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z-quantum-core

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What is it?

z-quantum-core is a core library of the scientific code for Orquestra – the platform developed by Zapata Computing for performing computations on quantum computers.

z-quantum-core provides:

  • core functionalities required to run other Orquestra modules, such as the Circuit class.
  • interfaces for implementing other Orquestra modules, such as backends and optimizers.
  • useful tools to support the development of workflows and other scientific projects; such as time evolution, sampling from probability distribution, etc.

Usage

Workflow

In order to use z-quantum-core in your workflow, you need to add it as an import in your Orquestra workflow:

imports:
  - name: z-quantum-core
    type: git
    parameters:
      repository: "[email protected]:zapatacomputing/z-quantum-core.git"
      branch: "master"

and then add it in the imports argument of your step:

- name: my-step
  config:
    runtime:
      language: python3
      imports: [z-quantum-core]

Once that is done you can:

  • use any z-quantum-core function by specifying its name and path as follows:
- name: generate-parameters
  config:
    runtime:
      language: python3
      imports: [z-quantum-core]
      parameters:
        file: z-quantum-core/steps/circuit.py
        function: generate_random_ansatz_params
  • use tasks which import zquantum.core in the python code (see below)

Python

Here's an example of how to use methods from z-quantum-core in a python task:

from zquantum.core.circuit import (
    build_ansatz_circuit,
    load_circuit_template,
    load_array,
    save_circuit,
)

ansatz = load_circuit_template("ansatz.json")
params = load_array("params.json")
circuit = build_ansatz_circuit(ansatz, params)
save_circuit(circuit, "circuit.json")

Even though it's intended to be used with Orquestra, z-quantum-core can be also used as a standalone Python module. To install it, you just need to run pip install -e . from the main directory. )

Development and Contribution

To install the development version, run pip install -e '.[dev]' from the main directory. (if using MacOS, you will need single quotes around the []. If using windows, or Linux, you might not need the quotes).

We use Google-style docstring format. If you'd like to specify types please use PEP 484 type hints instead adding them to docstrings.

There are codestyle-related Github Actions running for PRs to master or dev.

Additionally, you can set up our pre-commit hooks with pre-commit install . It checks for minor errors right before commiting or pushing code for quick feedback. More info here. Note that if needed, you can skip these checks with the --no-verify option, i.e. git commit -m "Add quickfix, prod is on fire" --no-verify.

  • If you'd like to report a bug/issue please create a new issue in this repository.
  • If you'd like to contribute, please create a pull request.

Running tests

Unit tests for this project can be run using pytest . from the main directory.

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  • Python 99.6%
  • Dockerfile 0.4%