Libraries to analyze numerical simulations (python3)
Forward modelling for gravity anomalies
Algorithm for Void Identification in Cosmology (https://arxiv.org/abs/2509.25329) is a comprehensive and significant update to a previous void finder published by Ricciardelli et al. (2013). It utilises density and velocity divergence data on a uniform grid to construct unstructured voids, which are formed by combining a set of cubes
The algorithm identifies clusters and gaps in integer datasets, calculates their Z-scores based on mean density and distance, and outputs the results as JSON.
Julia implementation of the DIVE algorithm for finding voids in a point set with applications in observational cosmology.
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