Designing Imaging Surveys for a Retrospective Relative Photometric Calibration
Rory Holmes, David W. Hogg, Hans-Walter Rix

TL;DR
This study explores how survey strategies affect the accuracy of self-calibration in wide-field imaging surveys, emphasizing the importance of varied focal-plane coverage for precise photometric calibration.
Contribution
It demonstrates that diverse focal-plane coverage in survey design enables highly accurate retrospective self-calibration of complex instrument responses.
Findings
Diverse focal-plane coverage improves calibration accuracy.
Regular tiling strategies are less effective for self-calibration.
Simulations show successful calibration with complex instrument models.
Abstract
In this paper, we investigate the impact of survey strategy on the performance of self-calibration when the goal is to produce accurate photometric catalogs from wide-field imaging surveys. This self-calibration technique utilizes multiple measurements of sources at different focal-plane positions to constrain instruments' large-scale response (flat-field) from survey science data alone. We create an artificial sky of sources and synthetically observe it under four basic survey strategies, creating an end-to-end simulation of an imaging survey for each. These catalog-level simulations include realistic measurement uncertainties and a complex focal-plane dependence of the instrument response. In the self-calibration step, we simultaneously fit for all the star fluxes and the parameters of a position-dependent flat-field. For realism, we deliberately fit with a wrong noise model and a…
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