AVISM: Algorithm for Void Identification in coSMology

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.

Authors

Institutions

Publication Details

Journal
Astronomy and Astrophysics
Published
2025-10-15
DOI
https://doi.org/10.1051/0004-6361/202554513
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AVISM: Algorithm for Void Identification in coSMology

Susana Planelles, David Vallés-Pérez, Vicent Quilis, Óscar Monllor-Berbegal
Astronomy and Astrophysics
Power Systems and Technologies
article

AVISM: Algorithm for Void Identification in coSMology

Susana Planelles, David Vallés-Pérez, Vicent Quilis, Óscar Monllor-Berbegal
article en

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.

Astronomy and AstrophysicsVol. 704
Universitat de València (ES), Osservatorio astronomico di Bologna (IT), University of Bologna (IT)
Openalex Percentile: Top 71%
Power Systems and Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.