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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 34.

Data from the top row of Figure 14, corresponding to 6 (left column), 12 (middle column), and 24 (right column) beamwidth background-subtraction scales, RFI-subtracted, with 0.95 (top row) and 0.5 (bottom row) beamwidth scales. RFI-subtracted data are biased neither high nor low. On the 0.95 beamwidth scale, the noise level of the RFI-subtracted data is ≈1.1% (left), ≈1.3% (middle), and ≈1.4% (right) of that of the background-subtracted data. On the smaller, 0.5 beamwidth scale, the noise level of the RFI-subtracted data is roughly twice that, ≈2.5% (left), ≈2.8% (middle), and ≈3.0% (right) of that of the background-subtracted data. Locally modeled surfaces (Section 1.2.1, see Section 3.7) have been applied for visualization only.

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