Window convolution of the galaxy clustering bispectrum

M.S. Wang et al.

Detalhes bibliográficos
Autores: Wang, Michael Shengbo, Gaztañaga, Enrique, Prada, Francisco
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/400473
Acesso em linha:http://hdl.handle.net/10261/400473
https://api.elsevier.com/content/abstract/scopus_id/105008527191
Access Level:acceso abierto
Palavra-chave:Galaxy clustering
Redshift surveys
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dc.title.none.fl_str_mv Window convolution of the galaxy clustering bispectrum
title Window convolution of the galaxy clustering bispectrum
spellingShingle Window convolution of the galaxy clustering bispectrum
Wang, Michael Shengbo
Galaxy clustering
Redshift surveys
title_short Window convolution of the galaxy clustering bispectrum
title_full Window convolution of the galaxy clustering bispectrum
title_fullStr Window convolution of the galaxy clustering bispectrum
title_full_unstemmed Window convolution of the galaxy clustering bispectrum
title_sort Window convolution of the galaxy clustering bispectrum
dc.creator.none.fl_str_mv Wang, Michael Shengbo
Gaztañaga, Enrique
Prada, Francisco
author Wang, Michael Shengbo
author_facet Wang, Michael Shengbo
Gaztañaga, Enrique
Prada, Francisco
author_role author
author2 Gaztañaga, Enrique
Prada, Francisco
author2_role author
author
dc.contributor.none.fl_str_mv European Commission
European Research Council
Ministerio de Ciencia e Innovación (España)
Wang, Michael Shengbo [0000-0002-2652-4043]
Gaztañaga, Enrique [0000-0001-9632-0815]
Prada, Francisco [0000-0001-7145-8674]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Galaxy clustering
Redshift surveys
topic Galaxy clustering
Redshift surveys
description M.S. Wang et al.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
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https://api.elsevier.com/content/abstract/scopus_id/105008527191
url http://hdl.handle.net/10261/400473
https://api.elsevier.com/content/abstract/scopus_id/105008527191
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info:eu-repo/grantAgreement/EC/H2020/853291
The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI :10.1088/1475-7516/2025/06/031
https://doi.org/10.1088/1475-7516/2025/06/031
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dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
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spelling Window convolution of the galaxy clustering bispectrumWang, Michael ShengboGaztañaga, EnriquePrada, FranciscoGalaxy clusteringRedshift surveysM.S. Wang et al.In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, for the bispectrum with a larger number of degrees of freedom, it poses a significant numerical and computational challenge. In this work, we consider the effect of the survey window in the tripolar spherical harmonic decomposition of the bispectrum and lay down a formal procedure for their convolution via a series expansion of configuration-space three-point correlation functions, which was first proposed by Sugiyama et al. (2019). We then provide a linear algebra formulation of the full window convolution, where an unwindowed bispectrum model vector can be directly premultiplied by a window matrix specific to each survey geometry. To validate the pipeline, we focus on the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) luminous red galaxy (LRG) sample in the South Galactic Cap (SGC) in the redshift bin 0.4 ≤ z ≤ 0.6. We first perform convergence checks on the measurement of the window function from discrete random catalogues, and then investigate the convergence of the window convolution series expansion truncated at a finite of number of terms as well as the performance of the window matrix. This work highlights the differences in window convolution between the power spectrum and bispectrum, and provides a streamlined pipeline for the latter for current surveys such as DESI and the Euclid mission.We would like to thank Hector Gil-Marín and Zachary Slepian for their helpful feedback on the manuscript. We would also like to thank Ashley Ross and Arnaud de Mattia for help with the mock catalogues, and Naonori Sugiyama for useful discussions. This project has received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement 853291). FB acknowledges the support of the Royal Society through the University Research Fellowship. This research used data obtained with the Dark Energy Spectroscopic Instrument (DESI). DESI construction and operations is managed by the Lawrence Berkeley National Laboratory. This material is based upon work supported by the United States Department of Energy (DOE), Office of Science, Office of High-Energy Physics, under Contract No. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract. Additional support for DESI was provided by the United States National Science Foundation (NSF), Division of Astronomical Sciences under Contract No. AST-0950945 to the NSF’s National Optical-Infrared Astronomy Research Laboratory; the Science and Technologies Facilities Council (STFC) of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico (CONACYT); the Ministry of Science and Innovation of Spain (MICINN), and by the DESI Member Institutions: https://www.desi.lbl.gov/collaborating-institutions/. The DESI Collaboration is honoured to be permitted to conduct scientific research on Iolkam Du’ag (Kitt Peak), a mountain with particular significance to the Tohono O’odham Nation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF, the DOE, or any of the listed funding agencies. This work used the DiRAC Data Intensive service at the University of Leicester (DIaL3), managed by the University of Leicester Research Computing Service on behalf of the STFC DiRAC HPC Facility (https://dirac.ac.uk/). The DiRAC service at Leicester was funded by the Department for Business, Energy & Industrial Strategy (BEIS), U.K. Research and Innovation (UKRI) and STFC capital funding and operations grants. DiRAC is part of the UKRI Digital Research InfrastructurePeer reviewedIOP PublishingEuropean CommissionEuropean Research CouncilMinisterio de Ciencia e Innovación (España)Wang, Michael Shengbo [0000-0002-2652-4043]Gaztañaga, Enrique [0000-0001-9632-0815]Prada, Francisco [0000-0001-7145-8674]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/400473https://api.elsevier.com/content/abstract/scopus_id/105008527191reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/853291The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI :10.1088/1475-7516/2025/06/031https://doi.org/10.1088/1475-7516/2025/06/031Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4004732026-05-22T06:33:51Z
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