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Euclid: Forecasts from redshift-space distortions and the Alcock–Paczynski test with cosmic voids

Hamaus, N. and Aubert, M. and Pisani, A. and Contarini, S. and Verza, G. and Cousinou, M.-C. and Escoffier, S. and Hawken, A. and Lavaux, G. and Pollina, G. and Wandelt, B. D. and Weller, J. and Bonici, M. and Carbone, C. and Guzzo, L. and Kovacs, A. and Marulli, F. and Massara, E. and Moscardini, L. and Ntelis, P. and Percival, W. J. and Radinović, S. and Sahlén, M. and Sakr, Z. and Sánchez, A. G. and Winther, H. A. and Auricchio, N. and Awan, S. and Bender, R. and Bodendorf, C. and Bonino, D. and Branchini, E. and Brescia, M. and Brinchmann, J. and Capobianco, V. and Carretero, J. and Castander, F. 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 Cropper, M. and Da Silva, A. and Degaudenzi, H. and Douspis, M. and Dubath, F. and Duncan, C. A. J. and Dupac, X. and Dusini, S. and Ealet, A. and Ferriol, S. and Fosalba, P. and Frailis, M. and Franceschi, E. and Franzetti, P. 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 Kilbinger, M. and Kitching, T. and Kümmel, M. and Kunz, M. and Kurki-Suonio, H. and Ligori, S. and Lilje, P. B. and Lloro, I. and Maiorano, E. and Marggraf, O. and Markovic, K. and Massey, R. and Maurogordato, S. and Melchior, M. and Meneghetti, M. and Meylan, G. and Moresco, M. and Munari, E. and Niemi, S. M. and Padilla, C. and Paltani, S. and Pasian, F. and Pedersen, K. and Pettorino, V. and Pires, S. and Poncet, M. and Popa, L. and Pozzetti, L. and Rebolo, R. and Rhodes, J. and Rix, H. and Roncarelli, M. and Rossetti, E. and Saglia, R. and Schneider, P. and Secroun, A. and Seidel, G. and Serrano, S. and Sirignano, C. and Sirri, G. and Starck, J.-L. and Tallada-Crespí, P. and Tavagnacco, D. 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 Mei, S. and Neissner, C. and Romelli, E. (2022) Euclid: Forecasts from redshift-space distortions and the Alcock–Paczynski test with cosmic voids. Astronomy and Astrophysics, 658 . Art. No. A20. ISSN 0004-6361. doi:10.1051/0004-6361/202142073. https://resolver.caltech.edu/CaltechAUTHORS:20220204-679616000

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Abstract

Euclid is poised to survey galaxies across a cosmological volume of unprecedented size, providing observations of more than a billion objects distributed over a third of the full sky. Approximately 20 million of these galaxies will have their spectroscopy available, allowing us to map the three-dimensional large-scale structure of the Universe in great detail. This paper investigates prospects for the detection of cosmic voids therein and the unique benefit they provide for cosmological studies. In particular, we study the imprints of dynamic (redshift-space) and geometric (Alcock–Paczynski) distortions of average void shapes and their constraining power on the growth of structure and cosmological distance ratios. To this end, we made use of the Flagship mock catalog, a state-of-the-art simulation of the data expected to be observed with Euclid. We arranged the data into four adjacent redshift bins, each of which contains about 11 000 voids and we estimated the stacked void-galaxy cross-correlation function in every bin. Fitting a linear-theory model to the data, we obtained constraints on f/b and D_MH, where f is the linear growth rate of density fluctuations, b the galaxy bias, D_M the comoving angular diameter distance, and H the Hubble rate. In addition, we marginalized over two nuisance parameters included in our model to account for unknown systematic effects in the analysis. With this approach, Euclid will be able to reach a relative precision of about 4% on measurements of f/b and 0.5% on D_MH in each redshift bin. Better modeling or calibration of the nuisance parameters may further increase this precision to 1% and 0.4%, respectively. Our results show that the exploitation of cosmic voids in Euclid will provide competitive constraints on cosmology even as a stand-alone probe. For example, the equation-of-state parameter, w, for dark energy will be measured with a precision of about 10%, consistent with previous more approximate forecasts.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1051/0004-6361/202142073DOIArticle
https://arxiv.org/abs/2108.10347arXivDiscussion Paper
ORCID:
AuthorORCID
Hamaus, N.0000-0002-0876-2101
Pisani, A.0000-0002-6146-4437
Contarini, S.0000-0002-9843-723X
Escoffier, S.0000-0002-2847-7498
Lavaux, G.0000-0003-0143-8891
Wandelt, B. D.0000-0002-5854-8269
Meneghetti, M.0000-0003-1225-7084
Rhodes, J.0000-0002-4485-8549
Additional Information:© ESO 2022. Received: 23 August 2021 Accepted: 31 October 2021. NH, GP and JW are supported by the Excellence Cluster ORIGINS, which is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2094 – 390783311. MA, MCC and SE are supported by the eBOSS ANR grant (under contract ANR-16-CE31-0021) of the French National Research Agency, the OCEVU LABEX (Grant No. ANR-11-LABX-0060) and the A*MIDEX project (Grant No. ANR-11-IDEX-0001-02) funded by the Investissements d’Avenir French government program, and by CNES, the French National Space Agency. AP is supported by NASA ROSES grant 12-EUCLID12-0004, and NASA grant 15-WFIRST15-0008 to the Nancy Grace Roman Space Telescope Science Investigation Team “Cosmology with the High Latitude Survey”. GL is supported by the ANR BIG4 project, grant ANR-16-CE23-0002 of the French Agence Nationale de la Recherche. PN is funded by the Centre National d’Etudes Spatiales (CNES). We acknowledge use of the Python libraries NumPy (Harris et al. 2020), SciPy (Virtanen et al. 2020), Matplotlib (Hunter 2007), Astropy (Astropy Collaboration 2013, 2018), emcee (Foreman-Mackey et al. 2019), GetDist (Lewis 2019), healpy (Górski et al. 2005; Zonca et al. 2019), and PyAbel (Hickstein et al. 2019). This work has made use of CosmoHub (Carretero et al. 2017; Tallada et al. 2020). CosmoHub has been developed by the Port d’Informació Científica (PIC), maintained through a collaboration of the Institut de Física d’Altes Energies (IFAE) and the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) and the Institute of Space Sciences (CSIC & IEEC), and was partially funded by the “Plan Estatal de Investigación Científica y Técnica y de Innovación” program of the Spanish government. 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 website (http://www.euclid-ec.org).
Group:Infrared Processing and Analysis Center (IPAC)
Funders:
Funding AgencyGrant Number
Deutsche Forschungsgemeinschaft (DFG)EXC-2094-390783311
Agence Nationale pour la Recherche (ANR)ANR-16-CE31-0021
Agence Nationale pour la Recherche (ANR)ANR-11-LABX-0060
Agence Nationale pour la Recherche (ANR)ANR-11-IDEX-0001-02
Centre National d'Études Spatiales (CNES)UNSPECIFIED
NASA12-EUCLID12-0004
NASA15-WFIRST15-0008
Agence Nationale pour la Recherche (ANR)ANR-16-CE23-0002
Plan Estatal de Investigación Científica y Técnica y de InnovaciónUNSPECIFIED
European Space Agency (ESA)UNSPECIFIED
Academy of FinlandUNSPECIFIED
Agenzia Spaziale Italiana (ASI)UNSPECIFIED
Belgian Federal Science Policy Office (BELSPO)UNSPECIFIED
Canadian Euclid ConsortiumUNSPECIFIED
Deutsches Zentrum für Luft- und Raumfahrt (DLR)UNSPECIFIED
Danish Space Research InstituteUNSPECIFIED
Fundação para a Ciência e a Tecnologia (FCT)UNSPECIFIED
Ministerio de Economia y Competitividad (MINECO)UNSPECIFIED
Nederlandse Onderzoekschool voor de Astronomie (NOVA)UNSPECIFIED
Norwegian Space AgencyUNSPECIFIED
Romanian Space AgencyUNSPECIFIED
Swiss Space Office (SSO)UNSPECIFIED
United Kingdom Space Agency (UKSA)UNSPECIFIED
Subject Keywords:cosmology: observations / cosmological parameters / dark energy / large-scale structure of Universe / methods: data analysis / surveys
DOI:10.1051/0004-6361/202142073
Record Number:CaltechAUTHORS:20220204-679616000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220204-679616000
Official Citation:Euclid: Forecasts from redshift-space distortions and the Alcock–Paczynski test with cosmic voids N. Hamaus, M. Aubert, A. Pisani, S. Contarini, G. Verza, M.-C. Cousinou, S. Escoffier, A. Hawken, G. Lavaux, G. Pollina, B. D. Wandelt, J. Weller, M. Bonici, C. Carbone, L. Guzzo, A. Kovacs, F. Marulli, E. Massara, L. Moscardini, P. Ntelis, W. J. Percival, S. Radinović, M. Sahlén, Z. Sakr, A. G. Sánchez, H. A. Winther, N. Auricchio, S. Awan, R. Bender, C. Bodendorf, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, V. Capobianco, J. Carretero, F. J. Castander, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, L. Conversi, Y. Copin, L. Corcione, M. Cropper, A. Da Silva, H. Degaudenzi, M. Douspis, F. Dubath, C. A. J. Duncan, X. Dupac, S. Dusini, A. Ealet, S. Ferriol, P. Fosalba, M. Frailis, E. Franceschi, P. Franzetti, 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, M. Kilbinger, T. Kitching, M. Kümmel, M. Kunz, H. Kurki-Suonio, S. Ligori, P. B. Lilje, I. Lloro, E. Maiorano, O. Marggraf, K. Markovic, R. Massey, S. Maurogordato, M. Melchior, M. Meneghetti, G. Meylan, M. Moresco, E. Munari, S. M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, V. Pettorino, S. Pires, M. Poncet, L. Popa, L. Pozzetti, R. Rebolo, J. Rhodes, H. Rix, M. Roncarelli, E. Rossetti, R. Saglia, P. Schneider, A. Secroun, G. Seidel, S. Serrano, C. Sirignano, G. Sirri, J.-L. Starck, P. Tallada-Crespí, D. Tavagnacco, 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, S. Mei, C. Neissner and E. Romelli A&A, 658 (2022) A20 DOI: https://doi.org/10.1051/0004-6361/202142073
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113287
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:08 Feb 2022 16:17
Last Modified:08 Feb 2022 16:17

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