Cosmic density field reconstruction from Ly-alpha forest data

Abstract

We present a novel, fast method to recover the density field through the statistics of the transmitted flux in high redshift quasar absorption spectra. The proposed technique requires the computation of the probability distribution function of the transmitted flux (P_F) in the Ly-alpha forest region and, as a sole assumption, the knowledge of the probability distribution function of the matter density field (P_Delta). We show that the probability density conservation of the flux and matter density unveils a flux-density (F-Delta) relation which can be used to invert the Ly-alpha forest without any assumption on the physical properties of the intergalactic medium. We test our inversion method at z=3 through the following steps: [i] simulation of a sample of synthetic spectra for which P_Delta is known; [ii] computation of P_F; [iii] inversion of the Ly-alpha forest through the F-Delta relation. Our technique, when applied to only 10 observed spectra characterized by a signal-to noise ratio S/N >= 100 provides an exquisite (relative error epsilon_Delta <~ 12 % in >~ 50 % of the pixels) reconstruction of the density field in >~ 90 % of the line of sight. We finally discuss strengths and limitations of the method.

5 pages, 3 figures, accepted for publication in MNRAS Letters

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• LyMAS: Predicting Large-Scale Lyman-alpha Forest Statistics from the Dark Matter Density Field
• Inferring high redshift large-scale structure dynamics from the Lyman-alpha forest
• Simba: The average properties of the circumgalactic medium of $2\le z\le 3$ quasars are determined primarily by stellar feedback
• A hierarchical field-level inference approach to reconstruction from sparse Lyman-$\alpha$ forest data
• Mapping Lyman-alpha forest three-dimensional large scale structure in real and redshift space
• Searching for dilaton fields in the Ly$\alpha$ forest
• A Novel Estimator for the Equation of State of the IGM by Ly$\alpha$ Forest Tomography
• An Optimized Ly$\alpha$ Forest Inversion Tool Based on a Quantitative Comparison of Existing Reconstruction Methods