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The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys

Title: The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys
Authors: Sánchez, J; Walter, CW; Awan, H; Chiang, J; Daniel, SF; Gawiser, E; Glanzman, T; Kirkby, D; Mandelbaum, R; Slosar, A; Wood-Vasey, WM; AlSayyad, Y; Burke, CJ; Digel, SW; Jarvis, M; Johnson, T; Kelly, H; Krughoff, S; Lupton, RH; Marshall, PJ; Peterson, JR; Price, PA; Sembroski, G; Van Klaveren, B; Wiesner, MP; Xin, B; Collaboration, The LSST Dark Energy Science
Source: Monthly Notices of the Royal Astronomical Society, vol 497, iss 1
Publisher Information: eScholarship, University of California
Publication Year: 2020
Collection: University of California: eScholarship
Subject Terms: 5101 Astronomical Sciences (for-2020); 51 Physical Sciences (for-2020); methods: observational; catalogues; software: simulations; cosmology: dark energy; astro-ph.IM; 0201 Astronomical and Space Sciences (for); Astronomy & Astrophysics (science-metrix); 5107 Particle and high energy physics (for-2020); 5109 Space sciences (for-2020)
Subject Geographic: 210 - 228
Description: Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ> 1200), highlighting the impact of blending in studies at small angular scales in LSST.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: unknown
Relation: qt4jq619pr; https://escholarship.org/uc/item/4jq619pr; https://escholarship.org/content/qt4jq619pr/qt4jq619pr.pdf
DOI: 10.1093/mnras/staa1957
Availability: https://escholarship.org/uc/item/4jq619pr; https://escholarship.org/content/qt4jq619pr/qt4jq619pr.pdf; https://doi.org/10.1093/mnras/staa1957
Rights: CC-BY
Accession Number: edsbas.10B193B0
Database: BASE