Cosmology with cosmic web environments

I. Real-space power spectra

¹ Université Paris-Saclay, CNRS, Institut d’Astrophysique Spatiale, 91405 Orsay, France
e-mail: tony.bonnaire@universite-paris-saclay.fr
² Université Paris-Saclay, TAU team INRIA Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, 91190 Gif-sur-Yvette, France
³ Laboratoire de Physique de l’École normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France
⁴ Departamento de Física Téorica I, Universidad Complutense, 28040 Madrid, Spain

Received: 7 December 2021
Accepted: 19 February 2022

Abstract

We undertake the first comprehensive and quantitative real-space analysis of the cosmological information content in the environments of the cosmic web (voids, filaments, walls, and nodes) up to non-linear scales, k = 0.5 h Mpc⁻¹. Relying on the large set of N-body simulations from the Quijote suite, the environments are defined through the eigenvalues of the tidal tensor and the Fisher formalism is used to assess the constraining power of the spectra derived in each of the four environments and their combination. Our results show that there is more information available in the environment-dependent power spectra – both individually and when combined – than in the matter power spectrum. By breaking some key degeneracies between parameters of the cosmological model such as M_ν–σ₈ or Ω_m–σ₈, the power spectra computed in identified environments improve the constraints on cosmological parameters by factors of ∼15 for the summed neutrino mass M_ν and ∼8 for the matter density Ω_m over those derived from the matter power spectrum. We show that these tighter constraints are obtained for a wide range of the maximum scale, from k_max = 0.1 h Mpc⁻¹ to highly non-linear regimes with k_max = 0.5 h Mpc⁻¹. We also report an eight times higher value of the signal-to-noise ratio for the combination of environment-dependent power spectra than for the matter spectrum. Importantly, we show that all the results presented here are robust to variations of the parameters defining the environments, suggesting a robustness to the definition we chose to extract them.