DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST

Abstract

We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis.

Authors:
ORCiD logo; ORCiD logo; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »; « less
Publication Date:
Research Org.:
Argonne National Laboratory (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF); 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)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Org.:
The LSST Dark Energy Science Collaboration
OSTI Identifier:
1973625
Report Number(s):
FERMILAB-PUB-23-221-CSAID; arXiv:2212.09345
Journal ID: ISSN 2565-6120; oai:inspirehep.net:2616184; TRN: US2313913
Grant/Contract Number:  
AC02-07CH11359; AC02-05CH11231; AC02-76SF00515; AC02-06CH11357; SC0021949; SC0010008
Resource Type:
Accepted Manuscript
Journal Name:
The Open Journal of Astrophysics
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2565-6120
Publisher:
Maynooth Academic Publishing
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; data analysis; Rubin Observatory; LSST; Dark Energy Science Collaboration; weak gravitational lensing; galaxy clustering; cosmology

Citation Formats

Prat, J., Zuntz, J., Chang, C., Tröster, T., Pedersen, E., García-García, C., Phillips-Longley, E., Sanchez, J., Alonso, David, Fang, X., Gawiser, E., Heitmann, K., Ishak, M., Jarvis, M., Kovacs, E., Larsen, P., Mao, Y. -Y., Medina Varela, L., Paterno, M., Vitenti, S. D., and Zhang, Z. The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST. United States: N. p., 2023. Web. doi:10.21105/astro.2212.09345.
Prat, J., Zuntz, J., Chang, C., Tröster, T., Pedersen, E., García-García, C., Phillips-Longley, E., Sanchez, J., Alonso, David, Fang, X., Gawiser, E., Heitmann, K., Ishak, M., Jarvis, M., Kovacs, E., Larsen, P., Mao, Y. -Y., Medina Varela, L., Paterno, M., Vitenti, S. D., & Zhang, Z. The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST. United States. https://doi.org/10.21105/astro.2212.09345
Prat, J., Zuntz, J., Chang, C., Tröster, T., Pedersen, E., García-García, C., Phillips-Longley, E., Sanchez, J., Alonso, David, Fang, X., Gawiser, E., Heitmann, K., Ishak, M., Jarvis, M., Kovacs, E., Larsen, P., Mao, Y. -Y., Medina Varela, L., Paterno, M., Vitenti, S. D., and Zhang, Z. Tue . "The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST". United States. https://doi.org/10.21105/astro.2212.09345. https://www.osti.gov/servlets/purl/1973625.
@article{osti_1973625,
title = {The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST},
author = {Prat, J. and Zuntz, J. and Chang, C. and Tröster, T. and Pedersen, E. and García-García, C. and Phillips-Longley, E. and Sanchez, J. and Alonso, David and Fang, X. and Gawiser, E. and Heitmann, K. and Ishak, M. and Jarvis, M. and Kovacs, E. and Larsen, P. and Mao, Y. -Y. and Medina Varela, L. and Paterno, M. and Vitenti, S. D. and Zhang, Z.},
abstractNote = {We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis.},
doi = {10.21105/astro.2212.09345},
journal = {The Open Journal of Astrophysics},
number = ,
volume = 6,
place = {United States},
year = {Tue Apr 25 00:00:00 EDT 2023},
month = {Tue Apr 25 00:00:00 EDT 2023}
}