JINGLE V: Dust properties of nearby galaxies derived from hierarchical Bayesian SED fitting
Isabella Lamperti, Am\'elie Saintonge, Ilse De Looze, Gioacchino, Accurso, Christopher J. R. Clark, Matthew W. L. Smith, Christine D. Wilson,, Elias Brinks, Toby Brown, Martin Bureau, David L. Clements, Stephen Eales,, David H. W. Glass, Ho Seong Hwang, Jong Chul Lee, Lihwai Lin

TL;DR
This study uses hierarchical Bayesian SED fitting to analyze dust properties of 192 nearby galaxies, reducing parameter degeneracy and revealing correlations with galaxy characteristics.
Contribution
It introduces a hierarchical Bayesian approach to derive dust parameters, improving accuracy and reducing degeneracy compared to traditional methods.
Findings
Dust temperatures range from 17-30 K.
Beta values range from 0.6 to 2.2.
Beta correlates with stellar mass surface density.
Abstract
We study the dust properties of 192 nearby galaxies from the JINGLE survey using photometric data in the 22-850micron range. We derive the total dust mass, temperature T and emissivity index beta of the galaxies through the fitting of their spectral energy distribution (SED) using a single modified black-body model (SMBB). We apply a hierarchical Bayesian approach that reduces the known degeneracy between T and beta. Applying the hierarchical approach, the strength of the T-beta anti-correlation is reduced from a Pearson correlation coefficient R=-0.79 to R=-0.52. For the JINGLE galaxies we measure dust temperatures in the range 17-30 K and dust emissivity indices beta in the range 0.6-2.2. We compare the SMBB model with the broken emissivity modified black-body (BMBB) and the two modified black-bodies (TMBB) models. The results derived with the SMBB and TMBB are in good agreement, thus…
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