Tracing cosmic voids with fast simulations

¹ Dipartimento di Fisica, Sezione di Astronomia, Università di Trieste, Via Tiepolo 11, I-34143 Trieste, Italy
² INAF – Osservatorio Astronomico di Trieste, via Tiepolo 11, I-34131 Trieste, Italy
³ ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data e Quantum Computing/Spoke 3, Astrophysics and Cosmos Observations, Via Magnanelli 2, Bologna, Italy
⁴ University Observatory, LMU Faculty of Physics, Scheinerstr. 1, 81679 Munich, Germany
⁵ Aix-Marseille Université, CNRS/IN2P3, CPPM, Marseille, France
⁶ INFN – Sezione di Trieste, I-34100 Trieste, Italy
⁷ IFPU – Institute for Fundamental Physics of the Universe, via Beirut 2, 34151 Trieste, Italy

^⋆ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 24 June 2025
Accepted: 6 October 2025

Abstract

Context. Cosmic voids are vast underdense regions in the cosmic web that encode crucial information about structure formation, the composition of the Universe, and its expansion history. Due to their lower density, these regions are less affected by non-linear gravitational dynamics, making them suitable candidates for analysis using semi-analytic methods.

Aims. We assess the accuracy of the PINOCCHIO code, a fast tool for generating dark matter halo catalogs based on Lagrangian perturbation theory, in modeling the statistical properties of cosmic voids. We validate this approach by comparing the resulting void statistics measured from PINOCCHIO to those obtained from N-body simulations.

Methods. We generate a set of simulations using PINOCCHIO and OpenGADGET3, assuming a fiducial cosmology and varying the resolution. For a given resolution, the simulations share the same initial conditions between the two codes. Snapshots are saved at multiple redshifts and post-processed using the watershed void finder VIDE to identify cosmic voids. For each simulation, we measure the following statistics: void size function, void ellipticity function, core density function, and the void radial density profile. We use these statistics to quantify the accuracy of PINOCCHIO relative to OpenGADGET3 in the context of cosmic voids.

Results. We find agreement for all void statistics at better than 2σ between PINOCCHIO and OpenGADGET3, with no systematic difference in redshift trends. This demonstrates that the PINOCCHIO code can reliably produce void statistics with high computational efficiency compared to full N-body simulations.