z-quantum-optimizers is a module with basic optimizers to be used in workflows with Orquestra – a platform for performing computations on quantum computers developed by Zapata Computing.

Currently this library includes the following optimizers:

• Grid search
• Scipy optimizers
• CMS-ES (Covariance Matrix Adaptation Evolution Strategy)

It also includes a task templates for optimization of variational circuits.

In order to use z-quantum-optimizers in your workflow, you need to add it as a resource:

resources:
- name: z-quantum-optimizers
  type: git
  parameters:
    url: "[email protected]:zapatacomputing/z-quantum-optimizers.git"
    branch: "master"

and then import in a specific step:

- - name: my-task
    template: template-1
    arguments:
      parameters:
      - param_1: 1
      - resources: [z-quantum-optimizers]

Once it's done you can:

• use any template from templates/ directory
• use tasks which import zquantum.optimizers in the python code (see below).

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

from zquantum.optimizers import ScipyOptimizer
optimizer = ScipyOptimizer(method='L-BFGS-B')

or use optimizer-specs parameter to make our code work with other backends too:

from zquantum.core.utils import create_object
optimizer_specs = {{inputs.parameters.optimizer-specs}}
optimizer = create_object(optimizer_specs)

Even though it's intended to be used with Orquestra, you can also use it as a standalone python module. In order to install it run pip install . from the src directory.

You can find the development guidelines in the z-quantum-core repository.

In order to run tests please run pytest . from the main directory.

In order for the tests related to the daemon optimizer to work you need to first specify FLASK_APP environmental variable: export FLASK_APP=/path/to/z-quantum-optimizer/src/python/orquestra/optimizers/daemon-optimizer/proxy/rest.py.