Status: In Progress
Fix Version/s: None
Task: To develop a DMTN on LSST difference-image detection efficiencies and, in particular, assess the question of whether (and if so, when) fake injection should be used to calculate them. The roles of this document would be to (a) inform DM activities and perhaps also (b) educate the community on how to obtain/apply LSST detection efficiencies.
Status: A draft of this DMTN is currently in progress here. This document includes the following sections, and currently only addresses "(a) inform DM activities" and does not yet serve to "(b) educate the community on how to obtain/apply LSST detection efficiencies".
(1) An introduction to detection efficiencies (the probability that a point source in a difference-image is detected, given that it exists).
(2) Science use-case examples of detection efficiencies and fake injection.
(3) A summary of existing LSST DM requirements and plans regarding detection efficiencies and fake injection.
(4) A review of the options for DM to enable or generate detection efficiencies, assessed under the criteria of scope, risk, requirements, and science.
(5) A precursory assembly of techniques for simulating artificial sources.