pytket-qsharp 0.29.0

Extension for pytket, providing access to Azure devices and simulators via Microsoft QDK

Pytket Extensions

This repository contains the pytket-qsharp extension, using Quantinuum's pytket quantum SDK.

pytket-qsharp

Pytket is a python module for interfacing with tket, a quantum computing toolkit and optimisation compiler developed by Quantinuum.

Azure Quantum is a portal for accessing quantum computers via Microsoft Azure.

Microsoft's QDK is a language and associated toolkit for quantum programming.

pytket-qsharp is an extension to pytket that allows pytket circuits to be executed on remote devices and simulators via Azure Quantum, as well as local simulators and resource estimators from the Microsoft QDK.

Backends provided in this module

This module provides four backends, all deriving from the pytket Backend class:

• AzureBackend, for executing pytket circuits on targets the user has access to on Azure Quantum;

• QsharpSimulatorBackend, for simulating a general pure-quantum circuit using the QDK;

• QsharpToffoliSimulatorBackend, for simulating a Toffoli circuit using the QDK;

• QsharpEstimatorBackend, for estimating various quantum resources of a circuit using the QDK. This provides a get_resources method, which returns a dictionary.

Getting started

pytket-qsharp is available for Python 3.8, 3.9 and 3.10, on Linux, MacOS and Windows. To install, run:

pip install pytket-qsharp

This will install pytket if it isn't already installed, and add new classes and methods into the pytket.extensions namespace.

In order to use pytket-qsharp you will first need to install the dotnet SDK (6.0) and the iqsharp tool. On some Linux systems it is also necessary to modify your PATH:

1. See this page for instructions on installing the SDK on your operating system.

2. On Linux, ensure that the dotnet tools directory is on your path. Typically this will be ~/.dotnet/tools.

3. Run dotnet tool install -g Microsoft.Quantum.IQSharp.

4. Run dotnet iqsharp install --user.

Alternatively, you can set up an environment with all the required packages using conda:

conda create -n qsharp-env -c quantum-engineering qsharp notebook

conda activate qsharp-env

Bugs, support and feature requests

Please file bugs and feature requests on the Github issue tracker.

There is also a Slack channel for discussion and support. Click here to join.

Development

To install an extension in editable mode, simply change to its subdirectory within the modules directory, and run:

pip install -e .

Contributing

Pull requests are welcome. To make a PR, first fork the repo, make your proposed changes on the develop branch, and open a PR from your fork. If it passes tests and is accepted after review, it will be merged in.

Code style

Formatting

All code should be formatted using black, with default options. This is checked on the CI. The CI is currently using version 20.8b1.

Type annotation

On the CI, mypy is used as a static type checker and all submissions must pass its checks. You should therefore run mypy locally on any changed files before submitting a PR. Because of the way extension modules embed themselves into the pytket namespace this is a little complicated, but it should be sufficient to run the script modules/mypy-check (passing as a single argument the root directory of the module to test). The script requires mypy 0.800 or above.

Linting

We use pylint on the CI to check compliance with a set of style requirements (listed in .pylintrc). You should run pylint over any changed files before submitting a PR, to catch any issues.

Tests

To run the tests for a module:

1. cd into that module's tests directory;
2. ensure you have installed pytest, hypothesis, and any modules listed in the test-requirements.txt file (all via pip);
3. run pytest.

When adding a new feature, please add a test for it. When fixing a bug, please add a test that demonstrates the fix.