Joint modeling of the probability distribution and power spectrum of the Lya forest: comparison with observations at z=3

Details Joint modeling of the probability distribution and power spectrum of the Lya forest: comparison with observations at z=3 Joint modeling of the probability distribution and power spectrum of the Lya forest: comparison with observations at z=3

2004-10-26

arxiv.org/abs/astro-ph/0410618v2

Mon.Not.Roy.Astron.Soc. 361 (2005) 1257-1272

Astronomy and Astrophysics

Astrophysics

revised version. new section discussing the impact of the PDF covariance matrix on the results. new figure comparing the const

Scientific paper

10.1111/j.1365-2966.2005.09254.x

We presents results of joint modeling of the probability distribution function (PDF) and the one-dimensional power spectrum (PS) of the Lya forest flux decrement. The sensitivity of these statistical measures to the shape and amplitude of the linear matter power spectrum is investigated using two variants of the LCDM cosmology. In the first model, the linear power spectrum has a scale-invariant spectral index, whereas in the second, it has a negative running index (RSI). We generate mock catalogs of QSO spectra, and compare their statistical properties to those of the observations at z=3. We perform a joint fit of the power spectrum and PDF. A scale-invariant model with \sigma_8=0.9 matches well the data if the mean IGM temperature is T\leq 15000K. For higher temperature, it tends to overestimate the flux power spectrum over scales k < 0.01s/km. The discrepancy is less severe when the PS alone is fitted. However, models matching the PS alone do not yield a good fit to the PDF. A joint analysis of the flux PS and PDF tightens the constraints on the model parameters and reduces systematic biases. The RSI model is consistent with the observed PS and PDF only if the temperature is T\geq 20000K. The best fit models reproduce the slope and normalisation of the column density distribution, irrespective of the shape and amplitude of the linear power spectrum. They are also consistent with the observed line-width distribution given the large uncertainties. Our joint analysis suggests that \sigma_8 is likely to be in the range 0.7 - 0.9 for a temperature 10000K

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