Joint Bayesian Estimation of Quasar Continua and the Lyman-Alpha Forest Flux Probability Distribution Function
Anna-Christina Eilers, Joseph F. Hennawi, Khee-Gan Lee

TL;DR
This paper introduces a Bayesian MCMC-based method to simultaneously estimate quasar continua and the Lyα forest flux PDF, enabling precise measurement of IGM thermal parameters from high-resolution spectra.
Contribution
The paper presents a novel fully Bayesian continuum fitting algorithm using PCA and MCMC, improving the accuracy of IGM thermal state measurements from quasar spectra.
Findings
Recoveries quasar continua with 7-10% precision at z=3 and z=5.
Achieves nearly unbiased estimates of the IGM temperature-density slope with ~8-9% precision.
Method performs well on mock spectra, promising application to real data.
Abstract
We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Ly forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear Principal Component Analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation , while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method…
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