Pith. sign in

REVIEW 4 cited by

Mock data sets for the Eboss and DESI Lyman-α forest surveys

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2310.18996 v2 pith:B66WY5XL submitted 2023-10-29 astro-ph.CO

Mock data sets for the Eboss and DESI Lyman-α forest surveys

classification astro-ph.CO
keywords mockcorrelationsdesiebossfgpafluxlambdasets
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

We present a publicly-available code to generate sets of mock Lyman-$\alpha$ (\lya) forest data that have realistic large-scale correlations including those due to the Baryonic Acoustic Oscillations (BAO). The primary purpose of these mocks is to test the analysis procedures of the Extended Baryon Oscillation Survey (eBOSS) and the Dark Energy Spectroscopy Instrument (DESI) surveys. The transmitted flux fraction, $F(\lambda)$, of background quasars due to \lya\ absorption in the intergalactic medium (IGM) is simulated using the Fluctuating Gunn-Petterson Approximation (FGPA) applied to Gaussian random fields produced through the use of fast Fourier transforms (FFT). The output includes the IGM-\lya\ transmitted flux fraction along quasar lines of sight and a catalog of high-column-density systems appropriately placed at high-density regions of the IGM. This output serves as input to additional code that superimposes the IGM tranmission on realistic quasar spectra, adds absorption by high-column-density systems and metals, and simulates instrumental transmission and noise. Redshift space distortions (RSD) of the flux correlations are implemented by including the large-scale velocity-gradient field in the FGPA resulting in a correlation function of $F(\lambda)$ that can be accurately predicted. One hundred realizations have been produced over the 14,000 deg$^2$ DESI survey footprint with 100 quasars per deg$^{2}$. The analysis of these realizations shows that the correlations of $F(\lambda)$ follows the prediction within the accuracy of eBOSS survey. The most time-consuming part of the mock production occurs before application of the FGPA, and the existing pre-FGPA forests can be used to easily produce new mock sets with modified redshift-dependent bias parameters or observational conditions

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 4 Pith papers

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

  1. Probing the matter-dominated expansion with multi-redshift Lyman-$\alpha$ BAO from DESI DR2

    astro-ph.CO 2026-07 conditional novelty 6.0

    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.

  2. DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest

    astro-ph.CO 2024-04 accept novelty 6.0

    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.

  3. DESI DR2 Results I: Baryon Acoustic Oscillations from the Lyman Alpha Forest

    astro-ph.CO 2025-03 accept novelty 4.0

    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.

  4. Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest

    astro-ph.CO 2026-05 unverdicted novelty 2.0

    Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.