PHANGS-ALMA Data Processing and Pipeline

Adam K. Leroy, Annie Hughes, Daizhong Liu, Jérôme Pety, Erik Rosolowsky, Toshiki Saito, Eva Schinnerer, Andreas Schruba, Antonio Usero, Christopher M. Faesi, Cinthya N. Herrera, Mélanie Chevance, Alexander P.S. Hygate, Amanda A. Kepley, Eric W. Koch, Miguel Querejeta, Kazimierz Sliwa, David Will, Christine D. Wilson, Gagandeep S. AnandAshley Barnes, Francesco Belfiore, Ivana Bešlić, Frank Bigiel, Guillermo A. Blanc, Alberto D. Bolatto, Mèdèric Boquien, Yixian Cao, Rupali Chandar, Jérémy Chastenet, I. Da Chiang, Enrico Congiu, Daniel A. Dale, Sinan Deger, Jakob S. Den Brok, Cosima Eibensteiner, Eric Emsellem, Axel García-Rodríguez, Simon C.O. Glover, Kathryn Grasha, Brent Groves, Jonathan D. Henshaw, María J. Jiménez Donaire, Jaeyeon Kim, Ralf S. Klessen, Kathryn Kreckel, J. M.Diederik Kruijssen, Kirsten L. Larson, Janice C. Lee, Ness Mayker, Rebecca McElroy, Sharon E. Meidt, Angus Mok, Hsi An Pan, Johannes Puschnig, Alessandro Razza, Patricia Sánchez-Bl'Azquez, Karin M. Sandstrom, Francesco Santoro, Amy Sardone, Fabian Scheuermann, Jiayi Sun, David A. Thilker, Jordan A. Turner, Leonardo Ubeda, Dyas Utomo, Elizabeth J. Watkins, Thomas G. Williams

Research output: Contribution to journalArticlepeer-review

106 Citations (Scopus)

Abstract

We describe the processing of the PHANGS-ALMA survey and present the PHANGS-ALMA pipeline, a public software package that processes calibrated interferometric and total power data into science-ready data products. PHANGS-ALMA is a large, high-resolution survey of CO(2-1) emission from nearby galaxies. The observations combine ALMA's main 12 m array, the 7 m array, and total power observations, and use mosaics of dozens to hundreds of individual pointings. We describe the processing of the u-v data, imaging and deconvolution, linear mosaicking, combining interferometer and total power data, noise estimation, masking, data product creation, and quality assurance. Our pipeline has a general design and can also be applied to Very Large Array and ALMA observations of other spectral lines and continuum emission. We highlight our recipe for deconvolution of complex spectral line observations, which combines multiscale clean, single-scale clean, and automatic mask generation in a way that appears robust and effective. We also emphasize our two-track approach to masking and data product creation. We construct one set of "broadly masked"data products, which have high completeness but significant contamination by noise, and another set of "strictly masked"data products, which have high confidence but exclude faint, low signal-to-noise emission. Our quality assurance tests, supported by simulations, demonstrate that 12 m+7 m deconvolved data recover a total flux that is significantly closer to the total power flux than the 7 m deconvolved data alone. In the appendices, we measure the stability of the ALMA total power calibration in PHANGS-ALMA and test the performance of popular short-spacing correction algorithms.

Original languageEnglish
Article number19
JournalAstrophysical Journal, Supplement Series
Volume255
Issue number1
DOIs
Publication statusPublished - Jul 2021

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