[ascl:1408.023]
WSClean: Widefield interferometric imager
Offringa, A. R.;
McKinley, B.;
Hurley-Walker, N.;
Briggs, F. H.;
Wayth, R. B.;
Kaplan, D. L.;
Bell, M. E.;
Feng, L.;
Neben, A. R.;
Hughes, J. D.;
Rhee, J.;
Murphy, T.;
Bhat, N. D. R.;
Bernardi, G.;
Bowman, J. D.;
Cappallo, R. J.;
Corey, B. E.;
Deshpande, A. A.;
Emrich, D.;
Ewall-Wice, A.;
Gaensler, B. M.;
Goeke, R.;
Greenhill, L. J.;
Hazelton, B. J.;
Hindson, L.;
Johnston-Hollitt, M.;
Jacobs, D. C.;
Kasper, J. C.;
Kratzenberg, E.;
Lenc, E.;
Lonsdale, C. J.;
Lynch, M. J.;
McWhirter, S. R.;
Mitchell, D. A.;
Morales, M. F.;
Morgan, E.;
Kudryavtseva, N.;
Oberoi, D.;
Ord, S. M.;
Pindor, B.;
Procopio, P.;
Prabu, T.;
Riding, J.;
Roshi, D. A.;
Shankar, N. Udaya;
Srivani, K. S.;
Subrahmanyan, R.;
Tingay, S. J.;
Waterson, M.;
Webster, R. L.;
Whitney, A. R.;
Williams, A.;
Williams, C. L.
WSClean (w-stacking clean) is a fast generic widefield imager. It uses the w-stacking algorithm and can make use of the w-snapshot algorithm. It supports full-sky imaging and proper beam correction for homogeneous dipole arrays such as the MWA. WSClean allows Hogbom and Cotton-Schwab cleaning, and can clean polarizations joinedly. All operations are performed on the CPU; it is not specialized for GPUs.
[ascl:1303.022]
ionFR: Ionospheric Faraday rotation
Sotomayor-Beltran, C.;
Sobey, C.;
Hessels, J. W. T.;
de Bruyn, G.;
Noutsos, A.;
Alexov, A.;
Anderson, J.;
Asgekar, A.;
Avruch, I. M.;
Beck, R.;
Bell, M. E.;
Bell, M. R.;
Bentum, M. J.;
Bernardi, G.;
Best, P.;
Birzan, L.;
Bonafede, A.;
Breitling, F.;
Broderick, J.;
Brouw, W. N.;
Brueggen, M.;
Ciardi, B.;
de Gasperin, F.;
Dettmar, R.-J.;
van Duin, A.;
Duscha, S.;
Eisloeffel, J.;
Falcke, H.;
Fallows, R. A.;
Fender, R.;
Ferrari, C.;
Frieswijk, W.;
Garrett, M. A.;
Griessmeier, J.;
Grit, T.;
Gunst, A. W.;
Hassall, T. E.;
Heald, G.;
Hoeft, M.;
Horneffer, A.;
Iacobelli, M.;
Juette, E.;
Karastergiou, A.;
Keane, E.;
Kohler, J.;
Kramer, M.;
Kondratiev, V. I.;
Koopmans, L. V. E.;
Kuniyoshi, M.;
Kuper, G.;
van Leeuwen, J.;
Maat, P.;
Macario, G.;
Markoff, S.;
McKean, J. P.;
Mulcahy, D. D.;
Munk, H.;
Orru, E.;
Paas, H.;
Pandey-Pommier, M.;
Pilia, M.;
Pizzo, R.;
Polatidis, A. G.;
Reich, W.;
Roettgering, H.;
Serylak, M.;
Sluman, J.;
Stappers, B. W.;
Tagger, M.;
Tang, Y.;
Tasse, C.;
ter Veen, S.;
Vermeulen, R.;
van Weeren, R. J.;
Wijers, R. A. M. J.;
Wijnholds, S. J.;
Wise, M. W.;
Wucknitz, O.;
Yatawatta, S.;
Zarka, P.
ionFR calculates the amount of ionospheric Faraday rotation for a specific epoch, geographic location, and line-of-sight. The code uses a number of publicly available, GPS-derived total electron content maps and the most recent release of the International Geomagnetic Reference Field. ionFR can be used for the calibration of radio polarimetric observations; its accuracy had been demonstrated using LOFAR pulsar observations.
[ascl:2312.030]
matvis: Fast matrix-based visibility simulator
Kittiwisit, Piyanat;
Murray, Steven G.;
Garsden, Hugh;
Bull, Philip;
Cain, Christopher;
Parsons, Aaron R.;
Sipple, Jackson;
Abdurashidova, Zara;
Adams, Tyrone;
Aguirre, James E.;
Alexander, Paul;
Ali, Zaki S.;
Baartman, Rushelle;
Balfour, Yanga;
Beardsley, Adam P.;
Berkhout, Lindsay M.;
Bernardi, Gianni;
Billings, Tashalee S.;
Bowman, Judd D.;
Bradley, Richard F.;
Burba, Jacob;
Carey, Steven;
Carilli, Chris L.;
Chen, Kai-Feng;
Cheng, Carina;
Choudhuri, Samir;
DeBoer, David R.;
de Lera Acedo, Eloy;
Dexter, Matt;
Dillon, Joshua S.;
Dynes, Scott;
Eksteen, Nico;
Ely, John;
Ewall-Wice, Aaron;
Fagnoni, Nicolas;
Fritz, Randall;
Furlanetto, Steven R.;
Gale-Sides, Kingsley;
Gehlot, Bharat Kumar;
Ghosh, Abhik;
Glendenning, Brian;
Gorce, Adelie;
Gorthi, Deepthi;
Greig, Bradley;
Grobbelaar, Jasper;
Halday, Ziyaad;
Hazelton, Bryna J.;
Hewitt, Jacqueline N.;
Hickish, Jack;
Huang, Tian;
Jacobs, Daniel C.;
Josaitis, Alec;
Julius, Austin;
Kariseb, MacCalvin;
Kern, Nicholas S.;
Kerrigan, Joshua;
Kim, Honggeun;
Kohn, Saul A.;
Kolopanis, Matthew;
Lanman, Adam;
La Plante, Paul;
Liu, Adrian;
Loots, Anita;
Ma, Yin-Zhe;
MacMahon, David H. E.;
Malan, Lourence;
Malgas, Cresshim;
Malgas, Keith;
Marero, Bradley;
Martinot, Zachary E.;
Mesinger, Andrei;
Molewa, Mathakane;
Morales, Miguel F.;
Mosiane, Tshegofalang;
Neben, Abraham R.;
Nikolic, Bojan;
Devi Nunhokee, Chuneeta;
Nuwegeld, Hans;
Pascua, Robert;
Patra, Nipanjana;
Pieterse, Samantha;
Qin, Yuxiang;
Rath, Eleanor;
Razavi-Ghods, Nima;
Riley, Daniel;
Robnett, James;
Rosie, Kathryn;
Santos, Mario G.;
Sims, Peter;
Singh, Saurabh;
Storer, Dara;
Swarts, Hilton;
Tan, Jianrong;
Thyagarajan, Nithyanandan;
van Wyngaarden, Pieter;
Williams, Peter K. G.;
Xu, Zhilei;
Zheng, Haoxuan
matvis simulates radio interferometric visibilities at the necessary scale with both CPU and GPU implementations. It is matrix-based and applicable to wide field-of-view instruments such as the Hydrogen Epoch of Reionization Array (HERA) and the Square Kilometre Array (SKA), as it does not make any approximations of the visibility integral (such as the flat-sky approximation). The only approximation made is that the sky is a collection of point sources, which is valid for sky models that intrinsically consist of point-sources, but is an approximation for diffuse sky models. The matvix matrix-based algorithm is fast and scales well to large numbers of antennas. The code supports both CPU and GPU implementations as drop-in replacements for each other and also supports both dense and sparse sky models.