Getting Ready For Analysing Rubin Data : CLMM v2, The Updated LSST-DESC Cluster Weak Lensing Mass Modeling Library For Cosmology
Year: 2026
Type: preprint
Abstract: The Dark Energy Science Collaboration has prepared a multitude of pipelines to process the upcoming Vera C. Rubin Observatory data and perform different scientific analyses. Here, we present the methodology to constrain the mass information of galaxy clusters from weak lensing, which is encompassed by the v2.0 release of the Cluster Lensing Mass Modeling (CLMM) code. This Python library provides the ingredients for both the modeling and data reduction of lensing observables, and the improvements in the new version were customized to handle the first WL analyses of LSST clusters, including, e.g., stacking functionalities and WL multipoles. This new version of CLMM has allowed various cluster analyses using LSST-DESC simulated data, precursor survey and Rubin commissioning and survey validation data, and is ready to be used for the first cluster cosmology analyses. CLMM is an open-source software package collaboratively written in Python, providing multiple example notebooks, including a set that can reproduce all figures in this work, and extensive documentation, publicly available at https://lsstdesc.org/CLMM/.
Source: arXiv (Cornell University)
Authors: Aguena, Michel, Combet, Céline, Fu, Shenming, Payerne, Constantin, Ricci, Marina, Avestruz, Camille, Barroso, Eduardo, Caio, de Oliveira, Conghao, Zhou, Fan, Hsin, Murray, Calum, Niemiec, Anna, Sarcevic, Nikolina, Shin, Tae-hyeon, Solomon, Rance, Srinivasan, Radhakrishnan, Tomomi, Sunayama, Zhang, Yuanyuan, Zuntz, Joe
Institutions: Trieste Astronomical Observatory, Laboratório Interinstitucional de e-Astronomia, National Institute for Astrophysics, Centre National de la Recherche Scientifique, Institut National de Physique Nucléaire et de Physique des Particules, Université Grenoble Alpes, SLAC National Accelerator Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Université Paris Cité, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Paris-Saclay, Astrophysique, Instrumentation et Modélisation, Duke University, Carnegie Mellon University, Laboratoire d’Annecy de Physique des Particules, Stony Brook University, NSF NOIRLab, University of Edinburgh
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Energy, Princeton University, Ohio State University, University of Chicago, University College London, Deutsche Forschungsgemeinschaft, Ministry of Education, Culture, Sports, Science and Technology, Academia Sinica, Cabinet Office, Government of Japan, Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Centre National de la Recherche Scientifique, Financiadora de Estudos e Projetos, National Astronomical Observatory of Japan, High Energy Accelerator Research Organization, Institut de Física d'Altes Energies, Toray Science Foundation, University of Illinois at Urbana-Champaign, Office of Science, Science and Technology Facilities Council, Japan Society for the Promotion of Science, Japan Science and Technology Agency, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Institut National de Physique Nucléaire et de Physique des Particules, Integrated Electronics Engineering Center, Binghamton University, Argonne National Laboratory, Fermilab
Awards: G1141912172, G1229526393, G1286236842, G1313983767, G1863003419, G2371548206, G2638771445, G303061748, G3685081974, G419881185, G4264918310, G42916606, G4501827968, G4654690619, G4711507462, G495301720, G498139845, G5252970658, G5287069595, G5438923238, G5570207115, G618388848, G638836682, G6447494072, G6652958823, G6902702339, G8382000481, G8726098666
OpenAlex ID: W7224079438