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Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: New models and constraints from the eBOSS measurement
Michael Walther, Nils Schöneberg, Solène Chabanier +8
We present the Lyssa suite of high-resolution cosmological simulations of the Lyman- forest designed for cosmological analyses. These 18 simulations have been run using the Nyx…
DESI 2024 VII: Cosmological Constraints from the Full-Shape Modeling of Clustering Measurements
DESI Collaboration, A. G. Adame, J. Aguilar +210
We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman- forest tracers from the first year of observations with the Dark Energy Spectrosc…
DESI 2024 II: Sample Definitions, Characteristics, and Two-point Clustering Statistics
DESI Collaboration, A. G. Adame, J. Aguilar +200
We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale struc…
DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars
A. G. Adame, J. Aguilar, S. Ahlen +195
We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range divi…
The ACCEL project: simulating Lyman- forest in large-volume hydrodynamical simulations
Solène Chabanier, Corentin Ravoux, Lucas Latrille +5
Cosmological information is usually extracted from the Lyman- forest correlations using only either large-scale information interpreted through linear theory or using small-scal…
CMB lensing and Lyα forest cross bispectrum from DESI's first-year quasar sample
N. G. Karaçaylı, P. Martini, D. H. Weinberg +50
The squeezed cross-bispectrum \bispeconed\ between the gravitational lensing in the Cosmic Microwave Background and the 1D \lya\ forest power spectrum can constrain bias parameters…
Validation of the DESI 2024 Ly forest BAO analysis using synthetic datasets
Andrei Cuceu, Hiram K. Herrera-Alcantar, Calum Gordon +56
The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman- (Ly) forest spectra ever observed. This data, collected in the…
DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars
DESI Collaboration, A. G. Adame, J. Aguilar +193
We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1<z<2.1. Divided…
High redshift LBGs from deep broadband imaging for future spectroscopic surveys
Vanina Ruhlmann-Kleider, Christophe Yèche, Christophe Magneville +60
Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, , a region only covered so far by Lyman- forest measurements. In this paper,…
Characterization of contaminants in the Lyman-alpha forest auto-correlation with DESI
J. Guy, S. Gontcho A Gontcho, E. Armengaud +61
Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-alpha forest auto-correlation and its cross-correlation with quasar positi…
DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations
DESI Collaboration, A. G. Adame, J. Aguilar +200
We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman- forest tracers from the first year of observations from t…
DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest
DESI Collaboration, A. G. Adame, J. Aguilar +196
We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman- (Ly) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectrosc…
Synthetic spectra for Lyman- forest analysis in the Dark Energy Spectroscopic Instrument
Hiram K. Herrera-Alcantar, Andrea Muñoz-Gutiérrez, Ting Tan +51
Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In th…