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

Publication ,  Journal Article
Sanchez, J; Walter, CW; Awan, H; Chiang, J; Daniel, SF; Gawiser, E; Glanzman, T; Kirkby, D; Mandelbaum, R; Slosar, A; Wood-Vasey, WM; Kelly, H ...
Published in: Monthly Notices of the Royal Astronomical Society
September 1, 2020

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 40 deg2 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 50 per 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 (2-6) in the estimated power spectra at small scales (> 1200), highlighting the impact of blending in studies at small angular scales in LSST.

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Published In

Monthly Notices of the Royal Astronomical Society

DOI

EISSN

1365-2966

ISSN

0035-8711

Publication Date

September 1, 2020

Volume

497

Issue

1

Start / End Page

210 / 228

Related Subject Headings

  • Astronomy & Astrophysics
  • 5109 Space sciences
  • 5107 Particle and high energy physics
  • 5101 Astronomical sciences
  • 0201 Astronomical and Space Sciences
 

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Sanchez, J., Walter, C. W., Awan, H., Chiang, J., Daniel, S. F., Gawiser, E., … Xin, B. (2020). The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys. Monthly Notices of the Royal Astronomical Society, 497(1), 210–228. https://doi.org/10.1093/mnras/staa1957
Sanchez, J., C. W. Walter, H. Awan, J. Chiang, S. F. Daniel, E. Gawiser, T. Glanzman, et al. “The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys.” Monthly Notices of the Royal Astronomical Society 497, no. 1 (September 1, 2020): 210–28. https://doi.org/10.1093/mnras/staa1957.
Sanchez J, Walter CW, Awan H, Chiang J, Daniel SF, Gawiser E, et al. The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys. Monthly Notices of the Royal Astronomical Society. 2020 Sep 1;497(1):210–28.
Sanchez, J., et al. “The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys.” Monthly Notices of the Royal Astronomical Society, vol. 497, no. 1, Sept. 2020, pp. 210–28. Scopus, doi:10.1093/mnras/staa1957.
Sanchez 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. The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys. Monthly Notices of the Royal Astronomical Society. 2020 Sep 1;497(1):210–228.
Journal cover image

Published In

Monthly Notices of the Royal Astronomical Society

DOI

EISSN

1365-2966

ISSN

0035-8711

Publication Date

September 1, 2020

Volume

497

Issue

1

Start / End Page

210 / 228

Related Subject Headings

  • Astronomy & Astrophysics
  • 5109 Space sciences
  • 5107 Particle and high energy physics
  • 5101 Astronomical sciences
  • 0201 Astronomical and Space Sciences