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Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets
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Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets
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The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$\alpha$ (Ly$\alpha$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$\alpha$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$\alpha$ forest. The synthetic data sets span a redshift range $1.8<z<3.8$, and are analysed using the same framework and pipeline used for the DESI 2024 Ly$\alpha$ forest BAO measurement. To measure BAO, we use both the Ly$\alpha$ auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Ly$\alpha$ forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly$\alpha$ forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.
Forward citations
Cited by 12 Pith papers
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DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations
First-year DESI BAO data are consistent with flat LambdaCDM and, when combined with CMB, show a 2.5-3.9 sigma preference for evolving dark energy (w0 > -1, wa < 0) that strengthens with certain supernova datasets.
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Lyman-$\alpha$ forest holography: 3D predictions from 1D measurements
One-dimensional Lyman-α forest power spectrum measurements, propagated through the ForestFlow emulator, predict three-dimensional clustering that matches DESI BAO and ACCEL-2 simulation results.
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DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints
DESI DR2 Lyman-alpha forest full-shape correlations yield a 1% Alcock-Paczyński measurement at z=2.33 and 0.8% distance ratio constraints.
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DESI DR2 Results IV: Alcock-Paczy\'nski Measurements from the Lyman Alpha Forest and Cosmological Constraints
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.
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Probing the matter-dominated expansion with multi-redshift Lyman-$\alpha$ BAO from DESI DR2
DESI DR2 Lyman-alpha BAO measurements split into three redshift bins trace the expansion rate H(z) over z≈2.1–2.8, yielding a power-law slope n=1.34±0.16 consistent with matter-dominated expansion.
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DESI DR2 Baryon Acoustic Oscillations from the Lyman Alpha Forest Multipoles
A Legendre-multipole BAO analysis of the DESI DR2 Lyα forest yields αiso=0.9997±0.0096 and αAP=0.9986±0.0276, consistent with the baseline, using an unsmoothed positive-definite covariance.
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Probing the limits of cosmological information from the Lyman-$\alpha$ forest 2-point correlation functions
Using idealized synthetic data, knowing the true continuum in Lyα forest auto- and cross-correlations reduces uncertainties on the AP parameter and Ω_m by ~10%, with extension to 240 h^{-1}Mpc scales adding up to ~15%...
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Lya2pcf: an efficient pipeline to estimate two- and three-point correlation functions of the Lyman-$\alpha$ forest
Lya2pcf is an efficient pipeline implementing standard algorithms for 2PCF and 3PCF of the Lyman-alpha forest, with GPU speedups over PICCA and the first large-sample anisotropic 3PCF measurement up to 80 Mpc/h.
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DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest
DESI measures BAO from the Lyα forest at z_eff=2.33, reporting H(z) = (239.2 ± 4.8) (147.09 Mpc/rd) km/s/Mpc and DM(z) = (5.84 ± 0.14) (rd/147.09 Mpc) Gpc.
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Validation of the DESI DR2 Ly$\alpha$ forest full-shape analysis
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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DESI DR2 Results I: Baryon Acoustic Oscillations from the Lyman Alpha Forest
DESI DR2 delivers 0.65% precision BAO measurements from the LyA forest at z_eff=2.33, with D_H/r_d = 8.632 ± 0.098 ± 0.026 and D_M/r_d = 38.99 ± 0.52 ± 0.12.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
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