A trailing lognormal approximation of the Lyman-$\alpha$ forest: comparison with full hydrodynamic simulations at $2.2\leq z\leq 2.7$

TL;DR

This paper develops a trailing lognormal model for the Lyman-$\alpha$ forest to improve parameter recovery from simulations, enabling more accurate semi-analytical analysis of cosmic density fields at redshifts 2.2 to 2.7.

Contribution

The authors extend the lognormal model with a trailing approach to better match hydrodynamical simulation data and recover key IGM parameters more accurately.

Findings

The trailing lognormal model improves the estimation of $\Gamma_{12}$ within 1-$\sigma$.

It alleviates over-prediction of Ly$\alpha$ absorbers compared to standard models.

The model enhances the potential for constraining cosmological parameters.

Abstract

Lyman-$\alpha$(Ly$\alpha$) forest in the spectra of distant quasars encodes the information of the underlying cosmic density field at smallest scales. The modelling of the upcoming large and high-fidelity forest data using cosmological hydrodynamical simulations is computationally challenging and therefore, requires accurate semi-analytical techniques. One such approach is based on the assumption that baryonic density fields in the intergalactic medium (IGM) follow lognormal distribution. Keeping this in mind, we extend our earlier work to improve the lognormal model of the Ly$\alpha$ forest in recovering the parameters characterizing IGM state, particularly the hydrogen photoionization rate ($\Gamma_{12}$), between $2.2 \leq z \leq 2.7$, by simulating the model spectra at a slightly lower redshift than the Sherwood smooth particle hydrodynamical simulations (SPH) data. The recovery of thermal parameters, namely, the mean-density IGM temperature ($T_0$) and the slope of the temperature-density relation ($\gamma$) is also alleviated. 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 tend to over-predict the number of Ly$\alpha$ absorbers seen in SPH simulation. A lognormal model simulated at a lower redshift than SPH data can address this limitation to a certain extent. We show that with such a "trailing" model of lognormal distribution, values of $\Gamma_{12}$ are recovered at $\lesssim 1-\sigma$. We argue that this model can be useful for constraining cosmological parameters.