Aneta Siemiginowska, Gwendolyn Eadie, Ian Czekala, Eric Feigelson, Eric B. Ford, Vinay Kashyap, Michael Kuhn, and et al. 5/2019. “The Next Decade of Astroinformatics and Astrostatistics.” Bulletin of the American Astronomical Society, 51, Pp. 355. Publisher's VersionAbstract

Over the past century, major advances in astronomy and astrophysics have been driven by improvements in instrumentation. With the amassing of high quality data from new telescopes it is becoming clear that research in astrostatistics and astroinformatics will be necessary to develop new methodology needed in astronomy.

J.D. Soler, H. Beuther, M. Rugel, Y. Wang, P. C. Clark, S. C. O. Glover, P. F. Goldsmith, and et al. 2/2019. “Histogram of Oriented Gradients: A Technique for the Study of Molecular Cloud Formation.” Astronomy and Astrophysics, 622, Pp. A166. Publisher's VersionAbstract

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 spectral line 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 characterized HOG using synthetic observations of HI and 13CO (J = 1 → 0) emission from numerical simulations of magnetohydrodynamic (MHD) turbulence leading to the formation of molecular gas after the collision of two atomic clouds. We found a significant spatial correlation between the two tracers in velocity channels where vHI ≈ v13CO, almost independent of the orientation of the collision with respect to the line of sight. Subsequently, we used HOG to investigate the spatial correlation of the HI, from The HI/OH/recombination line survey of the inner Milky Way (THOR), and the 13CO (J = 1 → 0) emission from the Galactic Ring Survey (GRS), toward the portion of the Galactic plane 33°.75 ≤l ≤ 35°.25 and |b| ≤ 1°.25. We found a significant spatial correlation between the two tracers in extended portions of the studied region. Although some of the regions with high spatial correlation are associated with HI self-absorption (HISA) features, suggesting that it is produced by the cold atomic gas, the correlation is not exclusive to this kind of region. The HOG results derived for the observational data indicate significant differences between individual regions: some show spatial correlation in channels around vHI ≈ v13CO while others present spatial correlations in velocity channels separated by a few kilometers per second. We associate these velocity offsets to the effect of feedback and to the presence of physical conditions that are not included in the atomic-cloud-collision simulations, such as more general magnetic field configurations, shear, and global gas infall.

H. Houghton, P. Udomprasert, S. Sunbury, E. Wright, A. Goodman, E. Johnson, and A. Bishop. 2019. “Cultivating Curiosity with Life in the Universe and WorldWide Telescope.” Astronomical Society of the Pacific, 524, 273.Abstract
When students encounter complex topics like the search for extraterrestrial life, questions abound - thoughtful, unpredictable, and often profound. Despite this thriving curiosity, the first step to be able to explore complex questions is developing the capacity to verbalize a meaningful question. The WorldWide Telescope Ambassadors team designed an out-of-school curriculum called Life in the Universe, which engages middle school-aged students in the science and scientific process of the search for distant life. Students practice generating meaningful questions, which will guide them through the science content, as groups of students build to culminating capstone projects. Results from surveys administered to participating students indicate gains in curiosity in science, as well as in seeing oneself as successful in science.
Hope How-Huan Chen, Jaime E. Pineda, Stella S. R. Offner, Alyssa A. Goodman, and alia. 2019. “Droplets II: Internal Velocity Structures and Potential Rotational Motions in Coherent Cores.” arXiv, 1908, 04367. Publisher's VersionAbstract
We present an analysis of the internal velocity structures of the newly identified sub-0.1 pc coherent structures, droplets, in L1688 and B18. By fitting 2D linear velocity fields to the observed maps of velocity centroids, we determine the magnitudes of linear velocity gradients and examine the potential rotational motions that could lead to the observed velocity gradients. The results show that the droplets follow the same power-law relation between the velocity gradient and size found for larger-scale dense cores. Assuming that rotational motion giving rise to the observed velocity gradient in each core is a solid-body rotation of a rotating body with a uniform density, we derive the "net rotational motions" of the droplets. We find a ratio between rotational and gravitational energies, β, of ∼0.046 for the droplets, and when including both droplets and larger-scale dense cores, we find β∼0.039. We then examine the alignment between the velocity gradient and the major axis of each droplet, using methods adapted from the histogram of relative orientations (HRO) introduced by Soler et al. (2013). We find no definitive correlation between the directions of velocity gradients and the elongations of the cores. Lastly, we discuss physical processes other than rotation that may give rise to the observed velocity field.
Jorma Harju, Jaime E. Pineda, Anton I. Vasyunin, Paola Caselli, Stella S. R. Offner, Alyssa A. Goodman, and alia. 2019. “Efficient methanol desorption in shear instability.” arXiv, 1903, 11298. Publisher's VersionAbstract
We present ALMA maps of the starless molecular cloud core Ophiuchus/H-MM1 in the lines of deuterated ammonia (ortho-NH2D), methanol (CH3OH), and sulphur monoxide (SO). The dense core is seen in NH2D emission, whereas the CH3OH and SO distributions form a halo surrounding the core. Because methanol is formed on grain surfaces, its emission highlights regions where desorption from grains is particularly efficient. Methanol and sulphur monoxide are most abundant in a narrow zone that follows the eastern side of the core. This side is sheltered from the stronger external radiation field coming from the west. We show that photodissociation on the illuminated side can give rise to an asymmetric methanol distribution, but that the stark contrast observed in H-MM1 is hard to explain without assuming enhanced desorption on the shaded side. The region of the brightest emission has a wavy structure that rolls up at one end. This is the signature of Kelvin-Helmholtz instability occurring in sheared flows. We suggest that in this zone, methanol and sulphur are released as a result of grain-grain collisions induced by shear vorticity.
Catherine Zucker, Joshua S. Speagle, Edward F. Schlafly, Gregory M. Green, Douglas P. Finkbeiner, Alyssa A. Goodman, and João Alves. 2019. “A Large Catalog of Accurate Distances to Local Molecular Clouds: The Gaia DR2 Edition.” arXiv e-prints, Pp. arXiv:1902.01425.
C. Zucker, J. S. Speagle, E. Schlafly, G. M. Green, D. P. Finkbeiner, A. Goodman, and J. Alves. 2019. “VizieR Online Data Catalog: Distances to molecular clouds in SFR (Zucker+, 2020).” VizieR Online Data Catalog, J/A+A/633/A51.Abstract

Distances to ~60 star-forming regions in Reipurth (2008, Star Formation Handbook, vols I and II) have been computed using stellar photometry and Gaia DR2 parallax measurements. Usually, several distance estimates are taken across each cloud.


For each sightline, the median distance (d50) is provided, plus the 16th and 84th percentiles on the distance probability distribution function. There is an additional systematic uncertainty, which is unknown but estimated to be ~5% in distance for clouds <1.5kpc, ~10% in distance for clouds >1.5kpc, and ~7% in distance for the southern clouds Lupus, Chamaeleon, and Corona Australis. These should be added in quadrature with the statistical uncertainties reported in the table. In addition to the distances, ancillary model parameters used in our fit are also included (e.g. the amount of foreground extinction "f"). See Section 3.2.1 and Section 3.2.2 in Zucker et al. (2019ApJ...879..125Z) for a complete description of model parameters.
Michelle Ntampaka, Camille Avestruz, Steven Boada, Joao Caldeira, Jessi Cisewski-Kehe, Rosanne Di Stefano, Cora Dvorkin, August E. Evrard, Arya Farahi, Doug Finkbeiner, Shy Genel, Alyssa Goodman, and alia. 2019. “The Role of Machine Learning in the Next Decade of Cosmology.” Bulletin of the American Astronomical Society, 51, 14. Publisher's VersionAbstract
In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.
Josefa E. Großschedl, João Alves, Stefan Meingast, Christine Ackerl, Joana Ascenso, Hervé Bouy, Andreas Burkert, Jan Forbrich, Verena Fürnkranz, Alyssa Goodman, Álvaro Hacar, Gabor Herbst-Kiss, Charles J. Lada, Irati Larreina, Kieran Leschinski, Marco Lombardi, André Moitinho, Daniel Mortimer, and Eleonora Zari. 2018. “3D shape of Orion A from Gaia DR2.” Astronomy & Astrophysics, 619, Pp. A106.
Philip Rosenfield, Jonathan Fay, Ronald K. Gilchrist, Chenzhou Cui, A. David Weigel, Thomas Robitaille, Oderah Justin Otor, and Alyssa Goodman. 2018. “AAS WorldWide Telescope: A Seamless, Cross-platform Data Visualization Engine for Astronomy Research, Education, and Democratizing Data.” The Astrophysical Journal Supplement Series, 236, Pp. 22.
Hope How-Huan Chen, Blakesley Burkhart, Alyssa Goodman, and David C. Collins. 2018. “The Anatomy of the Column Density Probability Distribution Function (N-PDF).” The Astrophysical Journal, 859, Pp. 162.
Shuo Kong, Héctor G. Arce, Jesse R. Feddersen, John M. Carpenter, Fumitaka Nakamura, Yoshito Shimajiri, Andrea Isella, Volker Ossenkopf-Okada, Anneila I. Sargent, Álvaro Sánchez-Monge, Sümeyye T. Suri, Jens Kauffmann, Thushara Pillai, Jaime E. Pineda, Jin Koda, John Bally, Dariusz C. Lis, Paolo Padoan, Ralf Klessen, Steve Mairs, Alyssa Goodman, Paul Goldsmith, Peregrine McGehee, Peter Schilke, Peter J. Teuben, Mar'ıa José Maureira, Chihomi Hara, Adam Ginsburg, Blakesley Burkhart, Rowan J. Smith, Anika Schmiedeke, Jorge L. Pineda, Shun Ishii, Kazushige Sasaki, Ryohei Kawabe, Yumiko Urasawa, Shuri Oyamada, and Yoshihiro Tanabe. 2018. “The CARMA-NRO Orion Survey.” The Astrophysical Journal Supplement Series, 236, Pp. 25.
Kristina Monsch, Jaime E. Pineda, Hauyu Baobab Liu, Catherine Zucker, Hope How-Huan Chen, Kate Pattle, Stella S. R. Offner, James Di Francesco, Adam Ginsburg, Barbara Ercolano, Héctor G. Arce, Rachel Friesen, Helen Kirk, Paola Caselli, and Alyssa A. Goodman. 2018. “Dense Gas Kinematics and a Narrow Filament in the Orion A OMC1 Region Using NH₃.” The Astrophysical Journal, 861, Pp. 77.
Hope How-Huan Chen, Jaime E. Pineda, Alyssa A. Goodman, Andreas Burkert, Stella S. R. Offner, Rachel K. Friesen, Philip C. Myers, Felipe Alves, Hector G. Arce, Paola Caselli, Ana Chacon-Tanarro, Michael Chun-Yuan Chen, James Di Francesco, Adam Ginsburg, Jared Keown, Helen Kirk, Peter G. Martin, Christopher Matzner, Anna Punanova, Elena Redaelli, Erik Rosolowsky, Samantha Scibelli, Young Min Seo, Yancy Shirley, and Ayushi Singh. 2018. “Droplets I: Pressure-Dominated Sub-0.1 pc Coherent Structures in L1688 and B18.” arXiv e-prints, Pp. arXiv:1809.10223.
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, J. S. Urquhart, F. Bigiel, P. Hennebelle, N. Roy, and P. Schilke. 2018. “Histogram of oriented gradients: a technique for the study of molecular cloud formation.” arXiv e-prints, Pp. arXiv:1809.08338.
Catherine Zucker, Edward F. Schlafly, Joshua S. Speagle, Gregory M. Green, Stephen K. N. Portillo, Douglas P. Finkbeiner, and Alyssa A. Goodman. 2018. “Mapping Distances across the Perseus Molecular Cloud Using CO Observations, Stellar Photometry, and Gaia DR2 Parallax Measurements.” The Astrophysical Journal, 869, Pp. 83.
Ian W. Stephens, Michael M. Dunham, Philip C. Myers, Riwaj Pokhrel, Tyler L. Bourke, Eduard I. Vorobyov, John J. Tobin, Sarah I. Sadavoy, Jaime E. Pineda, Stella S. R. Offner, Katherine I. Lee, Lars E. Kristensen, Jes K. Jørgensen, Alyssa A. Goodman, Héctor G. Arce, and Mark Gurwell. 2018. “Mass Assembly of Stellar Systems and Their Evolution with the SMA (MASSES)—1.3 mm Subcompact Data Release.” The Astrophysical Journal Supplement Series, 237, Pp. 22.
Gabrielle Allen, Warren Anderson, Erik Blaufuss, Joshua S. Bloom, Patrick Brady, Sarah Burke-Spolaor, S. Bradley Cenko, Andrew Connolly, Peter Couvares, Derek Fox, Avishay Gal-Yam, Suvi Gezari, Alyssa Goodman, Darren Grant, Paul Groot, James Guillochon, Chad Hanna, David W. Hogg, Kelly Holley-Bockelmann, D. Andrew Howell, David Kaplan, Erik Katsavounidis, Marek Kowalski, Luis Lehner, Daniel Muthukrishna, Gautham Narayan, J. E. G. Peek, Abhijit Saha, Peter Shawhan, and Ignacio Taboada. 2018. “Multi-Messenger Astrophysics: Harnessing the Data Revolution.” arXiv e-prints, Pp. arXiv:1807.04780.
Alyssa A. Goodman, Michelle A. Borkin, and Thomas P. Robitaille. 2018. “New Thinking on, and with, Data Visualization.” arXiv e-prints, Pp. arXiv:1805.11300.
Catherine Zucker, Cara Battersby, and Alyssa Goodman. 2018. “Physical Properties of Large-scale Galactic Filaments.” The Astrophysical Journal, 864, Pp. 153.