README

The project is the execution of Task 1 of of the QOSF Mentorship Program 2020. The task requirements can be found here.
In case the file is no longer available, I report it here (in brackets is my short rephrasing):

Implement, on a quantum simulator of your choice, the following 4 qubits state |psi(theta)>:

Where the number of layers, denoted with L, has to be considered as a parameter. We call Layer [the circuit in the picture, so L=2 for example would mean the circuit in the picture repeated two times]. The angles, are variational parameters, lying in the interval (0, 2*pi ), initialized at random. Report with a plot, as a function of the number of layers, L, the minimum distance
epsilon = min_theta(|| |\psi(\theta)> - |\phi> ||)
Where |phi> is a randomly generated vector on 4 qubits and the norm [is Euclidean norm].
Bonus question:
Try using other gates for the parametrized gates and see what happens.

Project structure

The project is composed by:

• main.py: The file to start optimization. The configuration for the runs is a dictionary in the file.

• results_summary.ipynb(.pdf): The notebook where results are presented and analyzed. Backup in pdf.

• utilities: Folder containing all the python support files:

  • circuit_model.py: Circuit class to work with the qiskit quantum circuit, independently from the optimizer.
  • optimizer_base.py: Base class for the optimizers.
  • grad_optimizer.py: Class for the gradient optimizer via Tensorflow Adam.
  • scipy_optimizer.py: Class for the scipy optimizer. Tested with Nelder-Mead but then deprecated in favour of Tensorflow.
  • results.py: Class to store and work with the optimization results.
  • plot_helper.py: Collection of methods to generate plots in the jupyter notebook.
  • utils.py: Collection of methods to support the operations during optimization.

• results: Folder containing the optimization results in json format.

• doc: Folder containing extra material, like pictures for this README.

Explore results

The results are collected in the jupyter notebook. To run it and make sure all plots are generated, it is necessary to perform the following steps:

1. Install requirements from requirements.txt;
2. Activate the Jupyter Widgets to inteact with the plots: jupyter nbextension enable --py widgetsnbextension.

In case of problem with jupyter, please refer to the pdf non interactive version.