SYMBA: An end-to-end VLBI synthetic data generation pipeline Simulating Event Horizon Telescope observations of M 87
Roelofs, F.1; Janssen, M.1; Natarajan, I2; Deane, R.2,3; Davelaar, J.1; Olivares, H.1; Porth, O.4,5; Paine, S. N.6; Bouman, K. L.6,7,8; Tilanus, R. P. J.1,9,10; van Bemmel, I. M.11; Falcke, H.1; Akiyama, K.7,12,13,14; Alberdi, A.15; Alef, W.16; Asada, K.17; Azulay, R.16,18,19; Baczko, A.16; Ball, D.20,21; Balokovic, M.6,7; Barrett, J.13; Bintley, D.22; Blackburn, L.6,7; Boland, W.23; Bower, G. C.24; Bremer, M.25; Brinkerink, C. D.1; Brissenden, R.6,7; Britzen, S.16; Broderick, A. E.26,27,28; Broguiere, D.25; Bronzwaer, T.1; Byun, D.29,30; Carlstrom, J. E.31,32,33,34; Chael, A.35; Chan, C.20,21,36; Chatterjee, S.37; Chatterjee, K.5; Chen, M.24; Chen, Y.38,39; Cho, I29,30; Christian, P.6,20,21; Conway, J. E.40; Cordes, J. M.37; Crew, G. B.13; Cui, Y.41,42; De Laurentis, M.4,43,44; Dempsey, J.22; Desvignes, G.16,80; Dexter, J.45; Doeleman, S. S.6,7; Eatough, R. P.16; Fish, V. L.13; Fomalont, E.12; Fraga-Encinas, R.1; Friberg, P.22; Fromm, C. M.4; Gomez, J. L.15; Galison, P.7,45,46; Gammie, C. F.47,48; Garcia, R.25; Gentaz, O.25; Georgiev, B.27,28; Goddi, C.1,9; Gold, R.4,26,99; Gu, M.38,49; Gurwell, M.6; Hada, K.41,42; Hecht, M. H.13; Hesper, R.50; Ho, L. C.51,52; Ho, P.17; Honma, M.41,42; Huang, C. L.17; Huang, L.38,49; Hughes, D. H.53; Ikeda, S.14,54,55,56; Inoue, M.17; Issaoun, S.1; James, D. J.6,7; Jannuzi, B. T.20,21; Jeter, B.27,28; Jiang, W.38; Johnson, M. D.6,7; Jorstad, S.57,58; Jung, T.29,30; Karami, M.26,27; Karuppusamy, R.16; Kawashima, T.14; Keating, G. K.6; Kettenis, M.11; Kim, J.8,16,29; Kino, M.14,59; Koay, J. Y.17; Koch, P. M.17; Koyama, S.17; Kramer, M.16; Kramer, C.25; Krichbaum, T. P.16; Kuo, C.60; Lauer, T. R.61; Lee, S.29; Li, Y.62; Li, Z.63,64; Lindqvist, M.40; Lico, R.16; Liu, K.16; Liuzzo, E.65; Lo, W.17,66; Lobanov, A. P.16; Loinard, L.67,68; Lonsdale, C.13; Lu, R.16,38,39; MacDonald, N. R.16; Mao, J.69,70,71; Markoff, S.5,72; Marrone, D. P.20,21; Marscher, A. P.57; Marti-Vidal, I18; Matsushita, S.17; Matthews, L. D.13; Medeiros, L.20,21,100; Menten, K. M.16; Mizuno, Y.4; Mizuno, I22; Moran, J. M.6,7; Moriyama, K.13,41; Moscibrodzka, M.1; Mueller, C.1,16; Nagai, H.14,42; Nagar, N. M.73; Nakamura, M.17; Narayan, R.6,7; Narayanan, G.74; Neri, R.25; Ni, C.27,28; Noutsos, A.16; Okino, H.41,75; Ortiz-Leon, G. N.16; Oyama, T.41; Ozel, F.20,21; Palumbo, D. C. M.6,7; Patel, N.6; Pen, U.26,76,77,78; Pesce, D. W.6,7; Pietu, V25; Plambeck, R.79; PopStefanija, A.74; Prather, B.47; Preciado-Lopez, J. A.26; Psaltis, D.20,21; Pu, H.26; Ramakrishnan, V73; Rao, R.24; Rawlings, M. G.22; Raymond, A. W.6,7; Rezzolla, L.4; Ripperda, B.80,81; Rogers, A.13; Ros, E.16; Rose, M.20,21; Roshanineshat, A.20,21; Rottmann, H.16; Roy, A. L.16; Ruszczyk, C.13; Ryan, B. R.82,83; Rygl, K. L. J.65; Sanchez, S.84; Sanchez-Arguelles, D.54,85; Sasada, M.41,86; Savolainen, T.16,87,88; Schloerb, F. P.74; Schuster, K.25; Shao, L.16,52; Shen, Z.38,39; Small, D.11; Sohn, B. Won29,30,89; SooHoo, J.13; Tazaki, F.41; Tiede, P.27,28; Titus, M.13; Toma, K.90,91; Torne, P.16,84; Traianou, E.16; Trent, T.20,21; Trippe, S.92; Tsuda, S.41; van Langevelde, H. J.11,93; van Rossum, D. R.1; Wagner, J.16; Wardle, J.94; Weintroub, J.6,7; Wex, N.16; Wharton, R.16; Wielgus, M.6,7; Wong, G. N.47,82; Wu, Q.95; Young, A.1; Young, K.6; Younsi, Z.4,96; Yuan, F.38,49,97; Yuan, Y.98; Zensus, J. A.16; Zhao, G.29; Zhao, S.1,63; Zhu, Z.46

Context. Realistic synthetic observations of theoretical source models are essential for our understanding of real observational data. In using synthetic data, one can verify the extent to which source parameters can be recovered and evaluate how various data corruption effects can be calibrated. These studies are the most important when proposing observations of new sources, in the characterization of the capabilities of new or upgraded instruments, and when verifying model-based theoretical predictions in a direct comparison with observational data. Aims. We present the SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations. SYMBA takes into account several realistic atmospheric, instrumental, and calibration effects. Methods. We used SYMBA to create synthetic observations for the Event Horizon Telescope (EHT), a millimetre VLBI array, which has recently captured the first image of a black hole shadow. After testing SYMBA with simple source and corruption models, we study the importance of including all corruption and calibration effects, compared to the addition of thermal noise only. Using synthetic data based on two example general relativistic magnetohydrodynamics (GRMHD) model images of M 87, we performed case studies to assess the image quality that can be obtained with the current and future EHT array for different weather conditions. Results. Our synthetic observations show that the effects of atmospheric and instrumental corruptions on the measured visibilities are significant. Despite these effects, we demonstrate how the overall structure of our GRMHD source models can be recovered robustly with the EHT2017 array after performing calibration steps, which include fringe fitting, a priori amplitude and network calibration, and self-calibration. With the planned addition of new stations to the EHT array in the coming years, images could be reconstructed with higher angular resolution and dynamic range. In our case study, these improvements allowed for a distinction between a thermal and a non-thermal GRMHD model based on salient features in reconstructed images.

Keywordgalaxies nuclei black hole physics telescopes atmospheric effects techniques high angular resolution techniques interferometric
Indexed BySCI
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000524552600002
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Document Type期刊论文
Corresponding AuthorRoelofs, F.
Affiliation1.Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands
2.Rhodes Univ, Ctr Radio Astron Tech & Technol, Dept Phys & Elect, ZA-6140 Grahamstown, South Africa
3.Univ Pretoria, Dept Phys, Lynnwood Rd, ZA-0083 Pretoria, South Africa
4.Goethe Univ Frankfurt, Inst Theoret Phys, Max Von Laue Str 1, D-60438 Frankfurt, Germany
5.Univ Amsterdam, Anton Pannekoek Inst Astron, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands
6.Harvard Smithsonian Ctr Astrophys, 60 Garden St, Cambridge, MA 02138 USA
7.Harvard Univ, Black Hole Initiat, 20 Garden St, Cambridge, MA 02138 USA
8.CALTECH, 1200 East Calif Blvd, Pasadena, CA 91125 USA
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10.Netherlands Org Sci Res NWO, Postbus 93138, NL-2509 AC The Hague, Netherlands
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13.MIT, Haystack Observ, 99 Millstone Rd, Westford, MA 01886 USA
14.Natl Astron Observ Japan, 2-21-1 Osawa, Mitaka, Tokyo 1818588, Japan
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21.Univ Arizona, Dept Astron, 933 N Cherry Ave, Tucson, AZ 85721 USA
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31.Univ Chicago, Kavli Inst Cosmol Phys, 5640 South Ellis Ave, Chicago, IL 60637 USA
32.Univ Chicago, Dept Astron & Astrophys, 5640 South Ellis Ave, Chicago, IL 60637 USA
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74.Univ Massachusetts, Dept Astron, Amherst, MA 01003 USA
75.Univ Tokyo, Grad Sch Sci, Dept Astron, Bunkyo Ku, 7-3-1 Hongo, Tokyo 1130033, Japan
76.Univ Toronto, Canadian Inst Theoret Astrophys, 60 St George St, Toronto, ON M5S 3H8, Canada
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Recommended Citation
GB/T 7714
Roelofs, F.,Janssen, M.,Natarajan, I,et al. SYMBA: An end-to-end VLBI synthetic data generation pipeline Simulating Event Horizon Telescope observations of M 87[J]. ASTRONOMY & ASTROPHYSICS,2020,636(0):19.
APA Roelofs, F..,Janssen, M..,Natarajan, I.,Deane, R..,Davelaar, J..,...&Zhu, Z..(2020).SYMBA: An end-to-end VLBI synthetic data generation pipeline Simulating Event Horizon Telescope observations of M 87.ASTRONOMY & ASTROPHYSICS,636(0),19.
MLA Roelofs, F.,et al."SYMBA: An end-to-end VLBI synthetic data generation pipeline Simulating Event Horizon Telescope observations of M 87".ASTRONOMY & ASTROPHYSICS 636.0(2020):19.
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