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Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies

Pires, S. and Vandenbussche, V. and Kansal, V. and Bender, R. and Blot, L. and Bonino, D. and Boucaud, A. and Brinchmann, J. and Capobianco, V. and Carretero, J. and Castellano, M. and Cavuoti, S. and Clédassou, R. and Congedo, G. and Conversi, L. and Corcione, L. and Dubath, F. and Fosalba, P. and Frailis, M. and Franceschi, E. and Fumana, M. and Grupp, F. and Hormuth, F. and Kermiche, S. and Knabenhans, M. and Kohley, R. and Kubik, B. and Kunz, M. and Ligori, S. and Lilje, P. B. and Lloro, I. and Maiorano, E. and Marggraf, O. and Massey, R. and Meylan, G. and Padilla, C. and Paltani, S. and Pasian, F. and Poncet, M. and Potter, D. and Raison, F. and Rhodes, J. and Roncarelli, M. and Saglia, R. and Schneider, P. and Secroun, A. and Serrano, S. and Stadel, J. and Tallada Crespí, P. and Tereno, I. and Toledo-Moreo, R. and Wang, Y. (2020) Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies. Astronomy and Astrophysics, 638 . Art. No. A141. ISSN 0004-6361. doi:10.1051/0004-6361/201936865.

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Weak lensing, which is the deflection of light by matter along the line of sight, has proven to be an efficient method for constraining models of structure formation and reveal the nature of dark energy. So far, most weak-lensing studies have focused on the shear field that can be measured directly from the ellipticity of background galaxies. However, within the context of forthcoming full-sky weak-lensing surveys such as Euclid, convergence maps (mass maps) offer an important advantage over shear fields in terms of cosmological exploitation. While it carry the same information, the lensing signal is more compressed in the convergence maps than in the shear field. This simplifies otherwise computationally expensive analyses, for instance, non-Gaussianity studies. However, the inversion of the non-local shear field requires accurate control of systematic effects caused by holes in the data field, field borders, shape noise, and the fact that the shear is not a direct observable (reduced shear). We present the two mass-inversion methods that are included in the official Euclid data-processing pipeline: the standard Kaiser & Squires method (KS), and a new mass-inversion method (KS+) that aims to reduce the information loss during the mass inversion. This new method is based on the KS method and includes corrections for mass-mapping systematic effects. The results of the KS+ method are compared to the original implementation of the KS method in its simplest form, using the Euclid Flagship mock galaxy catalogue. In particular, we estimate the quality of the reconstruction by comparing the two-point correlation functions and third- and fourth-order moments obtained from shear and convergence maps, and we analyse each systematic effect independently and simultaneously. We show that the KS+ method substantially reduces the errors on the two-point correlation function and moments compared to the KS method. In particular, we show that the errors introduced by the mass inversion on the two-point correlation of the convergence maps are reduced by a factor of about 5, while the errors on the third- and fourth-order moments are reduced by factors of about 2 and 10, respectively.

Item Type:Article
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Rhodes, J.0000-0002-4485-8549
Additional Information:© 2020 S. Pires et al. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Received 7 October 2019; Accepted 6 May 2020; Published online 26 June 2020. This paper is published on behalf of the Euclid Consortium. This study has been carried inside the Mass Mapping Work Package of the Weak Lensing Science Working Group of the Euclid project to better understand the impact of the mass inversion systematic effects on the convergence maps. The authors would like to thank the referees for their valuable comments, which helped to improve the manuscript. S. Pires thanks F. Sureau, J. Bobin, M. Kilbinger, A. Peel and J.-L. Starck for useful discussions. The Euclid Consortium acknowledges the European Space Agency and the support of a number of agencies and institutes that have supported the development of Euclid. A detailed complete list is available on the Euclid web site ( In particular the Academy of Finland, the Agenzia Spaziale Italiana, the Belgian Science Policy, the Canadian Euclid Consortium, the Centre National d’Etudes Spatiales, the Deutsches Zentrum für Luft- and Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciênca e a Tecnologia, the Ministerio de Economia y Competitividad, the National Aeronautics and Space Administration, the Netherlandse Onderzoekschool Voor Astronomie, the Norvegian Space Center, the Romanian Space Agency, the State Secretariat for Education, Research and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency.
Group:Infrared Processing and Analysis Center (IPAC)
Funding AgencyGrant Number
European Space Agency (ESA)UNSPECIFIED
Academy of FinlandUNSPECIFIED
Agenzia Spaziale Italiana (ASI)UNSPECIFIED
Belgian Federal Science Policy Office (BELSPO)UNSPECIFIED
Canadian Euclid ConsortiumUNSPECIFIED
Centre National d’Études Spatiales (CNES)UNSPECIFIED
Deutsches Zentrum für Luft- und Raumfahrt (DLR)UNSPECIFIED
Danish Space Research InstituteUNSPECIFIED
Fundação para a Ciência e a Tecnologia (FCT)UNSPECIFIED
Ministerio de Economía y Competitividad (MINECO)UNSPECIFIED
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)UNSPECIFIED
Norwegian Space CenterUNSPECIFIED
Romanian Space AgencyUNSPECIFIED
State Secretariat for Education, Research and Innovation (SER)UNSPECIFIED
Swiss Space Office (SSO)UNSPECIFIED
United Kingdom Space Agency (UKSA)UNSPECIFIED
Subject Keywords:gravitational lensing: weak – methods: data analysis – dark matter
Record Number:CaltechAUTHORS:20200629-123817826
Persistent URL:
Official Citation:Euclid: Reconstruction of weak-lensing mass maps for non-Gaussianity studies. S. Pires, V. Vandenbussche, V. Kansal, R. Bender, L. Blot, D. Bonino, A. Boucaud, J. Brinchmann, V. Capobianco, J. Carretero, M. Castellano, S. Cavuoti, R. Clédassou, G. Congedo, L. Conversi, L. Corcione, F. Dubath, P. Fosalba, M. Frailis, E. Franceschi, M. Fumana, F. Grupp, F. Hormuth, S. Kermiche, M. Knabenhans, R. Kohley, B. Kubik, M. Kunz, S. Ligori, P. B. Lilje, I. Lloro, E. Maiorano, O. Marggraf, R. Massey, G. Meylan, C. Padilla, S. Paltani, F. Pasian, M. Poncet, D. Potter, F. Raison, J. Rhodes, M. Roncarelli, R. Saglia, P. Schneider, A. Secroun, S. Serrano, J. Stadel, P. Tallada Crespí, I. Tereno, R. Toledo-Moreo and Y. Wang A&A, 638 (2020) A141. DOI:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104130
Deposited By: Tony Diaz
Deposited On:29 Jun 2020 20:10
Last Modified:16 Nov 2021 18:28

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