Predictions for the clustering properties of the Lyman-alpha forest – I. One-point statistics |
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Authors: | Enrique Gaztañ aga, Rupert A. C. Croft |
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Affiliation: | Consejo Superior de Investigaciones Científicas (CSIC), Institut d'Estudis Espacials de Catalunya (IEEC), Edf. Nexus-201 - c/ Gran Capitan 2-4, 08034 Barcelona, Spain; Astronomy Department, Harvard University, 60 Garden Street, Cambridge, MA 01238, USA |
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Abstract: | We present predictions for the one-point probability distribution and cumulants of the transmitted QSO flux in the high redshift Lyman- α forest. We make use of the correlation between the Lyman- α optical depth and the underlying matter density predicted by gravitational instability theory and seen in numerical hydrodynamic simulations. We have modelled the growth of matter fluctuations using the non-linear shear‐free dynamics, an approximation which reproduces well the results of perturbation theory for the cumulants in the linear and weakly non-linear clustering regime. As high matter overdensities tend to saturate in spectra, the statistics of the flux distribution are dominated by weakly non-linear overdensities. As a result, our analytic approach can produce accurate predictions, when tested against N -body simulation results, even when the underlying matter field has root-mean-square fluctuations larger than unity. Our treatment can be applied to either Gaussian or non-Gaussian initial conditions. Here we concentrate on the former case, but also include a study of a specific non-Gaussian model. We discuss how the methods and predictions we present can be used as a tool to study the generic clustering properties of the Lyman- α forest at high redshift. With such an approach, rather than concentrating on simulating specific cosmological models, we may be in a position to directly test our assumptions for the Gaussian nature of the initial conditions, and the gravitational instability origin of structure itself. In a separate paper we present results for two-point statistics. |
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Keywords: | methods: numerical large-scale structure of Universe |
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