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You Only Stack Once: A Motion-filtered, Deep Learning Framework for Detecting Faint Moving Sources

  • Authors: Nitya Pandey, César Fuentes, Pedro Bernardinelli, Valeria Frías, Colin Orion Chandler, David E. Trilling, Matthew J. Holman, Steven Stetzler, Dallin Spencer, Hsing Wen Lin, 省文 林, Luis E. Salazar Manzano, Darin Ragozzine, Ryder Strauss, Mario Juric, Andrew J. Connolly, Hayden Smotherman, Scott S. Sheppard, Kevin Napier

Nitya Pandey et al 2026 The Astronomical Journal 172 .

  • Provider: AAS Journals

Caption: Figure 7.

Detection efficiency as a function of magnitude difference relative to the DEEP survey limit for each analyzed FN. Colored curves show the recovery efficiency obtained with our method, while the shaded regions indicate the associated uncertainties. The black vertical line at Δm = 0 marks the nominal DEEP detection limit reported by K. J. Napier et al. (2024). The horizontal dashed line denotes the 25% recovery efficiency threshold. Offsets to the left of the vertical line correspond to brighter sources, and the displacement of each curve relative to this reference illustrates how much shallower each FN is compared to the DEEP survey.

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