AVISM: Algorithm for Void Identification in coSMology

¹ Departament d’Astronomia i Astrofísica, Universitat de València, 46100 Burjassot (València), Spain
² Dipartimento di Fisica e Astronomia, Università di Bologna, Via Gobetti 93/2, 40129 Bologna, Italy
³ Observatori Astronòmic, Universitat de València, 46980 Paterna (València), Spain

^★ Corresponding author: oscar.monllor@uv.es

Received: 13 March 2025
Accepted: 26 September 2025

Abstract

Context. Cosmic voids are key elements in our understanding of the large-scale structure of the Universe. They are crucial for constraining cosmological parameters, understanding the structure formation, and evolution of our Universe, and they could also serve as pristine laboratories for studying galaxy formation without all the hassle due to environmental effects. Thus, the ability to accurately and consistently identify voids, both in numerical simulations and in observations, is essential.

Aims. We present the Algorithm for Void Identification in coSMology (AVISM), a new void finder for analysing both cosmological simulation outputs and observational galaxy catalogues. In the first case, the code handles raw particle or cell data, dark matter haloes, and synthetic galaxy catalogues. For observational data, the code should be coupled with external tools that provide the required dynamical information to apply the algorithm. This new numerical tool is efficient in terms of computational resources, both wall time and memory.

Methods. A set of numerical tests designed to assess the code’s capabilities were carried out, including parameter robustness, computational performance, and the use of different matter components in a cosmological simulation. AVISM’s performance was also compared, both statistically and on a one-to-one basis, with the state-of-the-art void finders DIVE and ZOBOV using a dark matter halo catalogue from a large-volume cosmological simulation. An application to a galaxy survey is also provided to demonstrate the code’s ability to handle real data.

Results. We designed a new void finder algorithm that combines geometrical and dynamical information to identify void regions and a hierarchical merging process to reconstruct the entire 3D structure of the void. The outcome of this process is a void catalogue with complex boundaries without assuming a prior shape. This process can be repeated at different levels of resolution using finer grids, leading to a list of voids-in-voids and a proper description of void substructure.

Conclusions. We present and release AVISM, a new publicly available void finder.