Forecasting the impact of source galaxy photometric redshift uncertainties on the LSST 3 × 2pt analysis

ABSTRACT Photometric redshifts of the source galaxies are a key source of systematic uncertainty in the Rubin Observatory Legacy Survey of Space and Time (LSST)’s galaxy clustering and weak lensing analysis, i.e. the $3\times 2$pt analysis. This paper introduces a Fisher forecast code fishera2z for the LSST Yr 10 (Y10) $3 \times 2$pt and cosmic shear analyses, utilizing a 15-parameter redshift distribution model, with one redshift bias, variance, and outlier rate per tomographic bin. fishera2z employs the Core Cosmology Library ccl to compute the large-scale structure power spectrum and incorporates a four-parameter non-linear alignment model for intrinsic alignments. We evaluate the impact of marginalizing over redshift distribution parameters on weak lensing, forecast biases in cosmological parameters due to redshift errors, and assess cosmological parameter sensitivity to redshift systematic parameters using decision trees. The sensitivity study reveals that for LSST $3 \times 2$pt analysis, $S_8$ is most sensitive to the mean redshift of the fourth out of the five source tomographic bins, while other cosmological parameters possess different sensitivities. Additionally, we provide cosmological analysis forecasts based on different scenarios of spectroscopic training data sets. We find that the figures-of-merit for the cosmological results increase with the number of spectroscopic training galaxies, and with the completeness of the training set above $z=1.6$, assuming the redshift information comes solely from the training set galaxies without other external constraints.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-12-03
DOI
https://doi.org/10.1093/mnras/staf1829
Citations
1
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
1.15

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article

Forecasting the impact of source galaxy photometric redshift uncertainties on the LSST 3 × 2pt analysis

Markus Michael Rau, C. Danielle Leonard, Brett H. Andrews, N. Šarčević et al.
1 citations
Monthly Notices of the Royal Astronomical Society
Galaxies: Formation, Evolution, Phenomena
1.15
article

Forecasting the impact of source galaxy photometric redshift uncertainties on the LSST 3 × 2pt analysis

Markus Michael Rau, C. Danielle Leonard, Brett H. Andrews, N. Šarčević, Jeffrey A. Newman, Husni Almoubayyed, Rachel Mandelbaum, Tianqing Zhang, Shuang Liang
article en
1 citations

Abstract

ABSTRACT Photometric redshifts of the source galaxies are a key source of systematic uncertainty in the Rubin Observatory Legacy Survey of Space and Time (LSST)’s galaxy clustering and weak lensing analysis, i.e. the $3\times 2$pt analysis. This paper introduces a Fisher forecast code fishera2z for the LSST Yr 10 (Y10) $3 \times 2$pt and cosmic shear analyses, utilizing a 15-parameter redshift distribution model, with one redshift bias, variance, and outlier rate per tomographic bin. fishera2z employs the Core Cosmology Library ccl to compute the large-scale structure power spectrum and incorporates a four-parameter non-linear alignment model for intrinsic alignments. We evaluate the impact of marginalizing over redshift distribution parameters on weak lensing, forecast biases in cosmological parameters due to redshift errors, and assess cosmological parameter sensitivity to redshift systematic parameters using decision trees. The sensitivity study reveals that for LSST $3 \times 2$pt analysis, $S_8$ is most sensitive to the mean redshift of the fourth out of the five source tomographic bins, while other cosmological parameters possess different sensitivities. Additionally, we provide cosmological analysis forecasts based on different scenarios of spectroscopic training data sets. We find that the figures-of-merit for the cosmological results increase with the number of spectroscopic training galaxies, and with the completeness of the training set above $z=1.6$, assuming the redshift information comes solely from the training set galaxies without other external constraints.

Monthly Notices of the Royal Astronomical SocietyVol. 545(2)
Argonne National Laboratory (US), University of Pittsburgh (US), Duke University (US), SLAC National Accelerator Laboratory (US), Carnegie Mellon University (US), Newcastle University (GB)
National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Gordon and Betty Moore Foundation, Centre National de la Recherche Scientifique, Office of Science, Science and Technology Facilities Council, Institut National de Physique Nucléaire et de Physique des Particules, SLAC National Accelerator Laboratory
Openalex Percentile: Top 15%
Galaxies: Formation, Evolution, Phenomena
1.15
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