Skip to main content

Approximate quantum compilation with tensor networks

Project description

Release Platform Python Qiskit
Docs (stable) License Downloads Tests Coverage

Qiskit addon: approximate quantum compilation with tensor networks (AQC-Tensor)

Table of contents


About

Qiskit addons are a collection of modular tools for building utility-scale workloads powered by Qiskit.

This addon enables a Qiskit user to perform approximate quantum compilation using tensor networks, a technique that was introduced in arXiv:2301.08609.

Specifically, this package allows one to compile the initial portion of a circuit into a nearly equivalent approximation of that circuit, but with much fewer layers.

It has been tested primarily on Trotter circuits to date. It may, however, be applicable to any class of circuits where one has access to both:

  1. A great intermediate state, known as the "target state," that can be achieved by tensor-network simulation; and,
  2. A good circuit that prepares an approximation to the target state, but with fewer layers when compiled to the target hardware device.

Compression of initial portion of circuit with AQC

(Figure is taken from arXiv:2301.08609.)


Documentation

All documentation is available at https://qiskit.github.io/qiskit-addon-aqc-tensor/.


Installation

We encourage installing this package via pip, when possible.

To be useful, this package requires at least one tensor-network backend. The following command installs the Qiskit Aer backend, as well as the quimb backend with automatic differentiation support from JAX:

pip install 'qiskit-addon-aqc-tensor[aer,quimb-jax]'

For more installation information refer to these installation instructions.


Deprecation Policy

We follow semantic versioning and are guided by the principles in Qiskit's deprecation policy. We may occasionally make breaking changes in order to improve the user experience. When possible, we will keep old interfaces and mark them as deprecated, as long as they can co-exist with the new ones. Each substantial improvement, breaking change, or deprecation will be documented in the release notes.


Contributing

The source code is available on GitHub.

The developer guide is located at CONTRIBUTING.md in the root of this project's repository. By participating, you are expected to uphold Qiskit's code of conduct.

We use GitHub issues for tracking requests and bugs.


Citation

If you use this package in your research, please cite it according to the CITATION.bib file.


License

Apache License 2.0

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

qiskit_addon_aqc_tensor-0.2.0.tar.gz (993.2 kB view details)

Uploaded Source

Built Distribution

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

qiskit_addon_aqc_tensor-0.2.0-py3-none-any.whl (40.3 kB view details)

Uploaded Python 3

File details

Details for the file qiskit_addon_aqc_tensor-0.2.0.tar.gz.

File metadata

  • Download URL: qiskit_addon_aqc_tensor-0.2.0.tar.gz
  • Upload date:
  • Size: 993.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for qiskit_addon_aqc_tensor-0.2.0.tar.gz
Algorithm Hash digest
SHA256 f1e38ecf76f7302b062935a237408fb076a0c06b37b417afadd30742b81c69cd
MD5 bb6a69a9187e977b9df061df76f9718a
BLAKE2b-256 018c858ebf4c3006c6399d0e24c8f52eb3735530c45db8c4f3b4cf8bb40294ac

See more details on using hashes here.

Provenance

The following attestation bundles were made for qiskit_addon_aqc_tensor-0.2.0.tar.gz:

Publisher: release.yml on Qiskit/qiskit-addon-aqc-tensor

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

File details

Details for the file qiskit_addon_aqc_tensor-0.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for qiskit_addon_aqc_tensor-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 3cbda9638d7893a5effbf8085df4bf7cba451d0177a135df7122d1d484fb9db0
MD5 eb82682f03260a6e04cd9a7b6b997ab7
BLAKE2b-256 cd8973943738eeb9335d551b44a2f7d5345dfb1fc377fc0507562f6712fba00b

See more details on using hashes here.

Provenance

The following attestation bundles were made for qiskit_addon_aqc_tensor-0.2.0-py3-none-any.whl:

Publisher: release.yml on Qiskit/qiskit-addon-aqc-tensor

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 Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page