Skip to main content

For on-the-fly active learning of interatomic potentials.

Project description

Carcará logo

License: MIT PyPI

Carcará

Carcará is a high-performance Python framework designed for atomistic simulations powered by on-the-fly (OTF) machine learning interatomic potentials. It streamlines the integration of first-principles accuracy with the efficiency of classical force fields, enabling the automated development of robust potentials during the simulation process.

Installation

From pip

The easiest way to install Carcará is with pip:

pip install carcara

From github

To install Carcará directly from the GitHub repository, run the following commands:

pip install git+https://github.com/seixas-research/carcara.git

Getting started

License

This is an open source code under MIT License.

Acknowledgements

We thank financial support from INCT Materials Informatics (Grant No. 406447/2022-5), and CNPq (Grant No. 311324/2020-7).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

carcara-26.4.23.tar.gz (22.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

carcara-26.4.23-py3-none-any.whl (22.8 kB view details)

Uploaded Python 3

File details

Details for the file carcara-26.4.23.tar.gz.

File metadata

  • Download URL: carcara-26.4.23.tar.gz
  • Upload date:
  • Size: 22.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for carcara-26.4.23.tar.gz
Algorithm Hash digest
SHA256 57f82efeffd7dd46711b8bbfa8b8e7e0d0ca81f2485462aa5656e761d6f33a03
MD5 5b37cbde8dfb7c5e261432453600f629
BLAKE2b-256 fed07e1c9dd36e4fd308d0d1d7567935e000ec1955267a29685ff9dc58e20dc5

See more details on using hashes here.

File details

Details for the file carcara-26.4.23-py3-none-any.whl.

File metadata

  • Download URL: carcara-26.4.23-py3-none-any.whl
  • Upload date:
  • Size: 22.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for carcara-26.4.23-py3-none-any.whl
Algorithm Hash digest
SHA256 2e11d0c7e7a459d317c669aceaeb2dba17ea0a4c53d744b72885e281ebba853f
MD5 bd026d8e9af4dc04e2795d4aef3413c5
BLAKE2b-256 5024dbdfe9cdb5221bc7e8ad67b96ccedbc24a16358edac77aa6abae3c9b5d46

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page