Dark Energy Survey's Observation Strategy, Tactics, and Exposure Scheduler

TL;DR

The paper details the Dark Energy Survey's comprehensive strategy, tactics, and scheduling processes for its optical imaging survey, including decision-making, implementation, and evaluation of observational plans over multiple years.

Contribution

It introduces the DES observation scheduler 'obstac' and describes its development, application, and enhancements for optimizing survey scheduling and data quality assessment.

Findings

Effective scheduling strategies improved survey efficiency.

Simple seeing models are adequate for exposure planning.

The survey successfully completed six years of observations.

Abstract

The Dark Energy Survey is a stage III dark energy experiment, performing an optical imaging survey to measure cosmological equation of state parameters using four independent methods. The scope and complexity of the survey introduced complex strategic and tactical scheduling problems that needed to be addressed. We begin with an overview of the process used to develop DES strategy and tactics, from the inception of the project, to task forces that studied and developed strategy changes over the course of the survey, to the nightly pre-observing meeting in which immediate tactical issues were addressed. We then summarize the strategic choices made for each sub-survey, including metrics, scheduling considerations, choice of time domain fields and their sequences of exposures, and wide survey footprint and pointing layout choices. We go on to describe the detailed process that determined which specific exposures were taken at which specific times. We give a chronology of the strategic and tactical peculiarities of each year of observing, including the proposal and execution of a sixth year. We give an overview of obstac, the implementation of the DES scheduler used to simulate and evaluate strategic and tactical options, and automate exposure scheduling; and describe developments in obstac for use after DES. Appendices describe further details of data quality evaluation, tau, and t_eff; airmass calculation; and modeling of the seeing and sky brightness. The significant corpus of DES data indicates that the simple scaling relations for seeing as a function of wavelength and airmass derived from the Kolmogorov turbulence model work adequately for exposure planning purposes: deviations from these relations are modest in comparison with short time-scale seeing variations.