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Measuring and unbiasing the BAO shift in the Lyman-Alpha forest with AbacusSummit

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arxiv 2503.13442 v1 pith:ZYTN3UNB submitted 2025-03-17 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords alphashiftforestcross-correlationdeltadesidirectionerror
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

The currently observing Dark Energy Spectroscopic Instrument (DESI) places sub-percent constraints on the Baryon Acoustic Oscillations (BAO) scaling parameters from the Lyman-$\alpha$ (Ly-$\alpha$) forest. However, no systematic error budget stemming from non-linearities in the 3D clustering of the Ly-$\alpha$ forest is included in the DESI-Ly-$\alpha$ analysis. In this work, we measure the size of the shift of the BAO peak using large Ly-$\alpha$ forest mocks produced on the $N$-body simulation suite \textsc{AbacusSummit}. Specifically, we measure the Ly-$\alpha$ auto-correlation and the Ly-$\alpha$-quasar cross-correlation functions. We use the DESI Ly-$\alpha$ forest fitting pipeline, \textsc{Vega}, with the publicly available covariance matrix from eBOSS DR16. To mitigate the noise, we adopt a linear control variates (LCV) technique, reducing the error bars by a factor of up to $\sim \sqrt{50}$ on large scales. From the auto-correlation, we detect a small positive shift in radial direction of $\Delta \alpha_\parallel = 0.35\%$ at the 3$\sigma$ level and virtually no shift in the transverse direction, $\alpha_\perp$. From the cross-correlation, we see a similar shift to $\Delta\alpha_\parallel$, albeit with larger error bars, and a small negative shift, $\Delta \alpha_\perp=\sim$0.25\%, at the 2$\sigma$ level. We also make a connection with the Ly-$\alpha$ forest effective field theory (EFT) framework and find that the one-loop EFT power spectrum yields unbiased measurements of the BAO shift parameters in radial and transverse direction for Ly-$\alpha$ auto and the Ly-$\alpha$-quasar cross-correlation measurements. When using the one-loop EFT framework, we find that we can recover the BAO parameters without a shift, which has important implications for future Ly-$\alpha$ forest analyses based on EFT. This work paves the way for the full-shape analysis of DESI and future surveys.

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Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Modeling the Cosmological Lyman-$\alpha$ Forest at the Field Level

    astro-ph.CO 2025-06 conditional novelty 7.0 of 10

    An effective-field-theory forward model reproduces the Lyman-alpha forest field from a hydrodynamic simulation at percent level, down to a few megaparsecs, using the same initial conditions.

  2. Constraining Dynamical Dark Energy from Galaxy Clustering with Simulation-Based Priors

    astro-ph.CO 2025-06 conditional novelty 7.0 of 10

    Adding BOSS galaxy clustering with simulation-based priors modeled as Gaussian mixtures shifts the DESI plus CMB plus supernova constraints on dark energy toward a cosmological constant and improves the w0-wa figure o...

  3. DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    The full shape of DESI DR2 Lyman-alpha forest correlations constrains the distance ratio DM/DH at z=2.33 to 1.0%, twice as precise as BAO alone.

  4. Bridging Simulations and EFT: A Hybrid Model of the Lyman-Alpha Forest Field

    astro-ph.CO 2025-12 conditional novelty 6.0 of 10

    A hybrid EFT forward model using N-body displacements reproduces the simulated Lyman-alpha forest to 5% at k <= 1 h/Mpc with a white-noise residual.

  5. The Compressed 3D Lyman-Alpha Forest Bispectrum

    astro-ph.CO 2025-10 conditional novelty 6.0 of 10

    The Lyman-alpha forest bispectrum can be compressed into 26 skew spectra, including a new shifted variant, with tree-level EFT predictions matching simulations at 1-2 sigma up to k≈0.17 h/Mpc.

  6. Validation of the DESI DR2 Ly$\alpha$ forest full-shape analysis

    astro-ph.CO 2026-07 conditional novelty 5.0 of 10

    The DESI DR2 Lyman-alpha full-shape analysis passes validation for BAO and Alcock-Paczynski parameters on 400 mocks and blinded data, while f-sigma-8 is rejected due to a roughly 10% mock bias.

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