Improving cosmological distance measurements at high redshift using Lyman-Alpha forest BAO reconstruction

Abstract

The Dark Energy Spectroscopic Instrument (DESI) measures baryon acoustic oscillations (BAO) in the Lyman-α (Lyman-alpha) forest and provides a robust probe of the expansion history in the matter-dominated era. Yet, non-linear structure formation broadens and shifts the BAO peak. To undo these effects, we extend standard Zel'dovich reconstruction, routinely applied to galaxy surveys, to the Lyman-alpha forest. We validate our methodology on large-volume idealized Lyman-alpha forest mocks painted on top of the \textsc{AbacusSummit} N-body simulations, using linear control variates to suppress sample variance and thereby reduce the error bars by a factor of up to ≈ √(50). In fully sampled periodic boxes, reconstruction halves the radial BAO damping scale and reduces the uncertainties on the radial (apar) and transverse (aperp) scaling parameters by ≈25% and ≈15%, respectively. It also reduces the non-linear shift from Δapar=+0.3% to +0.10±0.07%, while aperp remains unbiased. To make this approach readily applicable to observational data, we demonstrate the impact of a survey mask with a DESI-like density of 50 deg⁻². For this mask, we compare two approaches to estimate the displacement field: either directly from the Lyman-alpha forest or using an external tracer with a number density of n̅ ≃ 10⁻³ h³Mpc⁻³, such as Lyman-break galaxies and Lyman-α emitters---both key targets for DESI-II. Both approaches give comparable gains and reduce the uncertainties on apar and aperp by ≈ 27% and ≈ 10%, respectively, with mild improvements for futuristic high-density surveys with 160 deg⁻². Correspondingly, the figure of merit improves by factors of $1.66$ for fully sampled boxes, $1.65$ for a DESI-like, and $1.76$ for a high-density survey.

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BibTeX RIS

BibTeX

@misc{hadzhiyska2026improving,
  title = {{Improving cosmological distance measurements at high redshift using Lyman-Alpha forest BAO reconstruction}},
  author = {Boryana Hadzhiyska and Roger de Belsunce},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.37664},
  eprint = {2610.37664},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.37664},
}

RIS

TY  - UNPB
TI  - Improving cosmological distance measurements at high redshift using Lyman-Alpha forest BAO reconstruction
AU  - Boryana Hadzhiyska
AU  - Roger de Belsunce
PY  - 2026
DA  - 2026/10/27
PB  - arXiv
DO  - 10.48550/arxiv.2610.37664
UR  - https://arxiv.org/abs/2610.37664
AB  - The Dark Energy Spectroscopic Instrument (DESI) measures baryon acoustic oscillations (BAO) in the Lyman-α (Lyman-alpha) forest and provides a robust probe of the expansion history in the matter-dominated era. Yet, non-linear structure formation broadens and shifts the BAO peak. To undo these effects, we extend standard Zel'dovich reconstruction, routinely applied to galaxy surveys, to the Lyman-alpha forest. We validate our methodology on large-volume idealized Lyman-alpha forest mocks painted on top of the \textsc{AbacusSummit} N-body simulations, using linear control variates to suppress sample variance and thereby reduce the error bars by a factor of up to ≈ √(50). In fully sampled periodic boxes, reconstruction halves the radial BAO damping scale and reduces the uncertainties on the radial (apar) and transverse (aperp) scaling parameters by ≈25% and ≈15%, respectively. It also reduces the non-linear shift from Δapar=+0.3% to +0.10±0.07%, while aperp remains unbiased. To make this approach readily applicable to observational data, we demonstrate the impact of a survey mask with a DESI-like density of 50 deg^−2. For this mask, we compare two approaches to estimate the displacement field: either directly from the Lyman-alpha forest or using an external tracer with a number density of n̅ ≃ 10^−3 h^3Mpc^−3, such as Lyman-break galaxies and Lyman-α emitters---both key targets for DESI-II. Both approaches give comparable gains and reduce the uncertainties on apar and aperp by ≈ 27% and ≈ 10%, respectively, with mild improvements for futuristic high-density surveys with 160 deg^−2. Correspondingly, the figure of merit improves by factors of $1.66$ for fully sampled boxes, $1.65$ for a DESI-like, and $1.76$ for a high-density survey.
ER  -

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