QUICHE

QUICHE (QUantum Integrated CHEmistry) is a toolkit for studying quantum computing algorithms for quantum chemistry, with a focus on quantum phase estimation (QPE). It integrates a resource estimation backend based on Qualtran, with a QuEST-powered simulation backend. The two backends can be used in isolation or combined using the Python package capable of dispatching between the two.

⚠️ This project is in early active development and should not be considered production-ready. Breaking changes may occur without notice before v1.0.

Features

  • Range of quantum phase estimation algorithms including various single- and multi-ancilla methods.
  • Wide variety of Hamiltonian simulation techniques, such as Suzuki-Trotter, QDRIFT and qubitisation.
  • Extensible, Python-based resource estimation tooling.
  • High-performance simulation capabilities.

Installation

QUICHE is available on PyPI as pyquiche. For a basic install, execute

pip install pyquiche

Then import the package from Python

import quiche

Prebuilt wheels are available for Linux (x86_64, aarch64), macOS 15+ (arm64) and Windows (x64), on Python 3.12 or later. They bundle a multithreaded, double precision build of QuEST. On other platforms pip falls back to building from source. That is also needed for custom precision, GPU acceleration or MPI-enabled builds.

Building from source

Building from source compiles the C++ simulation backend locally. This requires CMake, a C++17 compiler and network access to fetch dependencies. MPI- and GPU-enabled builds additionally require the corresponding toolchains, which are not fetched automatically.

The simulation backend depends on:

  • QuEST for simulation. Always built from a pinned source archive, since QUICHE depends on internal headers that are not part of the installed interface.
  • nanobind for Python bindings. Toggled with QUICHE_BUILD_BINDINGS.
  • Catch2 for testing. Toggled with QUICHE_BUILD_TESTS.

nanobind and Catch2 are located with find_package and downloaded via FetchContent if unavailable.

To build the Python package from the published sdist, passing configuration flags through to CMake:

pip install pyquiche --no-binary pyquiche -C cmake.define.ENABLE_DISTRIBUTION=ON

Note: --no-binary is required: without it pip installs the prebuilt wheel and the configuration flags are ignored.

Or to build from a checkout

git clone https://github.com/Quantum-Motion/quiche.git
cd quiche
pip install .

C++ backend only

To build only the C++ simulator backend, along with the examples, execute

cd quiche
cmake -B build -D QUICHE_BUILD_EXAMPLES=ON
cmake --build build

Then execute an example (e.g. the Textbook QPE example)

./build/cpp/examples/qpe-textbook

Other C++ configuration flags can be similarly toggled ON and OFF. See also the QuEST docs for the available simulation flags.

Usage

For Python usage examples see the python/examples directory. For C++ simulator usage examples see the cpp/examples directory.

Contributing

For further information about how you can contribute to QUICHE see the contributing guide.

License

Copyright 2026 Quantum Motion Technologies Ltd. Licensed under the Apache License, Version 2.0.

Funding

This software is supported by Innovate UK and Germany's ZIM via the QUantum-Integrated CHEmistry (QUICHE) project.

Project links

Data verified by PyPI on Sep 13, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

2 maintainers

PyPI data
Data sourced directly from PyPI's database.
Avatar for tom-quantummotion from gravatar.com tom-quantummotion Avatar for vaferreiQMT from gravatar.com vaferreiQMT

Credits

Author: Thomas Bromley

GitHub Statistics

Data verified by PyPI on Sep 13, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0
View SPDX License List

Requires

Python <4.0, >=3.12

Tags

quantum computing quantum chemistry quantum phase estimation QPE resource estimation quantum simulation

Classifiers

Report project as malware

Download files

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

Source Distribution

pyquiche-0.1.0.tar.gz (431.6 kB view details)

Uploaded Source

Built Distributions

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

pyquiche-0.1.0-cp312-abi3-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.12+Windows x86-64

pyquiche-0.1.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

pyquiche-0.1.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl (2.4 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.26+ ARM64manylinux: glibc 2.28+ ARM64

pyquiche-0.1.0-cp312-abi3-macosx_15_0_arm64.whl (2.4 MB view details)

Uploaded CPython 3.12+macOS 15.0+ ARM64

File details

Details for the file pyquiche-0.1.0.tar.gz.

File metadata

  • Download URL: pyquiche-0.1.0.tar.gz
  • Upload date:
  • Size: 431.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for pyquiche-0.1.0.tar.gz
Algorithm Hash digest
SHA256 5e051ee5a161d2c7cfb7d63977a69982fdf02df167c877266ea65c6d8c61320e
MD5 d875fb0c28c073e13511a806de02ab9a
BLAKE2b-256 246bb2962e43b0f2f4b7f460a56e21384fd42258f3cda014c954f52bd757f8a9

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyquiche-0.1.0.tar.gz:

Publisher: publish-wheels.yml on Quantum-Motion/quiche

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

File details

Details for the file pyquiche-0.1.0-cp312-abi3-win_amd64.whl.

File metadata

  • Download URL: pyquiche-0.1.0-cp312-abi3-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.12+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for pyquiche-0.1.0-cp312-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 520a1f414d91fce2534b9fcf2f42a8565952b843ebf37fd06f384c1fdcc86a2e
MD5 00a21d1beb37ceb92b430a1daa9c9997
BLAKE2b-256 2526bfa572ac8e039856f440cc087978e16715c36449b0d1a9c66f132584be47

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyquiche-0.1.0-cp312-abi3-win_amd64.whl:

Publisher: publish-wheels.yml on Quantum-Motion/quiche

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

File details

Details for the file pyquiche-0.1.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyquiche-0.1.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7dd9a31a7568ca04ad6fd9cd6e7a303ab3ce88fbc93789163303073150b0edff
MD5 780fa2e9a264eb58d5567cc7edc402df
BLAKE2b-256 4872bcd584bb5cc9ceec8e19bd91fb54f619dcfbdb322a44f6a97b512577971a

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyquiche-0.1.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl:

Publisher: publish-wheels.yml on Quantum-Motion/quiche

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

File details

Details for the file pyquiche-0.1.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pyquiche-0.1.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 9c28cf3046444512b2a3b177ff0c366e4b0b5cc6e7d1736e591d9b81777362d5
MD5 d9c46653390391c4c03b2caee88cbdb5
BLAKE2b-256 2e25debea3b90ddd49b78d785b4e0e0969eedbf9b726e45533d7e55417e6e0b9

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyquiche-0.1.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl:

Publisher: publish-wheels.yml on Quantum-Motion/quiche

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

File details

Details for the file pyquiche-0.1.0-cp312-abi3-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyquiche-0.1.0-cp312-abi3-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 4fdaacb9ad00de47cb2ea604f726c65c90f4e61d15a02b3493dd7cf5d2f29c9e
MD5 79599fc18dafb9670dbaafc84bdf1b66
BLAKE2b-256 062e679ac865b094bf34882d84fb403e86b4cc2ce9844546148eec2603f98305

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyquiche-0.1.0-cp312-abi3-macosx_15_0_arm64.whl:

Publisher: publish-wheels.yml on Quantum-Motion/quiche

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

Release history Release notifications | RSS feed

This release

0.1.0 This release

5 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page