Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder

Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities. The availability of rich contextual information requires a nimble learning scheme that tightly integrates with deep neural networks and has the ability to capture correlation structures among exponentially many outcomes. We propose MEDL_CVAE, which encodes a conditional multivariate distribution as a generating process. As a result, the variational lower bound of the joint likelihood can be optimized via a conditional variational auto-encoder and trained end-to-end on GPUs. Our MEDL_CVAE was motivated by two real-world applications in computational sustainability: one studies the spatial correlation among multiple bird species using the eBird data and the other models multi-dimensional landscape composition and human footprint in the Amazon rainforest with satellite images. We show that MEDL_CVAE captures rich dependency structures, scales better than previous methods, and further improves on the joint likelihood taking advantage of very large datasets that are beyond the capacity of previous methods.Comment: The first two authors contribute equall

Physical properties of CO-dark molecular gas traced by C+^+

Neither HI nor CO emission can reveal a significant quantity of so-called dark gas in the interstellar medium (ISM). It is considered that CO-dark molecular gas (DMG), the molecular gas with no or weak CO emission, dominates dark gas. We identified 36 DMG clouds with C$^+$ emission (data from Galactic Observations of Terahertz C+ (GOT C+) project) and HINSA features. Based on uncertainty analysis, optical depth of HI $\tau\rm_{HI}$ of 1 is a reasonable value for most clouds. With the assumption of $\tau\rm_{HI}=1$, these clouds were characterized by excitation temperatures in a range of 20 K to 92 K with a median value of 55 K and volume densities in the range of $6.2\times10^1$ cm$^{-3}$ to $1.2\times 10^3$ cm$^{-3}$ with a median value of $2.3\times 10^2$ cm$^{-3}$. The fraction of DMG column density in the cloud ($f\rm_{DMG}$) decreases with increasing excitation temperature following an empirical relation $f\rm_{DMG}=-2.1\times 10^{-3}T_(ex,\tau_{HI}=1)$+1.0. The relation between $f\rm_{DMG}$ and total hydrogen column density $N_H$ is given by $f\rm_{DMG}$=$1.0-3.7\times 10^{20}/N_H$. The values of $f\rm_{DMG}$ in the clouds of low extinction group ($A\rm_V \le 2.7$ mag) are consistent with the results of the time-dependent, chemical evolutionary model at the age of ~ 10 Myr. Our empirical relation cannot be explained by the chemical evolutionary model for clouds in the high extinction group ($A\rm_V > 2.7$ mag). Compared to clouds in the low extinction group ($A\rm_V \le 2.7$ mag), clouds in the high extinction group ($A\rm_V > 2.7$ mag) have comparable volume densities but excitation temperatures that are 1.5 times lower. Moreover, CO abundances in clouds of the high extinction group ($A\rm_V > 2.7$ mag) are $6.6\times 10^2$ times smaller than the canonical value in the Milky Way. #[Full version of abstract is shown in the text.]#Comment: Accepted for publishing in Astronomy & Astrophysics. 13 pages, 8 figure

Quantifying Dark Gas

A growing body of evidence has been supporting the existence of so-called "dark molecular gas" (DMG), which is invisible in the most common tracer of molecular gas, i.e., CO rotational emission. DMG is believed to be the main gas component of the intermediate extinction region between A$\rm_v$$\sim$0.05-2, roughly corresponding to the self-shielding threshold of H$_2$ and $^{13}$CO. To quantify DMG relative to HI and CO, we are pursuing three observational techniques, namely, HI self-absorption, OH absorption, and TeraHz C$^+$ emission. In this paper, we focus on preliminary results from a CO and OH absorption survey of DMG candidates. Our analysis show that the OH excitation temperature is close to that of the Galactic continuum background and that OH is a good DMG tracer co-existing with molecular hydrogen in regions without CO. Through systematic "absorption mapping" by Square Kilometer Array (SKA) and ALMA, we will have unprecedented, comprehensive knowledge of the ISM components including DMG in terms of their temperature and density, which will impact our understanding of galaxy evolution and star formation profoundly.Comment: 4 pages, 5 figures, Proceedings Asia-Pacific Regional IAU Meeting (APRIM) 201