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https://github.com/learningmatter-mit/Segal
https://github.com/learningmatter-mit/Segal
Last synced: 27 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/learningmatter-mit/Segal
- Owner: learningmatter-mit
- License: mit
- Created: 2021-07-01T00:57:34.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-16T23:06:02.000Z (3 months ago)
- Last Synced: 2024-04-16T03:56:29.799Z (2 months ago)
- Language: Jupyter Notebook
- Size: 8.97 MB
- Stars: 8
- Watchers: 4
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Lists
- awesome-stars - learningmatter-mit/Segal - (Jupyter Notebook)
README
This is a repository of SEGAL, a method to study Monte Carlo simulations in the semi-grand canonical ensemble with machine learning.
Updated work can be found in the revision submission folder.
Published article: https://www.nature.com/articles/s41524-022-00736-4
Examples were run in the environment defined by [environment.yml](environment.yml) file and `conda`:
```
conda env create -f environment.yml
conda activate segal
```