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This content will become publicly available on February 8, 2019

Title: DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs

The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding the effect of systematic uncertainties on measured signals and testing mitigation strategies for reducing these uncertainties, aiding analysis pipeline development and testing, and survey strategy optimization. The list of applications is growing with improvements in the quality of the catalogs and the details that they can provide. Given the importance of simulated catalogs, it is critical to provide rigorous validation protocols that enable both catalog providers and users to assess the quality of the catalogs in a straightforward and comprehensive way. For this purpose, we have developed the DESCQA framework for the Large Synoptic Survey Telescope Dark Energy Science Collaboration as well as for the broader community. The goal of DESCQA is to enable the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. Here in this paper, we present the design concept and first implementation of DESCQA. In order to establish and demonstrate its full functionality we use a set of interim catalogs and validationmore » tests. We highlight several important aspects, both technical and scientific, that require thoughtful consideration when designing a validation framework, including validation metrics and how these metrics impose requirements on the synthetic sky catalogs.« less
Authors:
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Publication Date:
Grant/Contract Number:
AC02-76SF00515
Type:
Accepted Manuscript
Journal Name:
The Astrophysical Journal. Supplement Series (Online)
Additional Journal Information:
Journal Name: The Astrophysical Journal. Supplement Series (Online); Journal Volume: 234; Journal Issue: 2; Journal ID: ISSN 1538-4365
Publisher:
American Astronomical Society/IOP
Research Org:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org:
USDOE
Contributing Orgs:
The LSST Dark Energy Science Collaboration
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; large-scale structure of universe; methods: numerical
OSTI Identifier:
1424028