This project may be used as a monitoring system for quantum processors
that allows estimating their parameters based on the set of executed quantum circuits.
Currently it is in a work-in-progress state with lots of drawbacks -
typical embodiment of a "research code".
However, it was enough to produce satisfactory results,
as it will be shown in the article, which is going to be finished soon and then published (hopefully).
The main requirements are:
- python >= 3.9
- tensorflow >= 2.0
- tensornetwork library
- QGOpt library
Qiskit library is nost used in monitoring system itself, but
is required for post-processing and working with IBMQ.
For a full list of requirements, see requirements.txt.
This package is not wrapped into a Python library yet.
Right now, as a workaround, one may clone the repository and run the test Jupyter notebooks.
They will import .py files directly from the solver folder instead of an installed library.
Mind the required libraries, since there's no wheel package to resolve dependencies automatically.
After cloning, you may install essential libraries by running shell command
pip install -r requirements.txtRight now there is a tomography notebook which can be used as tutorial. It is heavily recommended to look it first; the notebook will walk you through the most important parts of conducting experiments.
Since this project is in a work-in-progress state and is not very well documented (yet),
it may also be useful to see the folder solver/unit_tests.
They can provide some insights about the program.
To run the tests, one should install pytest (it is included in requirements)
and run the simple command
pytest solver/unit_tests