Detecting Organic Molecules in Star-Forming Regions with Markov Chain Monte Carlo Inference

Spectroscopic radio observations enable studies of the chemical composition of star-forming regions based on their distinct molecular emission and absorption spectra. Emission from heavy molecules is distributed over many lines, too weak to detect individually. To address this, we adapt and implement a Markov Chain Monte Carlo (MCMC) algorithm to enhance signal detection in radio spectra from the Deep Space Network’s (DSN) 70-m antenna in Canberra. This stacking approach leads to a robust detection of a HC7N in the Chamaeleon I molecular cloud core and shows promise for the detection of elusive ring species such as benzonitrile.