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.

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.

Metadata

Release files for pyqtorch 1.7.8

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyqtorch 1.7.8
File	Size	Uploaded
pyqtorch-1.7.8.tar.gz	122.0 kB	Jun 17, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for pyqtorch 1.7.8
File	Interpreter	ABI	Platform	Reset
pyqtorch-1.7.8-py3-none-any.whl 86.0 kB Jun 17, 2025	Python 3	none	any	Details

Total release size: 208.0 kB

Release files / pyqtorch-1.7.8.tar.gz

Download URL	pyqtorch-1.7.8.tar.gz
Size	122.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`f4e2fca3e58a33e05da77b7ffef42a4d332235308a99b371acb45755d1c87301`
BLAKE2b-256 checksum How to use checksums	`bed26c5cbdca91d9ad1fa60845e52383cf5c46354bccf1dfedd3336cfe206f0b`
Upload date	Jun 17, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/pasqal-io/pyqtorch
Publishing commit: github.com/pasqal-io/pyqtorch/tree/42b8a84e6c4103c37841624afad44c46caaf4e4a

Workflow

Publishing configuration: github.com/pasqal-io/pyqtorch/blob/42b8a84e6c4103c37841624afad44c46caaf4e4a/.github/workflows/test.yml
Publishing logs: github.com/pasqal-io/pyqtorch/actions/runs/15707374426/attempts/2

Artifact

Subject: pyqtorch-1.7.8.tar.gz
SHA-256 checksum: f4e2fca3e58a33e05da77b7ffef42a4d332235308a99b371acb45755d1c87301 Verifying attestations

Release files / pyqtorch-1.7.8-py3-none-any.whl

Download URL	pyqtorch-1.7.8-py3-none-any.whl
Size	86.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`be4522e230004d08ba483a72ef25f7e375bbffedfcd97a040ecf5f0b7b100ad6`
BLAKE2b-256 checksum How to use checksums	`8ebdb5887048004a5ee6b9a20e06e990a5a6b0ae4b010ecb4362932ba1787049`
Upload date	Jun 17, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.12.9`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/pasqal-io/pyqtorch
Publishing commit: github.com/pasqal-io/pyqtorch/tree/42b8a84e6c4103c37841624afad44c46caaf4e4a

Workflow

Publishing configuration: github.com/pasqal-io/pyqtorch/blob/42b8a84e6c4103c37841624afad44c46caaf4e4a/.github/workflows/test.yml
Publishing logs: github.com/pasqal-io/pyqtorch/actions/runs/15707374426/attempts/2

Artifact

Subject: pyqtorch-1.7.8-py3-none-any.whl
SHA-256 checksum: be4522e230004d08ba483a72ef25f7e375bbffedfcd97a040ecf5f0b7b100ad6 Verifying attestations