New method for estimating molecular cloud distances based on Gaia, 2MASS, and the TRILEGAL galaxy model

Author:

Mei JuanORCID,Chen ZhiweiORCID,Jiang Zhibo,Zheng Sheng,Feng HaoranORCID

Abstract

We propose a new method for estimating the distances of molecular clouds traced by CO line emission. Stars from 2MASS and Gaia EDR3 are selected as on-cloud stars when they are projected on a cloud. The background on-cloud stars have redder colors on average than the foreground stars. Instead of searching for stars projected away from the cloud, we employed the TRILEGA galaxy model to mimic the stellar population without cloud extinction along the sightline toward the cloud. Our method does not require an exact boundary of a cloud. The boundaries are highly variable and depend on the sensitivity of the molecular line data. For each cloud, we compared the distributions of on-cloud stars to the TRILEGAL stellar populations in the diagram of JKs color versus distance. The intrinsic JKs colors of main-sequence and evolved stars from TRILEGAL were considered separately, and they were used as the baseline for subtracting the observed JKs colors. The baseline-corrected JKs color was deployed with the Bayesian analysis and Markov chain Monte Carlo sampling to determine the distance at which the JKs color jump is largest. This method was successfully applied to measure the distances of 27 molecular clouds, which were selected from previously published cloud samples. By replacing TRILEGAL with the GALAXIA galaxy model, we were able to measure the distances for 21 of the 27 clouds. The distances of the 21 clouds based on the GALAXIA model agree well with those based on the TRILEGAL model. The distances of the 27 clouds estimated by this method are consistent with previous estimates. We will apply this new method to a larger region of the gaseous galactic plane, in particular, for the inner galactic region, where a region free of CO emission is hard to separate from the crowded field of clouds.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

National Key R&D Program of China

CAS Key Research Program of Frontier Sciences

Publisher

EDP Sciences

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