Orbiting Astronomical Satellite for Investigating Stellar Systems (OASIS): following the water trail from the interstellar medium to oceans

Proceedings of SPIE--the International Society for Optical Engineering SPIE, the international society for optics and photonics 11820 (2021) 118200o-118200o-52

Authors:

Christopher K Walker, Gordon Chin, Susanne Aalto, Carrie M Anderson, Jonathan W Arenberg, Cara Battersby, Edwin Bergin, Jenny Bergner, Nicolas Biver, Gordon L Bjoraker, John Carr, Thibault Cavalié, Elvire De Beck, Michael A DiSanti, Paul Hartogh, Leslie K Hunt, Daewook Kim, Yuzuru Takashima, Craig Kulesa, David Leisawitz, Joan Najita, Dimitra Rigopoulou, Kamber Schwarz, Yancy Shirly, Antony A Stark, Xander Tielens, Serena Viti, David Wilner, Edward Wollack, Erick Young

Galaxy Zoo DECaLS: detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies

Monthly Notices of the Royal Astronomical Society Oxford University Press 509:3 (2021) 3966-3988

Authors:

Mike Walmsley, Chris Lintott, Tobias Géron, Sandor Kruk, Coleman Krawczyk, Kyle W Willett, Steven Bamford, Lee S Kelvin, Lucy Fortson, Yarin Gal, William Keel, Karen L Masters, Vihang Mehta, Brooke D Simmons, Rebecca Smethurst, Lewis Smith, Elisabeth M Baeten, Christine Macmillan

Abstract:

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r = 23.6 versus r = 22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314 000 galaxies. 140 000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314 000 galaxies. We use active learning to focus our volunteer effort on the galaxies which, if labelled, would be most informative for training our ensemble. When measured against confident volunteer classifications, the trained networks are approximately 99 per cent accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.

Dense molecular gas properties on 100 pc scales across the disc of NGC 3627

Monthly Notices of the Royal Astronomical Society 506:1 (2021) 963-988

Authors:

I Bešlić, AT Barnes, F Bigiel, J Puschnig, J Pety, C Herrera Contreras, AK Leroy, A Usero, E Schinnerer, SE Meidt, E Emsellem, A Hughes, C Faesi, K Kreckel, FMC Belfiore, M Chevance, JS Den Brok, C Eibensteiner, SCO Glover, K Grasha, MJ Jimenez-Donaire, RS Klessen, JMD Kruijssen, D Liu, I Pessa, M Querejeta, E Rosolowsky, T Saito, F Santoro, A Schruba, MC Sormani, TG Williams

Abstract:

It is still poorly constrained how the densest phase of the interstellar medium varies across galactic environment. A large observing time is required to recover significant emission from dense molecular gas at high spatial resolution, and to cover a large dynamic range of extragalactic disc environments. We present new NOrthern Extended Millimeter Array (NOEMA) observations of a range of high critical density molecular tracers (HCN, HNC, HCO+) and CO isotopologues (13CO, C18O) towards the nearby (11.3 Mpc) strongly barred galaxy NGC 3627. These observations represent the current highest angular resolution (1.85 arcsec; 100 pc) map of dense gas tracers across a disc of a nearby spiral galaxy, which we use here to assess the properties of the dense molecular gas, and their variation as a function of galactocentric radius, molecular gas, and star formation. We find that the HCN(1-0)/CO(2-1) integrated intensity ratio does not correlate with the amount of recent star formation. Instead, the HCN(1-0)/CO(2-1) ratio depends on the galactic environment, with differences between the galaxy centre, bar, and bar-end regions. The dense gas in the central 600 pc appears to produce stars less efficiently despite containing a higher fraction of dense molecular gas than the bar ends where the star formation is enhanced. In assessing the dynamics of the dense gas, we find the HCN(1-0) and HCO+(1-0) emission lines showing multiple components towards regions in the bar ends that correspond to previously identified features in CO emission. These features are cospatial with peaks of Hα emission, which highlights that the complex dynamics of this bar-end region could be linked to local enhancements in the star formation.

Resolved Neutral Outflow from a Lensed Dusty Star-forming Galaxy at z = 2.09

The Astrophysical Journal American Astronomical Society 919:1 (2021) 5

Authors:

Kirsty M Butler, Paul P van der Werf, Matus Rybak, Tiago Costa, Pierre Cox, Axel Weiß, Michał J Michałowski, Dominik A Riechers, Dimitra Rigopoulou, Lucia Marchetti, Stephen Eales, Ivan Valtchanov

The ALPINE-ALMA [CII] survey

Astronomy & Astrophysics EDP Sciences 653 (2021) a84

Authors:

F Pozzi, F Calura, Y Fudamoto, M Dessauges-Zavadsky, C Gruppioni, M Talia, G Zamorani, M Bethermin, A Cimatti, A Enia, Y Khusanova, R Decarli, O Le Fèvre, P Capak, P Cassata, AL Faisst, L Yan, D Schaerer, J Silverman, S Bardelli, M Boquien, A Enia, D Narayanan, M Ginolfi, NP Hathi, GC Jones, AM Koekemoer, BC Lemaux, F Loiacono, R Maiolino, DA Riechers, G Rodighiero, M Romano, L Vallini, D Vergani, E Zucca