Searching for codes credited to 'Schruba, Andreas'
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[ascl:2105.020]
PAP: PHANGS-ALMA pipeline
Leroy, Adam K.;
Hughes, Annie;
Liu, Daizhong;
Pety, Jerome;
Rosolowsky, Erik;
Saito, Toshiki;
Schinnerer, Eva;
Schruba, Andreas;
Usero, Antonio;
Faesi, Christopher M.;
Herrera, Cinthya N.;
Chevance, Melanie;
Hygate, Alexander P. S.;
Kepley, Amanda A.;
Koch, Eric W.;
Querejeta, Miguel;
Sliwa, Kazimierz;
Will, David;
Wilson, Christine D.;
Anand, Gagandeep S. Barnes, Ashley;
Belfiore, Francesco;
Beslic, Ivana;
Bigiel, Frank;
Blanc, Guillermo A.;
Bolatto, Alberto D.;
Boquien, Mederic;
Cao, Yixian;
Chandar, Rupali;
Chastenet, Jeremy;
Chiang, I-Da;
Congiu, Enrico;
Dale, Daniel A.;
Deger, Sinan;
den Brok, Jakob S.;
Eibensteiner, Cosima;
Emsellem, Eric;
Garcıa-Rodrıguez, Axel;
Glover, Simon C. O.;
Grasha, Kathryn;
Groves, Brent;
Henshaw, Jonathan D.;
Jimenez Donaire, Maria J.;
Kim, Jenny J.;
Klessen, Ralf S.;
Kreckel, Kathryn;
Kruijssen, J. M. Diederik;
Larson, Kirsten L.;
Lee, Janice C.;
Mayker, Ness;
McElroy, Rebecca;
Meidt, Sharon E.;
Mok, Angus;
Pan, Hsi-An;
Puschnig, Johannes;
Razza, Alessandro;
Sanchez-Blazquez, Patricia;
Sandstrom, Karin M.;
Santoro, Francesco;
Sardone, Amy;
Scheuermann, Fabian;
Sun, Jiayi;
Thilker, David A.;
Turner, Jordan A.;
Ubeda, Leonardo;
Utomo, Dyas;
Watkins, Elizabeth J.;
Williams, Thomas G.
The PHANGS-ALMA pipeline process data from radio interferometer observations. It uses CASA (ascl:1107.013), AstroPy (ascl:1304.002), and other affiliated packages to process data from calibrated visibilities to science-ready spectral cubes and maps. The PHANGS-ALMA pipeline offers a flexible alternative to the scriptForImaging script distributed by ALMA. The pipeline runs in two separate software environments: CASA 5.6 or 5.7 (staging, imaging and post-processing) and Python 3.6 or later (derived products) with modern versions of several packages.
[ascl:2211.014]
PDFchem: Average abundance of species from Av-PDFs
PDFchem models the cold ISM at moderate and large scales using functions connecting the quantities of the local and the observed visual extinctions and the local number density with probability density functions. For any given observed visual extinction sampled with thousands of clouds, the algorithm instantly computes the average abundances of the most important species and performs radiative transfer calculations to estimate the average emission of the most commonly observed lines.