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Uniform Rolling: An LSST Observing Cadence Offering Sufficient Survey Uniformity for Comprehensive Cosmological Analysis

Published version
Peer-reviewed

Repository DOI


Change log

Abstract

Abstract The Legacy Survey of Space and Time (LSST) that will be carried out by the NSF-DOE Vera C. Rubin Observatory promises to be the defining survey of the next decade for both static and time-domain science. Maximizing the LSST’s scientific output requires a nontrivial survey strategy (i.e., the sequence of observations in space, time, and passband). For time-domain science, the most promising strategy to date is a rolling survey strategy, whereby alternating subsets of the full LSST area are observed at a higher-than-nominal rate. Focusing on static science (galaxy clustering and weak lensing), we study how time-domain-optimized rolling strategies affect the depth uniformity at intermediate survey years and present new metrics directly connecting depth uniformity with science return. We characterize the amount of survey area at high risk of being lost in static-science analyses of a rolling LSST data set due to insufficient survey uniformity. At intermediate data releases, nearly half of the survey could be lost for static science, decreasing the dark energy figure of merit by 40%. We describe additional metrics focused on key analysis tasks, such as photometric redshifts and galaxy clustering. Finally, we propose a new strategy that returns the survey to uniformity at key release years, enabling use of the full area and restoring our metrics to the values they would have in a nonrolling cadence—without losing time domain data relative to a rolling survey with the same number of rolling cycles. These new “uniform rolling” strategies have been incorporated into the LSST baseline strategy.

Description

Journal Title

The Astrophysical Journal Supplement Series

Conference Name

Journal ISSN

0067-0049
1538-4365

Volume Title

284

Publisher

American Astronomical Society

Rights and licensing

Except where otherwised noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/
Sponsorship
Royal Society (The Royal Society) (P77450)
U.S. Department of Energy (DOE) (DE-SC0010118)
EC ∣ H2020 ∣ PRIORITY 'Excellent science' ∣ H2020 European Research Council (ERC) (101018897)