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

Abstract

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 percent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in themore » 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.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [3];  [4];  [6]; ORCiD logo [7];  [8];  [9];  [10]; ORCiD logo [11];  [4];  [12];  [4];  [4];  [13];  [10];  [4] more »;  [14];  [10];  [14];  [4];  [15];  [16]; « less
  1. Department of Physics and Astronomy, University of California, Frederick Reines Hall, Irvine, CA 92697, USA, Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
  2. Department of Physics , Duke University, Durham, NC 27708, USA
  3. Department of Physics, Astronomy, Rutgers, The State University of New Jersey, 136 Frelinghuysen Rd, Piscataway, NJ 08854, USA
  4. SLAC National Accelerator Laboratory, 2575 Sand Hill Rd, Menlo Park, CA 94025, USA
  5. Department of Astronomy, University of Washington, Seattle, WA 98195, USA
  6. Department of Physics and Astronomy, University of California, Frederick Reines Hall, Irvine, CA 92697, USA
  7. McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  8. Brookhaven National Laboratory, Upton, NY 11973, USA
  9. Pittsburgh Particle Physics, Astrophysics, Cosmology Center (PITT PACC), Physics and Astronomy Department, University of Pittsburgh, Pittsburgh, PA 15260, USA
  10. Princeton University, Princeton, NJ 08544, USA
  11. Department of Physics and Astronomy, Purdue University, West Lafayette, IN 47907, USA, Department of Astronomy, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
  12. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
  13. LSST Project Office, Tucson, AZ 85721, USA
  14. Department of Physics and Astronomy, Purdue University, West Lafayette, IN 47907, USA
  15. Benedictine University, 5700 College Road, Lisle, IL 60532, USA
  16. Large Synoptic Survey Telescope, Tucson, AZ 85721, USA
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Carnegie Mellon Univ., Pittsburgh, PA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP); National Science Foundation (NSF)
Contributing Org.:
The LSST Dark Energy Science Collaboration
OSTI Identifier:
1641874
Alternate Identifier(s):
OSTI ID: 1597064; OSTI ID: 1755671
Report Number(s):
arXiv:2001.00941; FERMILAB-PUB-19-618-AE
Journal ID: ISSN 0035-8711
Grant/Contract Number:  
AC02-07CH11359; SC0009920; SC0010007; SC0011636; SC0010008; AC02-76SF00515; SC0010118; AC02-05CH11231
Resource Type:
Published Article
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Name: Monthly Notices of the Royal Astronomical Society Journal Volume: 497 Journal Issue: 1; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United Kingdom
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; methods: observational; catalogues; software: simulations; cosmology: dark energy

Citation Formats

Sánchez, J., Walter, C. W., Awan, H., Chiang, J., Daniel, S. F., Gawiser, E., Glanzman, T., Kirkby, D., Mandelbaum, R., Slosar, A., Wood-Vasey, W. M., AlSayyad, Y., Burke, C. J., Digel, S. W., Jarvis, M., Johnson, T., Kelly, H., Krughoff, S., Lupton, R. H., Marshall, P. J., Peterson, J. R., Price, P. A., Sembroski, G., Van Klaveren, B., Wiesner, M. P., Xin, B., and The LSST Dark Energy Science Collaboration. The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys. United Kingdom: N. p., 2020. Web. doi:10.1093/mnras/staa1957.
Sánchez, J., Walter, C. W., Awan, H., Chiang, J., Daniel, S. F., Gawiser, E., Glanzman, T., Kirkby, D., Mandelbaum, R., Slosar, A., Wood-Vasey, W. M., AlSayyad, Y., Burke, C. J., Digel, S. W., Jarvis, M., Johnson, T., Kelly, H., Krughoff, S., Lupton, R. H., Marshall, P. J., Peterson, J. R., Price, P. A., Sembroski, G., Van Klaveren, B., Wiesner, M. P., Xin, B., & The LSST Dark Energy Science Collaboration. The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys. United Kingdom. https://doi.org/10.1093/mnras/staa1957
Sánchez, J., Walter, C. W., Awan, H., Chiang, J., Daniel, S. F., Gawiser, E., Glanzman, T., Kirkby, D., Mandelbaum, R., Slosar, A., Wood-Vasey, W. M., AlSayyad, Y., Burke, C. J., Digel, S. W., Jarvis, M., Johnson, T., Kelly, H., Krughoff, S., Lupton, R. H., Marshall, P. J., Peterson, J. R., Price, P. A., Sembroski, G., Van Klaveren, B., Wiesner, M. P., Xin, B., and The LSST Dark Energy Science Collaboration. Mon . "The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys". United Kingdom. https://doi.org/10.1093/mnras/staa1957.
@article{osti_1641874,
title = {The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys},
author = {Sánchez, J. and Walter, C. W. and Awan, H. and Chiang, J. and Daniel, S. F. and Gawiser, E. and Glanzman, T. and Kirkby, D. and Mandelbaum, R. and Slosar, A. and Wood-Vasey, W. M. and AlSayyad, Y. and Burke, C. J. and Digel, S. W. and Jarvis, M. and Johnson, T. and Kelly, H. and Krughoff, S. and Lupton, R. H. and Marshall, P. J. and Peterson, J. R. and Price, P. A. and Sembroski, G. and Van Klaveren, B. and Wiesner, M. P. and Xin, B. and The LSST Dark Energy Science Collaboration},
abstractNote = {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 percent 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.},
doi = {10.1093/mnras/staa1957},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 1,
volume = 497,
place = {United Kingdom},
year = {Mon Jul 13 00:00:00 EDT 2020},
month = {Mon Jul 13 00:00:00 EDT 2020}
}

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