A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b–NH i Distribution of Absorbers in the Lyα Forest

We present a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0(ρ/ρ 0) γ−1, and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We present a method that exploits all information encoded in the b –N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method’s robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D (T 0, γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure \(\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}\) and \(\gamma ={1.49}_{-0.074}^{+0.073}\) in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on \(\mathrm{log}{T}_{0}\) (γ) nearly two (three) times higher for current data set sizes.