Abstract
Abstract
Observations of the Lyman-α forest in distant quasar spectra with upcoming surveys
are expected to provide significantly larger and higher-quality datasets. To interpret these
datasets, it is imperative to develop efficient simulations. One such approach is based on the
assumption that baryonic densities in the intergalactic medium (IGM) follow a lognormal
distribution. We extend our earlier work to assess the robustness of the lognormal model of the
Lyman-α forest in recovering the parameters characterizing IGM state, namely, the
mean-density IGM temperature (T
0), the slope of the temperature-density relation (γ),
and the hydrogen photoionization rate (Γ12), by comparing with high-resolution Sherwood
SPH simulations across the redshift range 2 ≤ z ≤ 2.7. These parameters are estimated
through a Markov Chain Monte Carlo (MCMC) technique, using the mean and power spectrum of the
transmitted flux. We find that the usual lognormal distribution of IGM densities cannot recover
the parameters of the SPH simulations. This limitation arises from the fact that the SPH baryonic
density distribution cannot be described by a simple lognormal form. To address this, we extend
the model by scaling the linear density contrast by a parameter ν. While the resulting
baryonic density is still lognormal, the additional parameter gives us extra freedom in setting
the variance of density fluctuations. With this extension, values of T
0 and γ implied in
the SPH simulations are recovered at ∼ 1 - σ (≲ 10%) of the median (best-fit)
values for most redshifts bins. However, this extended lognormal model cannot recover
Γ12 reliably, with the best-fit value discrepant by ≳ 3 - σ for z >
2.2. Despite this limitation in the recovery of Γ12, whose origins we explain, we argue
that the model remains useful for constraining cosmological parameters.