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SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy

Publication ,  Journal Article
Sánchez, BO; Kessler, R; Scolnic, D; Armstrong, R; Biswas, R; Bogart, J; Chiang, J; Cohen-Tanugi, J; Fouchez, D; Gris, P; Heitmann, K; Jha, S ...
Published in: Astrophysical Journal
August 1, 2022

The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ∼106 transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg2) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ∼15 deg2 of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ∼90% of all detections, corresponding to ∼1000 artifacts deg-2 in g band, and falling to 300 deg-2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.

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Published In

Astrophysical Journal

DOI

EISSN

1538-4357

ISSN

0004-637X

Publication Date

August 1, 2022

Volume

934

Issue

2

Related Subject Headings

  • Astronomy & Astrophysics
  • 5109 Space sciences
  • 5107 Particle and high energy physics
  • 5101 Astronomical sciences
  • 0306 Physical Chemistry (incl. Structural)
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics
  • 0201 Astronomical and Space Sciences
 

Citation

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Sánchez, B. O., Kessler, R., Scolnic, D., Armstrong, R., Biswas, R., Bogart, J., … Wood-Vasey, W. M. (2022). SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy. Astrophysical Journal, 934(2). https://doi.org/10.3847/1538-4357/ac7a37
Sánchez, B. O., R. Kessler, D. Scolnic, R. Armstrong, R. Biswas, J. Bogart, J. Chiang, et al. “SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy.” Astrophysical Journal 934, no. 2 (August 1, 2022). https://doi.org/10.3847/1538-4357/ac7a37.
Sánchez BO, Kessler R, Scolnic D, Armstrong R, Biswas R, Bogart J, et al. SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy. Astrophysical Journal. 2022 Aug 1;934(2).
Sánchez, B. O., et al. “SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy.” Astrophysical Journal, vol. 934, no. 2, Aug. 2022. Scopus, doi:10.3847/1538-4357/ac7a37.
Sánchez BO, Kessler R, Scolnic D, Armstrong R, Biswas R, Bogart J, Chiang J, Cohen-Tanugi J, Fouchez D, Gris P, Heitmann K, Hložek R, Jha S, Kelly H, Liu S, Narayan G, Racine B, Rykoff E, Sullivan M, Walter CW, Wood-Vasey WM. SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy. Astrophysical Journal. 2022 Aug 1;934(2).
Journal cover image

Published In

Astrophysical Journal

DOI

EISSN

1538-4357

ISSN

0004-637X

Publication Date

August 1, 2022

Volume

934

Issue

2

Related Subject Headings

  • Astronomy & Astrophysics
  • 5109 Space sciences
  • 5107 Particle and high energy physics
  • 5101 Astronomical sciences
  • 0306 Physical Chemistry (incl. Structural)
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics
  • 0201 Astronomical and Space Sciences