Abstract: Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as the distance to a molecular cloud. However, there is a problem in that for the inner Galaxy, two different solutions, the “Near" solution, and the “Far" solution, can be derived simultaneously. We attempted to construct a two-class ( “Near” or “Far” ) inference model using a Convolutional Neural Network (CNN), a form of deep learning that can capture spatial features generally. In this study, we used the CO dataset toward the 1st quadrant of the Galactic plane obtained with the Nobeyama 45-m radio telescope (l = 62-10 degree, |b| < 1 degree). In the model, we applied the three-dimensional distribution (position-position-velocity) of the 12CO (J=1-0) emissions as the main input. The dataset with “Near” or “Far” annotation was made from the HII region catalog of the infrared astronomy satellite WISE to train the model. As a result, we could construct a CNN model with a 76% accuracy rate on the training dataset. By using the model, we determined the distance to molecular clouds identified by the CLUMPFIND algorithm. We found that the mass of the molecular clouds with a distance of < 16.3 kpc identified in the 12CO data follows a power-law distribution with an index of about from -1.5 to -2.3 in the mass range of M >1000 Msun. In particular, the slope was shallow in the arm region and the bar-end region. Also, the detailed molecular gas distribution of the Galaxy as seen from the Galactic North pole was determined. In addition, we obtained a result that approximately 450 cloud-cloud collision events are expected to be included in the data.
Abstract: The discovery of complex organic molecules (COMs) in solar-type protostars highlights the extensive chemical evolution at the onset of planet formation. These molecules, which are potential precursors to pre-biotic molecules, are also found in comets that contain the most pristine matter in the solar system. In recent years, the increasing detection of COMs by interferometric sub-mm/mm observations, such as ALMA and VLA, suggest a common presence of COMs in the early stage of star formation. However, the formation pathways of COMs and whether most protostars undergo similar chemical evolution remain open questions with incomplete observational constraints. It is thought that COMs form in the ice mantles on dust grains followed by thermal sublimation near protostars, but direct observational constraints are scarce. While ALMA provides sub-100 au resolution, a resolution necessary to resolve sites of planet formation, to characterize gaseous COMs in nearby embedded protostars, measurements of chemical composition in ices had been limited by low-resolution and limited sensitivity spectroscopy until JWST, which can probe ices at a spatial scale comparable to that by ALMA with unprecedented sensitivity. In this talk, I will highlight the frontier of complex chemistry from observations of COMs in both gas- and ice-phase. Particularly, I will discuss the recent JWST results on ice in protostellar environments, especially focusing on the latest results of the CORINOS program. We have found potential signatures of icy COMs in a young embedded protostar. I will also discuss the prospects of a holistic chemical analysis of both ice and gas in the era of JWST and ALMA.
Abstract: The James Clerk Maxwell Telescope (JCMT) has been monitoring eight nearby low-mass star-forming regions in the Gould Belt at submillimetre wavelengths for over six years to search for and quantify the time dependent brightness variability of the resident deeply embedded protostars. Secular variability is common among these protostars; greater than 25% of the sample show measurable long-term brightness changes and 10% show burst behaviour lasting months to years. We interpret this secular variability as reflecting changes in the mass accretion rate from the disk to the protostar, as predicted by theoretical models of (proto)stellar assembly. For a subset of our sample we have contemporaneous mid-IR light-curves which allow additional constraints on the conditions responsible for the brightness variations, confirming that the submillimetre variability is driven by changes in the dust temperature profile of the envelope. Furthermore, we have combined, for one source, single dish and interferometric sub-mm monitoring, which has allowed us to unambiguously recover a time lag in the variability at larger angular scales and use the results to confirm the envelope structure surrounding the embedded protostar. More recently, we have added somewhat more distant intermediate mass regions to our JCMT monitoring and collaborated with the Maser Monitoring Organization (M2O) in follow-up of more massive protostar candidate variables.