PHANGS-ALMA Data Processing and Pipeline
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 J=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 VLA 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.
Cite
@article{arxiv.2104.07665,
title = {PHANGS-ALMA Data Processing and Pipeline},
author = {Adam K. Leroy and Annie Hughes and Daizhong Liu and Jerome Pety and Erik Rosolowsky and Toshiki Saito and Eva Schinnerer and Andreas Schruba and Antonio Usero and Christopher M. Faesi and Cinthya N. Herrera and Melanie Chevance and Alexander P. S. Hygate and Amanda A. Kepley and Eric W. Koch and Miguel Querejeta and Kazimierz Sliwa and David Will and Christine D. Wilson and Gagandeep S. Anand and Ashley Barnes and Francesco Belfiore and Ivana Beslic and Frank Bigiel and Guillermo A. Blanc and Alberto D. Bolatto and Mederic Boquien and Yixian Cao and Rupali Chandar and Jeremy Chastenet and I-Da Chiang and Enrico Congiu and Daniel A. Dale and Sinan Deger and Jakob S. den Brok and Cosima Eibensteiner and Eric Emsellem and Axel Garcıa-Rodrıguez and Simon C. O. Glover and Kathryn Grasha and Brent Groves and Jonathan D. Henshaw and Maria J. Jimenez Donaire and Jenny J. Kim and Ralf S. Klessen and Kathryn Kreckel and J. M. Diederik Kruijssen and Kirsten L. Larson and Janice C. Lee and Ness Mayker and Rebecca McElroy and Sharon E. Meidt and Angus Mok and Hsi-An Pan and Johannes Puschnig and Alessandro Razza and Patricia Sanchez-Blazquez and Karin M. Sandstrom and Francesco Santoro and Amy Sardone and Fabian Scheuermann and Jiayi Sun and David A. Thilker and Jordan A. Turner and Leonardo Ubeda and Dyas Utomo and Elizabeth J. Watkins and Thomas G. Williams},
journal= {arXiv preprint arXiv:2104.07665},
year = {2021}
}
Comments
Accepted for publication in the Astrophysical Journal Supplement series. 65 pages, 33 figures. Software available at https://github.com/akleroy/phangs_imaging_scripts . For a full resolution version see https://sites.google.com/view/phangs/publications