Non-linearities in the Lyman-α forest and in its cross-correlation with dark matter halos. Issue 9 (1st September 2022)

• Record Type: Journal Article
• Authors: Givans, Jahmour J.; Font-Ribera, Andreu; Slosar, Anže; Seeyave, Louise; Pedersen, Christian; Rogers, Keir K.; Garny, Mathias; Blas, Diego; Iršič, Vid
• Is Part Of: Journal of cosmology and astroparticle physics. Volume 2022:Issue 9(2022)
• Publication Date: 2022-09-01
• Subjects: Lyman alpha forest -- power spectrum; Cosmology -- Periodicals; Astrophysics -- Periodicals; 523.0105
• DOI: 10.1088/1475-7516/2022/09/070
• Languages: English
• ISSNs: 1475-7516

Abstract

Abstract: Three-dimensional correlations of the Lyman- α (Ly α ) forest and cross correlations between the Ly α forest and quasars have been measured on large scales, allowing a precise measurement of the baryon acoustic oscillation (BAO) feature at redshifts z > 2. These 3D correlations are often modelled using linear perturbation theory, but full-shape analyses to extract cosmological information beyond BAO will require more realistic models capable of describing non-linearities present at smaller scales. We present a measurement of the Ly α forest flux power spectrum from large hydrodynamic simulations — the Sherwood simulations — and compare it to different models describing the small-scale deviations from linear theory. We confirm that the model presented in Arinyo-i-Prats et al. (2015) fits the measured 3D power up to k = 10 h Mpc -1 with an accuracy better than 5%, and show that the same model can also describe the 1D correlations with similar precision. We also present, for the first time, an equivalent study for the cross-power spectrum of halos with the Ly α forest, and we discuss different challenges we face when modelling the cross-power spectrum beyond linear scales. We make all our measured power spectra public in https://github.com/andreufont/sherwoo_p3d . This study is a step towards joint analyses of 1D and 3D flux correlations, and towards using the quasar-Ly α cross-correlation beyond BAO analyses.