<i>Euclid</i>: Cosmological forecasts from the void size function

Contarini, S.; Verza, Giovanni; Pisani, Alice; Hamaus, Nico; Sahlén, Martin; Carbone, C.; Dusini, S.; Marulli, F.; Moscardini, L.; Renzi, A.; Sirignano, C.; Stančo, L.; Aubert, M; Bonici, Marco; Castignani, G.; Courtois, H. M.; Escoffier, S.; Guinet, D.; Kovács, András; Lavaux, Guilhem; Massara, Elena; Nadathur, Seshadri; Pollina, Giorgia; Ronconi, Tommaso; Ruppin, F.; Sakr, Z.; Veropalumbo, Alfonso; Wandelt, B. D.; Amara, Adam; Auricchio, N.; Baldi, Marco; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, Jarle; Camera, Stefano; Capobianco, V.; Carretero, J.; Castellano, M.; Cavuoti, S.; Clédassou, R.; Congedo, G.; Conselice, Christopher J.; Conversi, L.; Copin, Y.; Corcione, L.; Courbin, F.; Cropper, Mark; Silva, A. Da; Degaudenzi, H.; Dubath, F.; Duncan, C. A. J.; Dupac, X.; Ealet, A.; Farrens, S.; Ferriol, S.; Fosalba, P.; Frailis, M.; Franceschi, E.; Garilli, B.; Gillard, W.; Gillis, B.; Giocoli, Carlo; Grazian, A.; Grupp, F.; Guzzo, L.; Haugan, S. V. H.; Holmes, W. A.; Hormuth, F.; Jahnke, K.; Kümmel, M.; Kermiche, S.; Kiessling, Alina; Kilbinger, M.; Kunz, M.; Kurki-Suonio, H.; Laureijs, R. J.; Ligori, S.; Lilje, P. B.; Lloro, I.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovič, K.; Massey, Richard; Melchior, M.; Meneghetti, M.; Meylan, G.; Moresco, M.; Munari, E.; Niemi, S. M.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Percival, Will J.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L.; Pozzetti, L.; Raison, F.; Rhodes, Jason; Rossetti, E.; Saglia, R.; Sartoris, B.; Schneider, Peter; Secroun, A.; Seidel, G.; Sirri, G.; Surace, C.; Tallada-Crespí, P.; Taylor, Andy; Tereno, I.; Toledo-Moreo, R.; Torradeflot, F.; Valentijn, E. A.; Valenziano, L.; Wang, Y.; Weller, J.; Zamorani, G.; Zoubian, J.; Andreon, S.; Maino, D.; Mei, S.

doi:10.1051/0004-6361/202244095

Cited by 13 publications

(28 citation statements)

References 189 publications

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“…where d v,tr NL is the tracer density contrast embedded by voids identified in the tracer field and, as already mentioned, d v,DM NL is the matter underdensity threshold to be used in the void size function model, after its conversion from linear theory. The two coefficients regulating the slope and the offset of the linear function b eff ( ), i.e., B slope and B offset , are redshift independent and can be derived by calibrating the void size function model with simulations (Contarini et al 2019(Contarini et al , 2021(Contarini et al , 2022. They have been shown to depend on the kind of tracers used to identify the voids, but also to have a negligible dependence on the cosmological model (Contarini et al 2021).…”

Section: Vdn Model Parameterizationmentioning

confidence: 99%

“…This expression has the advantage to be based on a σ 8 -dependent bias, i.e., the product b eff σ 8 , which can be estimated directly via the modeling of the 2PCF. The linear parameterization reported in Equation (6) and equivalently the form of Equation ( 7) is effective also to encapsulate redshift-space distortions (Contarini et al 2022), i.e., the deformation of void shapes due to the peculiar velocities of tracers. Indeed, when estimating comoving distances from redshifts, the coherent outflow of tracers around the void center leads to larger observed void radii on average (Pisani et al 2015b).…”

Section: Vdn Model Parameterizationmentioning

confidence: 99%

“…With their large extent and unique low-density interior, voids indeed represent the ideal environment to study dark energy and modified gravity theories (Clampitt et al 2013;Spolyar et al 2013;Cai et al 2015;Hamaus et al 2015;Pisani et al 2015a;Zivick et al 2015;Achitouv 2016;Pollina et al 2016;Sahlén et al 2016;Falck et al 2018;Sahlén & Silk 2018;Paillas et al 2019;Perico et al 2019;Verza et al 2019;Contarini et al 2021Contarini et al , 2022, as well as models including massive neutrinos (Massara et al 2015;Banerjee & Dalal 2016;Kreisch et al 2019Kreisch et al , 2022Sahlén 2019;Schuster et al 2019;Contarini et al 2021), primordial non-Gaussianities (Chan et al 2019) and phenomena beyond the standard model of particle physics (e.g., Reed et al 2015;Yang et al 2015;Baldi & Villaescusa-Navarro 2018;Lester & Bolejko 2021;Arcari et al 2022).…”

Section: Introductionmentioning

confidence: 99%

“…This statistic is called the void size function. In recent years it has been explored in detail through cosmological simulations (e.g., Pisani et al 2015a;Pollina et al 2017;Contarini et al 2019Contarini et al , 2021Contarini et al , 2022Ronconi et al 2019;Verza et al 2019;Pelliciari et al 2023) and more rarely with real survey catalogs (Nadathur 2016;Sahlén et al 2016;Pollina et al 2019). Another fundamental and extensively studied void statistic is the void-galaxy crosscorrelation function, which represents an equivalent of the void density profile (Hamaus et al 2014b;Schuster et al 2023).…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, our goal is to measure and model the size function of BOSS DR12 voids to test the standard cosmological scenario. Since it offers cosmological constraints that are complementary to those of standard cosmological probes, this kind of analysis is extremely promising (Bayer et al 2021;Contarini et al 2022;Kreisch et al 2022;Pelliciari et al 2023). In particular, the negligible correlation between void counts and the main overdensity-based statistics (e.g., galaxy clustering and the halo mass function), together with the striking orthogonality of the corresponding growth of structure constraints (i.e., the Ω m -σ 8 confidence contours), has revealed the utmost importance of modeling the void size function, in the perspective of combining its achievements with those of other cosmological probes.…”

Section: Introductionmentioning

confidence: 99%

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Cosmological Constraints from the BOSS DR12 Void Size Function

Contarini,

Pisani,

Hamaus

et al. 2023

ApJ

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We present the first cosmological constraints derived from the analysis of the void size function. This work relies on the final Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) data set, a large spectroscopic galaxy catalog, ideal for the identification of cosmic voids. We extract a sample of voids from the distribution of galaxies, and we apply a cleaning procedure aimed at reaching high levels of purity and completeness. We model the void size function by means of an extension of the popular volume-conserving model, based on two additional nuisance parameters. Relying on mock catalogs specifically designed to reproduce the BOSS DR12 galaxy sample, we calibrate the extended size function model parameters and validate the methodology. We then apply a Bayesian analysis to constrain the Lambda cold dark matter (ΛCDM) model and one of its simplest extensions, featuring a constant dark energy equation of state parameter, w. Following a conservative approach, we put constraints on the total matter density parameter and the amplitude of density fluctuations, finding Ωm = 0.29 ± 0.06 and σ 8 = 0.79 − 0.08 + 0.09 . Testing the alternative scenario, we derive w = −1.1 ± 0.2, in agreement with the ΛCDM model. These results are independent and complementary to those derived from standard cosmological probes, opening up new ways to identify the origin of potential tensions in the current cosmological paradigm.

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Section: Vdn Model Parameterizationmentioning

confidence: 99%

Section: Vdn Model Parameterizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cosmological Constraints from the BOSS DR12 Void Size Function

Contarini,

Pisani,

Hamaus

et al. 2023

ApJ

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Euclid: Forecasts from the void-lensing cross-correlation

Bonici

Carbone

Davini

et al. 2023

A&A

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The Euclid space telescope will survey a large dataset of cosmic voids traced by dense samples of galaxies. In this work we estimate its expected performance when exploiting angular photometric void clustering, galaxy weak lensing, and their cross-correlation. To this aim, we implemented a Fisher matrix approach tailored for voids from the Euclid photometric dataset and we present the first forecasts on cosmological parameters that include the void-lensing correlation. We examined two different probe settings, pessimistic and optimistic, both for void clustering and galaxy lensing. We carried out forecast analyses in four model cosmologies, accounting for a varying total neutrino mass, M ν , and a dynamical dark energy (DE) equation of state, w(z), described by the popular Chevallier-Polarski-Linder parametrization. We find that void clustering constraints on h and Ω b are competitive with galaxy lensing alone, while errors on n s decrease thanks to the orthogonality of the two probes in the 2D-projected parameter space. We also note that, as a whole, with respect to assuming the two probes as independent, the inclusion of the void-lensing crosscorrelation signal improves parameter constraints by 10 − 15%, and enhances the joint void clustering and galaxy lensing figure of merit (FoM) by 10% and 25%, in the pessimistic and optimistic scenarios, respectively. Finally, when further combining with the spectroscopic galaxy clustering, assumed as an independent probe, we find that, in the most competitive case, the FoM increases by a factor of 4 with respect to the combination of weak lensing and spectroscopic galaxy clustering taken as independent probes. The forecasts presented in this work show that photometric void clustering and its cross-correlation with galaxy lensing deserve to be exploited in the data analysis of the Euclid galaxy survey and promise to improve its constraining power, especially on h, Ω b , the neutrino mass, and the DE evolution.

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Euclid: Cosmology forecasts from the void-galaxy cross-correlation function with reconstruction

Radinović¹,

Nadathur²,

Winther³

et al. 2023

A&A

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We have investigated the cosmological constraints that can be expected from measurement of the cross-correlation of galaxies with cosmic voids identified in the Euclid spectroscopic survey, which will include spectroscopic information for tens of millions of galaxies over 15 000 deg2 of the sky in the redshift range 0.9 ≤ z < 1.8. We have done this using simulated measurements obtained from the Flagship mock catalogue, the official Euclid mock that closely matches the expected properties of the spectroscopic dataset. To mitigate anisotropic selection-bias effects, we have used a velocity field reconstruction method to remove large-scale redshift-space distortions from the galaxy field before void-finding. This allowed us to accurately model contributions to the observed anisotropy of the cross-correlation function arising from galaxy velocities around voids as well as from the Alcock–Paczynski effect, and we studied the dependence of constraints on the efficiency of reconstruction. We find that Euclid voids will be able to constrain the ratio of the transverse comoving distance DM and Hubble distance DH to a relative precision of about 0.3%, and the growth rate fσ8 to a precision of between 5% and 8% in each of the four redshift bins covering the full redshift range. In the standard cosmological model, this translates to a statistical uncertainty ΔΩm = ±0.0028 on the matter density parameter from voids, which is better than what can be achieved from either Euclid galaxy clustering and weak lensing individually. We also find that voids alone can measure the dark energy equation of state to a 6% precision.

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Euclid: Cosmological forecasts from the void size function

Cited by 13 publications

References 189 publications

Cosmological Constraints from the BOSS DR12 Void Size Function

Cosmological Constraints from the BOSS DR12 Void Size Function

Euclid: Forecasts from the void-lensing cross-correlation

Euclid: Cosmology forecasts from the void-galaxy cross-correlation function with reconstruction

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