Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 518, Issue 2, Pages 2567-2573Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stac3257
Keywords
methods; methods; data analysis - cosmological parameters - large-scale structure of universe; data analysis - cosmological parameters - large-scale structure of universe; methods; data analysis - cosmological parameters - large-scale structure of universe
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When analyzing Lyman alpha three-dimensional correlation functions, standard methods only consider the information from the distinct peak caused by baryon acoustic oscillations. This study investigates whether this compression is enough to capture all the relevant cosmological information. By directly fitting the full shape of synthetic Lyman alpha autocorrelation functions and cross-correlations with quasars, including all physical scales without compression, our approach provides significantly better constraints on parameters like the matter density and the growth term compared to using BAO alone.
When performing cosmological inference, standard analyses of the Lyman alpha (Ly alpha) three-dimensional correlation functions only consider the information carried by the distinct peak produced by baryon acoustic oscillations (BAO). In this work, we address whether this compression is sufficient to capture all the relevant cosmological information carried by these functions. We do this by performing a direct fit to the full shape, including all physical scales without compression, of synthetic Ly alpha autocorrelation functions and cross-correlations with quasars at effective redshift z(eff) = 2.3, assuming a DESI-like survey, and providing a comparison to the classic method applied to the same data set. Our approach leads to a $3.5{{\ \rm per\ cent}}$ constraint on the matter density omega(M), which is about three to four times better than what BAO alone can probe. The growth term f sigma(8)(z(eff)) is constrained to the $10{{\ \rm per\ cent}}$ level, and the spectral index n(s) to $\sim 3-4{{\ \rm per\ cent}}$. We demonstrate that the extra information resulting from our 'direct fit' approach, except for the n(s) constraint, can be traced back to the Alcock-Paczynski effect and redshift space distortion information.
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