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Euclid: Forecast constraints on consistency tests of the ΛCDM model

Nesseris, S. and Sapone, D. and Martinelli, M. and Camarena, D. and Marra, V. and Sakr, Z. and García-Bellido, J. and Martins, C. J. A. P. and Clarkson, C. and Da Silva, A. and Fleury, P. and Lombriser, L. and Mimoso, J. P. and Casas, S. and Pettorino, V. and Tutusaus, I. and Amara, A. and Auricchio, N. and Bodendorf, C. and Bonino, D. and Branchini, E. and Brescia, M. and Capobianco, V. and Carbone, C. and Carretero, J. and Castellano, M. and Cavuoti, S. and Cimatti, A. and Cledassou, R. and Congedo, G. and Conversi, L. and Copin, Y. and Corcione, L. and Courbin, F. and Cropper, M. and Degaudenzi, H. and Douspis, M. and Dubath, F. and Duncan, C. A. J. and Dupac, X. and Dusini, S. and Ealet, A. and Farrens, S. and Fosalba, P. and Frailis, M. and Franceschi, E. and Fumana, M. and Garilli, B. and Gillis, B. and Giocoli, C. and Grazian, A. and Grupp, F. and Haugan, S. V. H. and Holmes, W. and Hormuth, F. and Jahnke, K. and Kermiche, S. and Kiessling, A. and Kitching, T. and Kümmel, M. and Kunz, M. and Kurki-Suonio, H. and Ligori, S. and Lilje, P. B. and Lloro, I. and Mansutti, O. and Marggraf, O. and Markovic, K. and Marulli, F. and Massey, R. and Meneghetti, M. and Merlin, E. and Meylan, G. and Moresco, M. and Moscardini, L. and Munari, E. and Niemi, S. M. and Padilla, C. and Paltani, S. and Pasian, F. and Pedersen, K. and Percival, W. J. and Poncet, M. and Popa, L. and Racca, G. D. and Raison, F. and Rhodes, J. and Roncarelli, M. and Saglia, R. and Sartoris, B. and Schneider, P. and Secroun, A. and Seidel, G. and Serrano, S. and Sirignano, C. and Sirri, G. and Stanco, L. and Starck, J.-L. and Tallada-Crespí, P. and Taylor, A. N. and Tereno, I. and Toledo-Moreo, R. and Torradeflot, F. and Valentijn, E. A. and Valenziano, L. and Wang, Y. and Welikala, N. and Zamorani, G. and Zoubian, J. and Andreon, S. and Baldi, M. and Camera, S. and Medinaceli, E. and Mei, S. and Renzini, A. (2022) Euclid: Forecast constraints on consistency tests of the ΛCDM model. Astronomy and Astrophysics, 660 . Art. No. A67. ISSN 0004-6361. doi:10.1051/0004-6361/202142503. https://resolver.caltech.edu/CaltechAUTHORS:20220414-26796000

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Abstract

Context. The standard cosmological model is based on the fundamental assumptions of a spatially homogeneous and isotropic universe on large scales. An observational detection of a violation of these assumptions at any redshift would immediately indicate the presence of new physics. Aims. We quantify the ability of the Euclid mission, together with contemporary surveys, to improve the current sensitivity of null tests of the canonical cosmological constant Λ and the cold dark matter (ΛCDM) model in the redshift range 0 z < 1.8. Methods. We considered both currently available data and simulated Euclid and external data products based on a ΛCDM fiducial model, an evolving dark energy model assuming the Chevallier-Polarski-Linder parameterization or an inhomogeneous Lemaître-Tolman-Bondi model with a cosmological constant Λ, and carried out two separate but complementary analyses: a machine learning reconstruction of the null tests based on genetic algorithms, and a theory-agnostic parametric approach based on Taylor expansion and binning of the data, in order to avoid assumptions about any particular model. Results. We find that in combination with external probes, Euclid can improve current constraints on null tests of the ΛCDM by approximately a factor of three when using the machine learning approach and by a further factor of two in the case of the parametric approach. However, we also find that in certain cases, the parametric approach may be biased against or missing some features of models far from ΛCDM. Conclusions. Our analysis highlights the importance of synergies between Euclid and other surveys. These synergies are crucial for providing tighter constraints over an extended redshift range for a plethora of different consistency tests of some of the main assumptions of the current cosmological paradigm.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1051/0004-6361/202142503DOIArticle
https://arxiv.org/abs/2110.11421arXivDiscussion Paper
ORCID:
AuthorORCID
Nesseris, S.0000-0002-0567-0324
Sapone, D.0000-0001-7089-4503
García-Bellido, J.0000-0002-9370-8360
Pettorino, V.0000-0002-4203-9320
Tutusaus, I.0000-0002-3199-0399
Auricchio, N.0000-0003-4444-8651
Bonino, D.0000-0002-3336-9977
Branchini, E.0000-0002-0808-6908
Brescia, M.0000-0001-9506-5680
Capobianco, V.0000-0002-3309-7692
Carretero, J.0000-0002-3130-0204
Castellano, M.0000-0001-9875-8263
Cavuoti, S.0000-0002-3787-4196
Cimatti, A.0000-0002-4409-5633
Cledassou, R.0000-0002-8313-2230
Congedo, G.0000-0003-2508-0046
Conversi, L.0000-0002-6710-8476
Copin, Y.0000-0002-5317-7518
Corcione, L.0000-0002-6497-5881
Cropper, M.0000-0003-4571-9468
Dusini, S.0000-0002-1128-0664
Farrens, S.0000-0002-9594-9387
Fosalba, P.0000-0002-1510-5214
Frailis, M.0000-0002-7400-2135
Franceschi, E.0000-0002-0585-6591
Garilli, B.0000-0001-7455-8750
Gillis, B.0000-0002-4478-1270
Giocoli, C.0000-0002-9590-7961
Jahnke, K.0000-0003-3804-2137
Kermiche, S.0000-0002-0302-5735
Kitching, T.0000-0002-4061-4598
Kunz, M.0000-0003-1676-6126
Kurki-Suonio, H.0000-0002-4618-3063
Ligori, S.0000-0003-4172-4606
Lloro, I.0000-0001-5966-1434
Mansutti, O.0000-0001-5758-4658
Marggraf, O.0000-0001-7242-3852
Marulli, F.0000-0002-8850-0303
Massey, R.0000-0002-6085-3780
Meneghetti, M.0000-0003-1225-7084
Merlin, E.0000-0001-6870-8900
Moresco, M.0000-0002-7616-7136
Moscardini, L.0000-0002-3473-6716
Padilla, C.0000-0001-7951-0166
Paltani, S.0000-0002-8108-9179
Percival, W. J.0000-0002-0644-5727
Rhodes, J.0000-0002-4485-8549
Roncarelli, M.0000-0001-9587-7822
Saglia, R.0000-0003-0378-7032
Schneider, P.0000-0002-5094-2245
Secroun, A.0000-0003-0505-3710
Tereno, I.0000-0002-4537-6218
Toledo-Moreo, R.0000-0002-2997-4859
Valentijn, E. A.0000-0003-1032-6680
Valenziano, L.0000-0002-1170-0104
Wang, Y.0000-0002-4749-2984
Zamorani, G.0000-0002-2318-301X
Andreon, S.0000-0002-2041-8784
Baldi, M.0000-0003-4145-1943
Camera, S.0000-0003-3399-3574
Medinaceli, E.0000-0002-4040-7783
Mei, S.0000-0002-2849-559X
Renzini, A.0000-0002-7093-7355
Additional Information:© ESO 2022. Received: 21 October 2021 Accepted: 26 January 2022. We are grateful to S. Ávila for interesting discussions. J.G.B., M.M. and S.N. acknowledge support from the research project PGC2018-094773-B-C32, and the Centro de Excelencia Severo Ochoa Program SEV-2016-059. S.N. also acknowledges support from the Ramón y Cajal program through Grant No. RYC-2014-15843. M.M. also received support from “la Caixa” Foundation (ID 100010434), with fellowship code LCF/BQ/PI19/11690015. D.S. acknowledges financial support from the Fondecyt Regular project number 1200171. The work of CJM was financed by FEDER – Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 – Operational Programme for Competitiveness and Internationalisation (POCI), and by Portuguese funds through FCT – Fundação para a Ciência e a Tecnologia in the framework of the project POCI-01-0145-FEDER-028987. D.C. thanks CAPES for financial support. V.M. thanks CNPq and FAPES for partial financial support. L.L. was supported by a Swiss National Science Foundation (SNSF) Professorship grant (No. 170547). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 888258. C.C. is supported by the UK Science and Technology Facilities Council (STFC) Consolidated Grant ST/P000592/1. A.dS. acknowledges support from the Fundação para a Ciência e a Tecnologia (FCT) through the Investigador FCT Contract No. IF/01135/2015 and POCH/FSE (EC) and in the form of an exploratory project with the same reference. J.P.M. and A.dS. acknowledge support from FCT Projects with references EXPL/FIS-AST/1368/2021, PTDC/FIS-AST/0054/2021, UIDB/04434/2020, UIDP/04434/2020, CERN/FIS-PAR/0037/2019, PTDC/FIS-OUT/29048/2017. Z.S. acknowledges support from the IRAP and IN2P3 Lyon computing centers. P.F. received the support of a fellowship from “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/PI19/11690018. I.T. acknowledges support from the Spanish Ministry of Science, Innovation and Universities through grant ESP2017-89838, and the H2020 programme of the European Commission through grant 776247. The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, 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-und Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciência e a Tecnologia, the Ministerio de Economia y Competitividad, the National Aeronautics and Space Administration, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, 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. A complete and detailed list is available on the Euclid web site (http://www.euclid-ec.org).
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
Fondo Europeo de Desarrollo Regional (FEDER)PGC2018-094773-B-C32
Centro de Excelencia Severo OchoaSEV-2016-0597
Ramón y Cajal programmeRYC-2014-15843
La Caixa Foundation100010434
La Caixa FoundationLCF/BQ/PI19/11690015
Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT)1200171
Fundação para a Ciência e a Tecnologia (FCT)POCI-01-0145-FEDER-028987
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)UNSPECIFIED
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)UNSPECIFIED
Fundacao de Assistencia e Previdencia Social do BNDES (FAPES)UNSPECIFIED
Swiss National Science Foundation (SNSF)170547
European Research Council (ERC)888258
Science and Technology Facilities Council (STFC)ST/P000592/1
Fundação para a Ciência e a Tecnologia (FCT)IF/01135/2015
Fundação para a Ciência e a Tecnologia (FCT)EXPL/FIS-AST/1368/2021
Fundação para a Ciência e a Tecnologia (FCT)PTDC/FIS-AST/0054/2021
Fundação para a Ciência e a Tecnologia (FCT)UIDB/04434/2020
Fundação para a Ciência e a Tecnologia (FCT)UIDP/04434/2020
Fundação para a Ciência e a Tecnologia (FCT)CERN/FIS-PAR/0037/2019
Fundação para a Ciência e a Tecnologia (FCT)PTDC/FIS-OUT/29048/2017
Institut de Recherche en Astrophysique et PlanétologieUNSPECIFIED
Institut National de Physique Nucléaire et de Physique des Particules (IN2P3)UNSPECIFIED
La Caixa FoundationLCF/BQ/PI19/11690018
Ministerio de Ciencia, Innovación y Universidades (MICIU)ESP2017-89838
European Research Council (ERC)776247
Euclid ConsortiumUNSPECIFIED
Subject Keywords:dark energy / large-scale structure of Universe / cosmology: observations
DOI:10.1051/0004-6361/202142503
Record Number:CaltechAUTHORS:20220414-26796000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220414-26796000
Official Citation:Euclid: Forecast constraints on consistency tests of the ΛCDM model S. Nesseris, D. Sapone, M. Martinelli, D. Camarena, V. Marra, Z. Sakr, J. Garcia-Bellido, C. J. A. P. Martins, C. Clarkson, A. Da Silva, P. Fleury, L. Lombriser, J. P. Mimoso, S. Casas, V. Pettorino, I. Tutusaus, A. Amara, N. Auricchio, C. Bodendorf, D. Bonino, E. Branchini, M. Brescia, V. Capobianco, C. Carbone, J. Carretero, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, L. Conversi, Y. Copin, L. Corcione, F. Courbin, M. Cropper, H. Degaudenzi, M. Douspis, F. Dubath, C. A. J. Duncan, X. Dupac, S. Dusini, A. Ealet, S. Farrens, P. Fosalba, M. Frailis, E. Franceschi, M. Fumana, B. Garilli, B. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V. H. Haugan, W. Holmes, F. Hormuth, K. Jahnke, S. Kermiche, A. Kiessling, T. Kitching, M. Kümmel, M. Kunz, H. Kurki-Suonio, S. Ligori, P. B. Lilje, I. Lloro, O. Mansutti, O. Marggraf, K. Markovic, F. Marulli, R. Massey, M. Meneghetti, E. Merlin, G. Meylan, M. Moresco, L. Moscardini, E. Munari, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, M. Poncet, L. Popa, G. D. Racca, F. Raison, J. Rhodes, M. Roncarelli, R. Saglia, B. Sartoris, P. Schneider, A. Secroun, G. Seidel, S. Serrano, C. Sirignano, G. Sirri, L. Stanco, J.-L. Starck, P. Tallada-Crespí, A. N. Taylor, I. Tereno, R. Toledo-Moreo, F. Torradeflot, E. A. Valentijn, L. Valenziano, Y. Wang, N. Welikala, G. Zamorani, J. Zoubian, S. Andreon, M. Baldi, S. Camera, E. Medinaceli, S. Mei and A. Renzi A&A, 660 (2022) A67 DOI: https://doi.org/10.1051/0004-6361/202142503
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114315
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:18 Apr 2022 22:10
Last Modified:18 Apr 2022 22:10

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