Jorma Harju, Jaime E. Pineda, Anton I. Vasyunin, Paola Caselli, Stella S. R. Offner, and Alyssa A. Goodman. 2020. “Efficient Methanol Production on the Dark Side of a Prestellar Core.” The Astrophysical Journal, 895, Pp. 101.Abstract
We present Atacama Large Millimeter/submillimeter Array maps of the starless molecular cloud core Ophiuchus/H-MM1 in the lines of deuterated ammonia (ortho-${\mathrm{NH}}_{2}{\rm{D}}$), methanol (${\mathrm{CH}}_{3}\mathrm{OH}$), and sulfur monoxide (SO). The dense core is seen in ${\mathrm{NH}}_{2}{\rm{D}}$ emission, whereas the ${\mathrm{CH}}_{3}\mathrm{OH}$ 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 sulfur 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 sulfur are released as a result of grain–grain collisions induced by shear vorticity.
Hope How-Huan Chen, Stella S. R. Offner, Jaime E. Pineda, Alyssa A. Goodman, Andreas Burkert, Adam Ginsburg, and Spandan Choudhury. 2020. “Core Formation, Coherence and Collapse: A New Core Evolution Paradigm Revealed by Machine Learning.” arXiv, 2006, Pp. 07325.Abstract
We study the formation, evolution and collapse of dense cores by tracking density structures in a magnetohydrodynamic (MHD) simulation. We identify cores using the dendrogram algorithm and utilize machine learning techniques, including principal component analysis (PCA) and the k-means clustering algorithm to analyze the full density and velocity dispersion profiles of these cores. We find that there exists an evolutionary sequence consisting of three distinct phases: i) the formation of turbulent density structures (Phase I), ii) the dissipation of turbulence and the formation of coherent cores (Phase II), and iii) the transition to protostellar cores through gravitational collapse (Phase III). In dynamically evolving molecular clouds, the existence of these three phases corresponds to the coexistence of three populations of cores with distinct physical properties. The prestellar and protostellar cores frequently analyzed in previous studies of observations and simulations belong to the last phase in this evolutionary picture. We derive typical lifetimes of 1.4±1.0×105 yr, 3.3±1.4×105 yr and 3.3±1.4×105 yr, respectively for Phase I, II and III. We find that cores can form from both converging flows and filament fragmentation and that cores may form both inside and outside the filaments. We then compare our results to previous observations of coherent cores and provide suggestions for future observations to study cores belonging to the three phases.
Spandan Choudhury, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Stella S. R. Offner, Erik Rosolowsky, Rachel K. Friesen, Felipe O. Alves, Ana Chacón-Tanarro, Anna Punanova, Elena Redaelli, Philip Helen Kirk, C. Myers, Peter G. Martin, Yancy Shirley, Michael Chun-Yuan Chen, Alyssa A. Goodman, and James Di Francesco. 2020. “Ubiquitous NH\(_{3}\) supersonic component in L1688 coherent cores.” A&A, 640, Pp. L6. Publisher's VersionAbstract

Context. Star formation takes place in cold dense cores in molecular clouds. Earlier observations have found that dense cores exhibit subsonic non-thermal velocity dispersions. In contrast, CO observations show that the ambient large-scale cloud is warmer and has supersonic velocity dispersions.

Aims. We aim to study the ammonia (NH3) molecular line profiles with exquisite sensitivity towards the coherent cores in L1688 in order to study their kinematical properties in unprecedented detail.

Methods. We used NH3 (1,1) and (2,2) data from the first data release (DR1) in the Green Bank Ammonia Survey (GAS). We first smoothed the data to a larger beam of 1′ to obtain substantially more extended maps of velocity dispersion and kinetic temperature, compared to the DR1 maps. We then identified the coherent cores in the cloud and analysed the averaged line profiles towards the cores.

Results. For the first time, we detected a faint (mean NH3(1,1) peak brightness < 0.25 K in TMB), supersonic component towards all the coherent cores in L1688. We fitted two components, one broad and one narrow, and derived the kinetic temperature and velocity dispersion of each component. The broad components towards all cores have supersonic linewidths (ℳS ≥ 1). This component biases the estimate of the narrow dense core component’s velocity dispersion by ≈28% and the kinetic temperature by ≈10%, on average, as compared to the results from single-component fits.

Conclusions. Neglecting this ubiquitous presence of a broad component towards all coherent cores causes the typical single-component fit to overestimate the temperature and velocity dispersion. This affects the derived detailed physical structure and stability of the cores estimated from NH3 observations.

T. K. Sridharan, Shmuel Bialy, Raymond Blundell, Andrew Burkhardt, Thomas Dame, Sheperd Doeleman, Douglas Finkbeiner, Alyssa Goodman, and alia. 2020. “A Prospective ISRO-CfA Himalayan Sub-millimeter-wave Observatory Initiative.” arXiv, 2008, 07453. Publisher's VersionAbstract
The Smithsonian Astrophysical Observatory (SAO), a member of the Center for Astrophysics | Harvard and Smithsonian, is in discussions with the Space Applications Centre (SAC) of the Indian Space Research Organization (ISRO) and its partners in the newly formed Indian Sub-millimetre-wave Astronomy Alliance (ISAA), to collaborate in the construction of a sub-millimeter-wave astronomy observatory in the high altitude deserts of the Himalayas, initially at the 4500 m Indian Astronomical Observatory, Hanle. Two primary science goals are targeted. One is the mapping of the distribution of neutral atomic carbon, and the carbon monoxide (CO) molecule in higher energy states, in large parts of the Milky Way, and in selected external galaxies. Such studies would advance our understanding of molecular hydrogen present in the interstellar medium, but partly missed by existing observations; and characterize Galaxy-wide molecular cloud excitation conditions, through multi-level CO observations. Stars form in interstellar clouds of molecular gas and dust, and these observations would allow research into the formation and destruction processes of such molecular clouds and the life cycle of galaxies. As the second goal, the observatory would add a new location to the global Event Horizon Telescope (EHT) network, which lacks a station in the Himalayan longitudes. This addition would enhance the quality of the images synthesized by the EHT, support observations in higher sub-millimeter wave bands, sharpening its resolving ability, improve its dynamic imaging capability and add weather resilience to observing campaigns. In the broader context, this collaboration can be a starting point for a wider, mutually beneficial scientific exchange between the Indian and US astronomy communities, including a potential future EHT space component.
Kaustav K. Das, Catherine Zucker, Joshua S. Speagle, Alyssa Goodman, Gregory M. Green, and João Alves. 2020. “Constraining the distance to the North Polar Spur with Gaia DR2.” MNRAS, 498, Pp. 5863-5872.Abstract
The North Polar Spur (NPS) is one of the largest structures observed in the Milky Way in both the radio and soft X-rays. While several predictions have been made regarding the origin of the NPS, modelling the structure is difficult without precise distance constraints. In this paper, we determine accurate distances to the southern terminus of the NPS and towards latitudes ranging up to 55°. First, we fit for the distance and extinction to stars towards the NPS using optical and near-infrared photometry and Gaia Data Release 2 astrometry. We model these per-star distance–extinction estimates as being caused by dust screens at unknown distances, which we fit for using a nested sampling algorithm. We then compare the extinction to the Spur derived from our 3D dust modelling with integrated independent measures from XMM–Newton X-ray absorption and H I column density measures. We find that we can account for nearly 100 per cent of the total column density of the NPS as lying within 140 pc for latitudes >26° and within 700 pc for latitudes <11°. Based on the results, we conclude that the NPS is not associated with the Galactic Centre or the Fermi bubbles. Instead, it is likely associated, especially at higher latitudes, with the Scorpius–Centaurus association.
Milky Way

Astronomy Magazine Talks to the Team Who Discovered the Radcliffe Wave

December 1, 2020

Astronomy Magazine talks to the team from Harvard’s Radcliffe Institute for Advanced Study and Harvard-Smithsonian Center for Astrophysics (CfA) about their serendipitous discovery of the Radcliffe Wave, a massive interconnected stream of stellar nurseries, molecular clouds, and supernovae that snakes through the Milky Way galaxy - and how history, art and science came together to enable this paradigm-changing discovery.  Read the full article ...

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glue-ing Together the Universe, at Microsoft New England Research Division, Cambridge, MA , Friday, March 6, 2020:

Astronomers have a long history of visualization. Going back only as far as Galileo, discoveries were made using sketches of celestial objects moving over time. Today, Astronomy inquiries can, and often do, make use of petabytes of data at once. Huge surveys are analyzed statistically to understand tiny fluctuations that hint at the fundamental nature of the Universe, and myriad data sets, from telescopes across the globe and in space are brought together to solve problems ranging from the nature of black holes to the structure of the Milky Way to the origins of planets like Earth. In...

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Pecan Pie Logo for "PRISEd Conversation 2020" with photo of Dr. Goodman

Blog Feature: Dr. Alyssa Goodman talks with the The Harvard College Program in Science and Engineering (PRISE)

September 23, 2020

Dr. Alyssa Goodman talks with Felicia Ho, PRISE, Harvard College '23 about Jacques Cousteau, data visualization, climate change, prediction science, and the wide arc of influences that have shaped her multifaceted career as the Robert Wheeler Wilson Professor of Applied Astronomy at Harvard. 


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Catherine Zucker, Joshua S. Speagle, Edward F. Schlafly, Gregory M. Green, Douglas P. Finkbeiner, Alyssa Goodman, and João Alves. 1/2020. “A Compendium of Distances to Molecular Clouds in the Star Formation Handbook.” Astronomy and Astrophysics, 633, Pp. A51.Abstract
Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method that combines stellar photometric data with Gaia DR2 parallax measurements in a Bayesian framework to infer the distances of nearby dust clouds to a typical accuracy of ∼5%. After refining the technique to target lower latitudes and incorporating deep optical data from DECam in the southern Galactic plane, we have derived a catalog of distances to molecular clouds in Reipurth (2008, Star Formation Handbook, Vols. I and II) which contains a large fraction of the molecular material in the solar neighborhood. Comparison with distances derived from maser parallax measurements towards the same clouds shows our method produces consistent distances with ≲10% scatter for clouds across our entire distance spectrum (150 pc-2.5 kpc). We hope this catalog of homogeneous distances will serve as a baseline for future work. Table A.1 is also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr ( or via http://cdsarc.u-strasbg.fr/viz- bin/cat/J/A+A/633/A51. It is also available on the Harvard Dataverse at http://https://doi.org/1 0.7910/DVN/07L7YZ An interactive 3D version of Fig. 2 is available at http://https://www.aanda.org