The Physical Conditions in Starbursts Derived from Bayesian Fitting of Mid-IR SEDS: 30 Doradus as a Template
J. R. Mart\'inez-Galarza, B. Groves, B. Brandl, G. E. de Messieres, R., Indebetouw, M. A. Dopita

TL;DR
This paper introduces a Bayesian fitting method for starburst SEDs, validated on 30 Doradus, enabling more accurate derivation of physical conditions and breaking degeneracies in spectral analysis.
Contribution
A novel Bayesian analysis approach for fitting starburst SEDs that improves parameter estimation and degeneracy resolution, validated on 30 Doradus.
Findings
Derived physical parameters match known conditions of 30 Doradus.
Including emission lines is crucial to break degeneracies.
Hot dust (~300K) significantly contributes to mid-IR spectrum.
Abstract
To understand and interpret the observed Spectral Energy Distributions (SEDs) of starbursts, theoretical or semi-empirical SED models are necessary. Yet, while they are well-founded in theory, independent verification and calibration of these models, including the exploration of possible degeneracies between their parameters, are rarely made. As a consequence, a robust fitting method that leads to unique and reproducible results has been lacking. Here we introduce a novel approach based on Bayesian analysis to fit the Spitzer-IRS spectra of starbursts using the SED models proposed by Groves et al. (2008). We demonstrate its capabilities and verify the agreement between the derived best fit parameters and actual physical conditions by modelling the nearby, well-studied, giant HII region 30 Dor in the LMC. The derived physical parameters, such as cluster mass, cluster age, ISM pressure…
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