomplete Redshift Surveys with Projected Optimization
Chenze Dong, Benjamin Horowitz, Adrian E. Bayer +1
In this paper, we introduce MujicÎ (Mapping the Universe with Jax-based Initial Condition ReconstrÎction), an optimization-based framework for reconstructing initial conditions f…
astro-ph.CO2026
Field-Level Inference from Galaxies: BAO Reconstruction
Adrian E. Bayer, Liam Parker, David Valcin +3
Baryon acoustic oscillations (BAO) underpin the key cosmological results from modern spectroscopic galaxy surveys, but nonlinear gravitational evolution limits the precision achiev…
astro-ph.CO2026
Interpreting Cosmological Information from Neural Networks in the Hydrodynamic Universe
Arnab Lahiry, Adrian E. Bayer, Francisco Villaescusa-Navarro
What happens when a black box (neural network) meets a black box (simulation of the Universe)? Recent work has shown that convolutional neural networks (CNNs) can infer cosmologica…