The Astrophysical Journal Supplement Series (Jan 2024)

A Cohesive Deep Drilling Field Strategy for LSST Cosmology

  • Philippe Gris,
  • Humna Awan,
  • Matthew R. Becker,
  • Huan Lin,
  • Eric Gawiser,
  • Saurabh W. Jha,
  • The LSST Dark Energy Science Collaboration

DOI
https://doi.org/10.3847/1538-4365/ad79f5
Journal volume & issue
Vol. 275, no. 2
p. 21

Abstract

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The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will image billions of astronomical objects in the wide–fast–deep primary survey and in a set of minisurveys including intensive observations of a group of deep drilling fields (DDFs). The DDFs are a critical piece of three key aspects of the LSST Dark Energy Science Collaboration (DESC) cosmological measurements: they provide a required calibration for photometric redshifts (photo- z ) and weak gravitational lensing (WL) measurements and they directly contribute to cosmological constraints from the most distant Type Ia supernovae (SNe Ia). We present a set of cohesive DDF strategies fulfilling science requirements relevant to DESC and following the guidelines of the Survey Cadence Optimization Committee. We propose a method to estimate the observing strategy parameters and we perform simulations of the corresponding surveys. We define a set of metrics for each science case to assess the performance of the proposed observing strategies. We show that the most promising results are achieved with deep rolling surveys characterized by two sets of fields: ultradeep fields ( z ≲ 1.1) observed at a high cadence with a large number of visits over a limited number of seasons, and deep fields ( z ≲ 0.7), observed with a cadence of ∼3 nights for 10 yr. These encouraging results should be confirmed with realistic simulations using the LSST scheduler. A DDF budget of ∼8.5% is required to design observing strategies satisfying all the cosmological requirements. A lower DDF budget leads to surveys that either do not fulfill the photo- z /WL requirements or are not optimal for SN Ia cosmology.

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