Histogram of oriented gradients: a technique for the study of molecular cloud formation
J. D. Soler, H. Beuther, M. Rugel, Y. Wang, P.C. Clark, S.C.O. Glover,, P.F. Goldsmith, M. Heyer, L.D. Anderson, A. Goodman, Th. Henning, J., Kainulainen, R.S. Klessen, S.N. Longmore, N.M. McClure-Griffiths, K.M., Menten, J.C. Mottram, J. Ott, S.E. Ragan, R.J. Smith

TL;DR
This paper introduces the Histogram of Oriented Gradients (HOG), a machine vision tool for analyzing spatial correlations in molecular cloud observations, validated with simulations and applied to Galactic data to study cloud formation.
Contribution
The paper presents HOG as a novel metric for characterizing gas observations and investigates molecular cloud formation through synthetic and real data analysis.
Findings
HOG reveals significant spatial correlations between HI and $^{13}$CO in velocity channels.
Correlations are observed in both simulated and actual Galactic data.
Velocity offsets in correlations suggest effects of feedback and complex physical conditions.
Abstract
We introduce the histogram of oriented gradients (HOG), a tool developed for machine vision that we propose as a new metric for the systematic characterization of observations of atomic and molecular gas and the study of molecular cloud formation models. In essence, the HOG technique takes as input extended spectral-line observations from two tracers and provides an estimate of their spatial correlation across velocity channels. We characterize HOG using synthetic observations of HI and CO(J=1-0) emission from numerical simulations of MHD turbulence leading to the formation of molecular gas after the collision of two atomic clouds. We find a significant spatial correlation between the two tracers in velocity channels where , independent of the orientation of the collision with respect to the line of sight. We use HOG to investigate the spatial…
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