Skip to main content

Coupled cluster calculations on electron-boson systems

Project description

ebcc: Coupled cluster calculations on electron-boson systems

CI codecov PyPI version License: MIT

The ebcc package implements various coupled cluster (CC) models for both purely electronic and coupled electron-boson models, with a focus on generality and model extensibility.

For a summary of the implemented models, see the FEATURES.md file.

Installation

From PyPI:

pip install ebcc

From source:

git clone https://github.com/BoothGroup/ebcc
pip install .

Usage

The implemented models are built upon the mean-field objects of pyscf:

from pyscf import gto, scf
from ebcc import EBCC
mol = gto.M(atom="H 0 0 0; H 0 0 1", basis="cc-pvdz")
mf = scf.RHF(mol)
mf.kernel()
ccsd = EBCC(mf, ansatz="CCSD")
ccsd.kernel()

Many ansatzes for both fermionic and electron-boson coupled cluster calculations are available. For more details see the tutorials and examples directories.

Backends

By default, the tensor backend uses numpy for all array classes and contraction routines. A number of alternative backends are supported, offering varied frameworks such as parallelism, GPU acceleration, and automatic differentation. For more details, see the corresponding tutorial.

Additionally, mixed precision calculations are supported, which is also detailed in the following tutorial.

Code generation

The models implemented are generated algorithmically from expressions over second quantized operators. The scripts for generating these models are found in the codegen directory on the bootstrap branch. User-inputted models should operate seamlessly with the solvers by adding files under ebcc/codegen, so long as they satisfy the interface.

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

ebcc-1.6.2.tar.gz (807.7 kB view details)

Uploaded Source

Built Distribution

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

ebcc-1.6.2-py3-none-any.whl (886.6 kB view details)

Uploaded Python 3

File details

Details for the file ebcc-1.6.2.tar.gz.

File metadata

  • Download URL: ebcc-1.6.2.tar.gz
  • Upload date:
  • Size: 807.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ebcc-1.6.2.tar.gz
Algorithm Hash digest
SHA256 03e6b6359961db4f00eef6c911444b9ca37ca9974baecb20d75d785ec2eb5cb0
MD5 ed1c0e7188ed82f84e4c5b212c368639
BLAKE2b-256 74663a08475a37c5b2345d95f4b4f036b1e7f58e50fab2935d1a13026a888f9c

See more details on using hashes here.

File details

Details for the file ebcc-1.6.2-py3-none-any.whl.

File metadata

  • Download URL: ebcc-1.6.2-py3-none-any.whl
  • Upload date:
  • Size: 886.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ebcc-1.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 4d08e843eeba7470e0409eb37c06fb1f33e51254c281411213f0e90e8b037afa
MD5 9dfc82f9c617c5c07d5708eede325041
BLAKE2b-256 6157537925c2082aba524c252cdb3814e18b8d1f7c70545e3d90b8235c3ba335

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