Tracing the Cosmic Origins: Machine Learning Reconstruction of the Primordial Density Field from EoR Observations
Abstract
Reconstructing the initial conditions of the Universe from late-time tracers would unlock cosmological information buried by non-linear structure formation and astrophysics. We reconstruct the initial density field corresponding to z=300, with its linear amplitude extrapolated to z=0, from simulated 21-cm and CO(1-0) line-intensity maps at z=8 generated with LIMFAST. Using a three-dimensional U-Net, we reconstruct the initial conditions and evaluate their impact on cosmological parameter constraints. The two tracers probe complementary environments: 21-cm emission traces neutral, low-density regions of the IGM, while CO traces overdense, star-forming regions. We also train and evaluate the reconstruction on maps incorporating SKA1-Low- and COMAP-ERA-like instrumental response and thermal noise. In the noiseless case, combining both tracers delivers the most accurate reconstruction across ionisation states, with the cross-correlation coefficient between the reconstructed and true initial density fields, |C(k)| ≳ 0.90 for k ≲ 0.75 Mpc−1. With observational effects, small-scale information is degraded, but the joint reconstruction retains substantial large-scale coherence, with |C(k)| ≳ 0.70 for k ≲ 0.3 Mpc−1. We quantify cosmological information gains through simulation-based inference using power-spectrum summaries pre- and post-reconstruction. The largest improvements occur for σ8 and ns, with a median aggregate marginal compression of $1.17$ bits in the noiseless case, corresponding to a 56% reduction in the factorised product of prior-normalised 68% marginal widths. With observational effects, the corresponding median compression is $1.29$ bits. These results demonstrate that joint 21-cm-CO reconstruction recovers cosmological information beyond pre-reconstruction summaries.
Versions
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BibTeX
@misc{saxena2026tracing,
title = {{Tracing the Cosmic Origins: Machine Learning Reconstruction of the Primordial Density Field from EoR Observations}},
author = {Anchal Saxena and P. Daniel Meerburg and Guochao Sun and Tzu-Ching Chang and Lluís Mas-Ribas},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.05412},
eprint = {2609.05412},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.05412},
}
RIS
TY - UNPB
TI - Tracing the Cosmic Origins: Machine Learning Reconstruction of the Primordial Density Field from EoR Observations
AU - Anchal Saxena
AU - P. Daniel Meerburg
AU - Guochao Sun
AU - Tzu-Ching Chang
AU - Lluís Mas-Ribas
PY - 2026
DA - 2026/10/23
PB - arXiv
DO - 10.48550/arxiv.2609.05412
UR - https://arxiv.org/abs/2609.05412
AB - Reconstructing the initial conditions of the Universe from late-time tracers would unlock cosmological information buried by non-linear structure formation and astrophysics. We reconstruct the initial density field corresponding to z=300, with its linear amplitude extrapolated to z=0, from simulated 21-cm and CO(1-0) line-intensity maps at z=8 generated with LIMFAST. Using a three-dimensional U-Net, we reconstruct the initial conditions and evaluate their impact on cosmological parameter constraints. The two tracers probe complementary environments: 21-cm emission traces neutral, low-density regions of the IGM, while CO traces overdense, star-forming regions. We also train and evaluate the reconstruction on maps incorporating SKA1-Low- and COMAP-ERA-like instrumental response and thermal noise. In the noiseless case, combining both tracers delivers the most accurate reconstruction across ionisation states, with the cross-correlation coefficient between the reconstructed and true initial density fields, |C(k)| ≳ 0.90 for k ≲ 0.75 Mpc^−1. With observational effects, small-scale information is degraded, but the joint reconstruction retains substantial large-scale coherence, with |C(k)| ≳ 0.70 for k ≲ 0.3 Mpc^−1. We quantify cosmological information gains through simulation-based inference using power-spectrum summaries pre- and post-reconstruction. The largest improvements occur for σ_8 and n_s, with a median aggregate marginal compression of $1.17$ bits in the noiseless case, corresponding to a 56% reduction in the factorised product of prior-normalised 68% marginal widths. With observational effects, the corresponding median compression is $1.29$ bits. These results demonstrate that joint 21-cm-CO reconstruction recovers cosmological information beyond pre-reconstruction summaries.
ER -