The Alcock-Paczy\'nski effect from Lyman-$\alpha$ forest correlations: Analysis validation with synthetic data
Andrei Cuceu, Andreu Font-Ribera, Paul Martini, Benjamin Joachimi,, Seshadri Nadathur, James Rich, Alma X. Gonz\'alez-Morales, H\'elion du Mas, des Bourboux, James Farr

TL;DR
This paper validates a method to extract detailed cosmological information from the Ly$ ext{α}$ forest correlations using synthetic eBOSS data, demonstrating unbiased full-shape measurements of key distance ratios and discussing analysis optimizations.
Contribution
It introduces a validation framework for full-shape Ly$ ext{α}$ forest correlation analysis using synthetic data, enhancing the potential for more precise cosmological constraints.
Findings
The model performs well on synthetic data.
Unbiased measurement of $D_M/D_H(z_{eff})$ is achieved.
Full-shape analysis could improve precision to about 2%."
Abstract
The three-dimensional distribution of the Ly forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly forest correlations through the Alcock-Paczy\'nski (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of one hundred eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the one hundred eBOSS realizations, and find that our model of the Ly correlations performs well on…
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Taxonomy
TopicsMeteorological Phenomena and Simulations
