Libraries to analyze numerical simulations (python3)
Forward modelling for gravity anomalies
Algorithm for Void Identification in Cosmology is a comprehensive and significant update to a previous void finder published by Ricciardelli et al. (2013). Density and velocity divergence are used to define 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.
AI optimization of void property workflow. Contractor scheduling, progress tracking, void loss reduction. Integrates with HMS and repairs.
Julia implementation of the DIVE algorithm for finding voids in a point set with applications in observational cosmology.
Add a description, image, and links to the voids topic page so that developers can more easily learn about it.
To associate your repository with the voids topic, visit your repo's landing page and select "manage topics."