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Skynet Algorithm for Single-dish Radio Mapping. I. Contaminant-cleaning, Mapping, and Photometering Small-scale Structures

  • Authors: J. R. Martin, D. E. Reichart, D. A. Dutton, M. P. Maples, T. A. Berger, F. D. Ghigo, J. B. Haislip, O. H. Shaban, A. S. Trotter, L. M. Barnes, M. L. Paggen, R. L. Gao, C. P. Salemi, G. I. Langston, S. Bussa, J. A. Duncan, S. White, S. A. Heatherly, J. B. Karlik, E. M. Johnson, J. E. Reichart, A. C. Foster, V. V. Kouprianov, S. Mazlin, and J. Harvey

2019 The Astrophysical Journal Supplement Series 240 12.

  • Provider: AAS Journals

Caption: Figure 39.

Top left: background-subtracted mapping of, from right to left, 3C 84, NRAO 1560/1650, 3C 111, 3C 123, 3C 139.1, and 3C 147, as well as fainter sources, acquired with the 40 ft in the L-band using a maximum slew speed nodding pattern. The data are heavily contaminated by linearly polarized, broadband RFI, affecting only one of the receiver’s two polarization channels. Top right: data from the top-left panel time-delay corrected and RFI-subtracted, with a 0.7 beamwidth scale (Table 2). Bottom left: identically processed data from the receiver’s other, relatively uncontaminated polarization channel for comparison. The RFI-subtraction algorithm is not perfect, but performs very well given the original, extreme level of contamination. Bottom right: background-subtracted and time-delay-corrected data from both, equally calibrated polarization channels first appended and then jointly RFI-subtracted. Locally modeled surfaces have been applied for visualization (Section 1.2.1; see Section 3.7).

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