Revealing the Physical Conditions around Sgr A* using Bayesian Inference -- I. Observations and Radiative Transfer
Tomas A. James, Serena Viti, Farhad Yusef-Zadeh, Marc Royster, Mark, Wardle

TL;DR
This study uses Bayesian inference with radiative transfer models on ALMA observations to map the physical conditions of gas around Sgr A*, revealing variations in temperature, density, and chemical enrichment within the circumnuclear disk.
Contribution
It introduces a Bayesian radiative transfer approach to systematically determine gas physical conditions in the Sgr A* region from high-resolution ALMA data.
Findings
Most gas has T < 500 K and n ≈ 10^6 cm^-3
Identified a hot, dense source in the Northeastern Arm
Detected a cold, extremely dense, potentially bound region
Abstract
We report sub-arcsecond ALMA observations between 272 - 375 GHz towards Sgr A*'s Circumnuclear disk (CND). Our data comprises 8 individual pointings, with significant SiO (8(7) - 7(6)) and SO (7 - 6) emission detected towards 98 positions within these pointings. Additionally, we identify H2CS (9(1,9) - 8(1,8)), OCS (25 - 24) and CH3OH (2(1,1) - 2(0,2)) towards a smaller subset of positions. By using the observed peak line flux density together with a Bayesian Inference technique informed by radiative transfer models, we systematically recover the physical gas conditions towards each of these positions. We estimate that the bulk of the surveyed gas has temperature T < 500 K and density n cm, consistent with previous studies of similar positions as traced by HCN clumps. However, we identify an uncharacteristically hot (T K) and dense (n $\approx…
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