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GRANDWin: Gain-based Radio-frequency Interference Analysis Using Normalized Deviation with Winsorization for MWA Ultralow-frequency Calibration Data

  • Authors: Wildan Hidayat, Shintaro Yoshiura, Keitaro Takahashi, Cathryn M. Trott, D. Null, C. D. Nunhokee

Wildan Hidayat et al 2026 The Astrophysical Journal 1006 .

  • Provider: AAS Journals

Caption: Figure 7.

Dirty image comparison for observation ID 1098294120: panel (a) shows the dirty image using AOFlagger flags. Panel (b) highlights additional outliers detected by the winsorizing method within 97.92–99.20 MHz. Panel (c) displays the updated dirty image after adding GRANDWin flags, showing reduced contamination. Panel (d) shows the difference image between (a) and (c), illustrating the improvements achieved by combining both flagging methods.

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