https://github.com/boothgroup/gpsket

GPS plugin for NetKet (www.netket.org), introducing new models, optimizers and Fermionic functionality.

https://github.com/boothgroup/gpsket

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    2 of 4 committers (50.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.3%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

GPS plugin for NetKet (www.netket.org), introducing new models, optimizers and Fermionic functionality.

Basic Info
  • Host: GitHub
  • Owner: BoothGroup
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 479 KB
Statistics
  • Stars: 18
  • Watchers: 3
  • Forks: 3
  • Open Issues: 0
  • Releases: 0
Created over 4 years ago · Last pushed 10 months ago
Metadata Files
Readme

README.md

GPSKet

This is a plugin for NetKet (www.netket.org), extending it by additional functionality (mostly not yet available in the core code). We mostly understand this codebase a playground to test out new ideas and approaches, especially around the Gaussian Process State (GPS) ansatz for many-body systems. As such, the code is not tested to the high standards of released software. Different parts of the code might be merged into the NetKet code in the future.

Functionality implemented in this plugin includes: - GPS ansatz (including an autoregressive extension) - Fermionic mean-field ansatzes (Slater determinants, Pfaffians) - Backflow wavefunctions - On-the-fly evaluations of local energies for different Hamiltonians - Fast model updating (some models) for scaling improvements in the local energy evaluations (and sampling via the Metropolis-Hastings algorithm) - Efficient ab-initio Hamiltonians - Supervised learning of GPS within Bayesian frameworks

The code is, at this stage, largely undocumented, but different example applications can be found in the tutorials folder. Further documentation and additional examples will be provided in the near future.

Owner

  • Name: BoothGroup
  • Login: BoothGroup
  • Kind: organization

GitHub Events

Total
  • Watch event: 4
  • Delete event: 1
  • Push event: 13
  • Fork event: 1
  • Create event: 1
Last Year
  • Watch event: 4
  • Delete event: 1
  • Push event: 13
  • Fork event: 1
  • Create event: 1

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 359
  • Total Committers: 4
  • Avg Commits per committer: 89.75
  • Development Distribution Score (DDS): 0.362
Past Year
  • Commits: 15
  • Committers: 1
  • Avg Commits per committer: 15.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Yannic Rath y****h@k****k 229
Massimo Bortone m****e@k****k 119
Yannic Rath 4****a 6
Filippo Vicentini f****i@g****m 5
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 3
  • Total pull requests: 2
  • Average time to close issues: 3 months
  • Average time to close pull requests: 20 days
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 1.67
  • Average comments per pull request: 1.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • PhilipVinc (2)
  • maxbortone (1)
Pull Request Authors
  • PhilipVinc (2)
Top Labels
Issue Labels
bug (1)
Pull Request Labels