Skip to main content

An efficient, large-scale emulator designed for quantum machine learning, seamlessly integrated with a PyTorch backend. Please refer to https://pyqtorch.readthedocs.io/en/latest/ for setup and usage info, along with the full documentation.

Project description

pyqtorch

pyqtorch is a PyTorch-based state vector simulator designed for quantum machine learning. It acts as the main backend for Qadence, a digital-analog quantum programming interface. pyqtorch allows for writing fully differentiable quantum programs using both digital and analog operations; enabled via a intuitive, torch-based syntax.

Linting / Tests/ Documentation License Pypi Coverage

Installation guide

pyqtorch can be installed from PyPI with pip as follows:

pip install pyqtorch

Install from source

We recommend to use the hatch environment manager to install pyqtorch from source:

python -m pip install hatch

# get into a shell with all the dependencies
python -m hatch shell

# run a command within the virtual environment with all the dependencies
python -m hatch run python my_script.py

Please note that hatch will not combine nicely with other environment managers such Conda. If you want to use Conda, install pyqtorch from source using pip:

# within the Conda environment
python -m pip install -e .

Contributing

Please refer to CONTRIBUTING to learn how to contribute to pyqtorch.

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

pyqtorch-1.7.1.tar.gz (103.4 kB view details)

Uploaded Source

Built Distribution

pyqtorch-1.7.1-py3-none-any.whl (78.9 kB view details)

Uploaded Python 3

File details

Details for the file pyqtorch-1.7.1.tar.gz.

File metadata

  • Download URL: pyqtorch-1.7.1.tar.gz
  • Upload date:
  • Size: 103.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for pyqtorch-1.7.1.tar.gz
Algorithm Hash digest
SHA256 c2849e333c9adda20733c7ea265a27f1fb48d98d814a40508c4f99bcfd5bf4aa
MD5 73809eda5e109b5b339d8383b34c6b09
BLAKE2b-256 02531d829e2a245919d97fe74b9e14e7b517d3ad01f0a147e7bedecc7a82ee4d

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyqtorch-1.7.1.tar.gz:

Publisher: test.yml on pasqal-io/pyqtorch

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pyqtorch-1.7.1-py3-none-any.whl.

File metadata

  • Download URL: pyqtorch-1.7.1-py3-none-any.whl
  • Upload date:
  • Size: 78.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for pyqtorch-1.7.1-py3-none-any.whl
Algorithm Hash digest
SHA256 36cff067ae629fccc36cce88561e70cb3d07db627bbe468bebbf84db67e13fb4
MD5 41efc04f6ad4a1924782d444cc554699
BLAKE2b-256 a3f9ed1eb1e415d80071122e6b1e0b0cf11d41859dc0cf7b1beb6495f1412175

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyqtorch-1.7.1-py3-none-any.whl:

Publisher: test.yml on pasqal-io/pyqtorch

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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