Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

M. Aguena; O. Alves; J. Annis; D. Bacon; S. Bocquet; D. Brooks; A. Carnero Rosell; C. Chang; M. Costanzi; C. Coviello; L. N. da Costa; T. M. Davis; J. De Vicente; H. T. Diehl; P. Doel; J. Esteves; S. Everett; I. Ferrero; A. Ferté; D. Friedel; J. Frieman; M. Gatti; G. Giannini; D. Gruen; R. A. Gruendl; G. Gutierrez; K. Herner; S. R. Hinton; D. L. Hollowood; K. Honscheid; D. J. James; T. Jeltema; M. Kirby; K. Kuehn; O. Lahav; P. Li; J. L. Marshall; T. McClintock; D. Mellor; J. Mena-Fernández; R. Miquel; J. O'Donnell; A. Palmese; M. Paterno; M. E. S. Pereira; A. Pieres; A. A. Plazas Malagón; M. Rodriguez-Monroy; A. K. Romer; A. Roodman; E. Sanchez; M. Schubnell; I. Sevilla-Noarbe; T. Shin; M. Smith; E. Suchyta; M. E. C. Swanson; G. Tarle; J. Weller; P. Wiseman; H. -Y. Wu; Y. Zhang; C. Zhou

arXiv · 2309.06593

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

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Abstract

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software infrastructure to explore an increasingly large parameter space, and account for various cosmological and astrophysical effects. Our software package is designed to model the cluster observables in a wide-field optical survey, including galaxy cluster counts, their averaged weak-lensing masses, or the cluster's averaged weak-lensing radial signals. To ensure maximum efficiency, this software package is developed in C++ in the CosmoSIS software framework, making use of the CUBA integration library. We also implement a testing and validation scheme to ensure the quality of the package. We demonstrate the effectiveness of this development by applying the software to the Dark Energy Survey Year 1 galaxy cluster cosmological data sets, and acquired cosmological constraints that are consistent with the fiducial Dark Energy Survey analysis.

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M. Aguena, O. Alves, J. Annis, D. Bacon, S. Bocquet, D. Brooks, A. Carnero Rosell, C. Chang, M. Costanzi, C. Coviello, L. N. da Costa, T. M. Davis, J. De Vicente, H. T. Diehl, P. Doel, J. Esteves, S. Everett, I. Ferrero, A. Ferté, D. Friedel, J. Frieman, M. Gatti, G. Giannini, D. Gruen, R. A. Gruendl, G. Gutierrez, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, T. Jeltema, M. Kirby, K. Kuehn, O. Lahav, P. Li, J. L. Marshall, T. McClintock, D. Mellor, J. Mena-Fernández, R. Miquel, J. O'Donnell, A. Palmese, M. Paterno, M. E. S. Pereira, A. Pieres, A. A. Plazas Malagón, M. Rodriguez-Monroy, A. K. Romer, A. Roodman, E. Sanchez, M. Schubnell, I. Sevilla-Noarbe, T. Shin, M. Smith, E. Suchyta, M. E. C. Swanson, G. Tarle, J. Weller, P. Wiseman, H. -Y. Wu, Y. Zhang, C. Zhou. 2023-09-12. Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing. https://arxiv.org/abs/2309.06593

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