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Published August 2021 | Published + Submitted
Journal Article Open

Euclid preparation. IX. EuclidEmulator2 – power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations

Knabenhans, M.
Stadel, J.
Potter, D.
Dakin, J.
Hannestad, S.
Tram, T.
Marelli, S.
Schneider, A.
Teyssier, R.
Andreon, S.
Auricchio, N.
Baccigalupi, C.
Balaguera-Antolínez, A.
Baldi, M.
Bardelli, S.
Battaglia, P.
Bender, R.
Biviano, A.
Bodendorf, C.
Bozzo, E.
Branchini, E.
Brescia, M.
Burigana, C.
Cabanac, R.
Camera, S.
Capobianco, V.
Cappi, A.
Carbone, C.
Carretero, J.
Carvalho, C. S.
Casas, R.
Casas, S.
Castellano, M.
Castignani, G.
Cavuoti, S.
Cledassou, R.
Colodro-Conde, C.
Congedo, G.
Conselice, C. J.
Conversi, L.
Copin, Y.
Corcione, L.
Coupon, J.
Courtois, H. M.
Da Silva, A.
de la Torre, S. ORCID icon
Di Ferdinando, D.
Duncan, C. A. J.
Dupac, X.
Fabbian, G.
Farrens, S.
Ferreira, P. G.
Finelli, F.
Frailis, M.
Franceschi, E.
Galeotta, S.
Garilli, B.
Giocoli, C.
Gozaliasl, G.
Graciá-Carpio, J.
Grupp, F.
Guzzo, L.
Holmes, W.
Hormuth, F.
Israel, H.
Jahnke, K.
Keihanen, E.
Kermiche, S.
Kirkpatrick, C. C.
Kubik, B.
Kunz, M.
Kurki-Suonio, H.
Ligori, S.
Lilje, P. B.
Lloro, I.
Maino, D.
Marggraf, O.
Markovic, K.
Martinet, N.
Marulli, F.
Massey, R.
Mauri, N.
Maurogordato, S.
Medinaceli, E.
Meneghetti, M.
Metcalf, B.
Meylan, G.
Moresco, M.
Morin, B.
Moscardini, L.
Munari, E.
Neissner, C.
Niemi, S. M.
Padilla, C.
Paltani, S.
Pasian, F.
Patrizii, L.
Pettorino, V.
Pires, S.
Polenta, G.
Poncet, M.
Raison, F.
Renzi, A.
Rhodes, J. ORCID icon
Riccio, G.
Romelli, E.
Roncarelli, M.
Saglia, R.
Sánchez, A. G.
Sapone, D.
Schneider, P.
Scottez, V.
Secroun, A.
Serrano, S.
Sirignano, C.
Sirri, G.
Stanco, L.
Sureau, F.
Tallada Crespí, P.
Taylor, A. N.
Tenti, M.
Tereno, I.
Toledo-Moreo, R.
Torradeflot, F.
Valenziano, L.
Valiviita, J.
Vassallo, T.
Viel, M.
Wang, Y.
Welikala, N.
Whittaker, L.
Zacchei, A.
Zucca, E.
Euclid Collaboration

Abstract

We present a new, updated version of the EuclidEmulator (called EuclidEmulator2), a fast and accurate predictor for the nonlinear correction of the matter power spectrum. 2 per cent level accurate emulation is now supported in the eight-dimensional parameter space of w₀w_aCDM+∑m_ν models between redshift z = 0 and z = 3 for spatial scales within the range 0.01 h Mpc⁻¹ ≤ k ≤ 10 h Mpc⁻¹⁠. In order to achieve this level of accuracy, we have had to improve the quality of the underlying N-body simulations used as training data: (i) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy, and the metric field, (ii) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (iii) we run over 250 high-resolution simulations with 30003 particles in boxes of 1(h⁻¹ Gpc)³ volumes based on paired-and-fixed initial conditions, and (iv) we provide a resolution correction that can be applied to emulated results as a post-processing step in order to drastically reduce systematic biases on small scales due to residual resolution effects in the simulations. We find that the inclusion of the dynamical dark energy parameter w_a significantly increases the complexity and expense of creating the emulator. The high fidelity of EuclidEmulator2 is tested in various comparisons against N-body simulations as well as alternative fast predictors such as HALOFIT, HMCode, and CosmicEmu. A blind test is successfully performed against the Euclid Flagship v2.0 simulation. Nonlinear correction factors emulated with EuclidEmulator2 are accurate at the level of 1 per cent or better for 0.01 h Mpc⁻¹ ≤ k ≤ 10 h Mpc⁻¹ and z ≤ 3 compared to high-resolution dark-matter-only simulations. EuclidEmulator2 is publicly available at https://github.com/miknab/EuclidEmulator2.

Additional Information

© 2021 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2021 May 2. Received 2021 May 2; in original form 2020 October 23. Published: 14 May 2021. MK acknowledges support from the Swiss National Science Foundation (SNF) grant 200020_149848 and the Forschungskredit of the University of Zurich, grant no. K-76102-01-01. Simulations were performed on the PizDaint supercomputer at the Swiss National Scientific supercomputing center CSCS and on the zBox4+ cluster at the University of Zurich. The Euclid Consortium acknowledges 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). Data Availability: The data underlying this article will be shared on reasonable request to the corresponding author.

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Additional details

Created:
August 20, 2023
Modified:
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