Euclid: Cosmological forecasts from the void size function
Abstract
The Euclid mission with its spectroscopic galaxy survey covering a sky area over in the redshift range will provide a sample of tens of thousands of cosmic voids. This paper explores for the first time the constraining power of the void size function on the properties of dark energy (DE) from a survey mock catalogue, the official Euclid Flagship simulation. We identify voids in the Flagship light-cone, which closely matches the features of the upcoming Euclid spectroscopic data set. We model the void size function considering a state-of-the art methodology: we rely on the volume conserving (Vdn) model, a modification of the popular Sheth & van de Weygaert model for void number counts, extended by means of a linear function of the large-scale galaxy bias. We find an excellent agreement between model predictions and measured mock void number counts. We compute updated forecasts for the Euclid mission on DE from the void size function and provide reliable void number estimates to serve as a basis for further forecasts of cosmological applications using voids. We analyse two different cosmological models for DE: the first described by a constant DE equation of state parameter, , and the second by a dynamic equation of state with coefficients and . We forecast errors on lower than , and we estimate an expected figure of merit (FoM) for the dynamical DE scenario when considering only the neutrino mass as additional free parameter of the model. The analysis is based on conservative assumptions to ensure full robustness, and is a pathfinder for future enhancements of the technique. Our results showcase the impressive constraining power of the void size function from the Euclid spectroscopic sample, both as a stand-alone probe, and to be combined with other Euclid cosmological probes.
Keywords
Cite
@article{arxiv.2205.11525,
title = {Euclid: Cosmological forecasts from the void size function},
author = {S. Contarini and G. Verza and A. Pisani and N. Hamaus and M. Sahlén and C. Carbone and S. Dusini and F. Marulli and L. Moscardini and A. Renzi and C. Sirignano and L. Stanco and M. Aubert and M. Bonici and G. Castignani and H. M. Courtois and S. Escoffier and D. Guinet and A. Kovacs and G. Lavaux and E. Massara and S. Nadathur and G. Pollina and T. Ronconi and F. Ruppin and Z. Sakr and A. Veropalumbo and B. D. Wandelt and A. Amara and N. Auricchio and M. Baldi and D. Bonino and E. Branchini and M. Brescia and J. Brinchmann and S. Camera and V. Capobianco and J. Carretero and M. Castellano and S. Cavuoti and R. Cledassou and G. Congedo and C. J. Conselice and L. Conversi and Y. Copin and L. Corcione and F. Courbin and M. Cropper and A. Da Silva and H. Degaudenzi and F. Dubath and C. A. J. Duncan and X. Dupac and A. Ealet and S. Farrens and S. Ferriol and P. Fosalba and M. Frailis and E. Franceschi and B. Garilli and W. Gillard and B. Gillis and C. Giocoli and A. Grazian and F. Grupp and L. Guzzo and S. Haugan and W. Holmes and F. Hormuth and K. Jahnke and M. Kümmel and S. Kermiche and A. Kiessling and M. Kilbinger and M. Kunz and H. Kurki-Suonio and R. Laureijs and S. Ligori and P. B. Lilje and I. Lloro and E. Maiorano and O. Mansutti and O. Marggraf and K. Markovic and R. Massey and M. Melchior and M. Meneghetti and G. Meylan and M. Moresco and E. Munari and S. M. Niemi and C. Padilla and S. Paltani and F. Pasian and K. Pedersen and W. J. Percival and V. Pettorino and S. Pires and G. Polenta and M. Poncet and L. Popa and L. Pozzetti and F. Raison and J. Rhodes and E. Rossetti and R. Saglia and B. Sartoris and P. Schneider and A. Secroun and G. Seidel and G. Sirri and C. Surace and P. Tallada-Crespí and A. N. Taylor and I. Tereno and R. Toledo-Moreo and F. Torradeflot and E. A. Valentijn and L. Valenziano and Y. Wang and J. Weller and G. Zamorani and J. Zoubian and S. Andreon and D. Maino and S. Mei},
journal= {arXiv preprint arXiv:2205.11525},
year = {2022}
}
Comments
19 pages, 7 figures, 4 tables - published in A&A