Testing SALT Approximations with Numerical Radiation Transfer Code Part 1: Validity and Applicability

TL;DR

This paper compares an analytical radiation transfer model SALT with a numerical code RASCAS to evaluate their accuracy in recovering galactic outflow parameters from UV spectra, leading to model improvements and insights into their applicability.

Contribution

It introduces improvements to SALT and RASCAS, and assesses their effectiveness in parameter recovery from simulated spectra with varying resolutions and turbulence.

Findings

High resolution data allows accurate parameter recovery.

Medium resolution data recovers derived quantities well.

Turbulence introduces biases in parameter estimates, but not in derived quantities.

Abstract

Absorption line spectroscopy offers one of the best opportunities to constrain the properties of galactic outflows and the environment of the circumgalactic medium. Extracting physical information from line profiles is difficult, however, for the physics governing the underlying radiation transfer is complicated and depends on many different parameters. Idealized analytical models are necessary to constrain the large parameter spaces efficiently, but are typically plagued by model degeneracy and systematic errors. Comparison tests with idealized numerical radiation transfer codes offer an excellent opportunity to confront both of these issues. In this paper, we present a detailed comparison between SALT, an analytical radiation transfer model for predicting UV spectra of galactic outflows, with the numerical radiation transfer software, RASCAS. Our analysis has lead to upgrades to both models including an improved derivation of SALT and a customizable adaptive mesh refinement routine for RASCAS. We explore how well SALT, when paired with a Monte Carlo fitting procedure, can recover flow parameters from non-turbulent and turbulent flows. When the velocity and density gradients are excluded, we find that flow parameters are well recovered from high resolution (20 $\rm{km}$ $\rm{s}^{-1}$) data and moderately well from medium resolution (100 $\rm{km}$ $\rm{s}^{-1}$) data without turbulence at a S/N = 10, while derived quantities (e.g., mass outflow rates, column density, etc.) are well recovered at all resolutions. In the turbulent case, biased errors emerge in the recovery of individual parameters, but derived quantities are still well recovered.