This repository contains the Pennylane code adaptation work of the original Qiskit based QuFI (Quantum Fault Injector) proposed by Oliveira et al. in the paper QuFI: a Quantum Fault Injector to Measure the Reliability of Qubits and Quantum Circuits.
All the dependencies of this project can be installed through the requirements.txt file.
You can create a virtual environment by installing miniconda and then running the following code:
conda create -n qufi_tutorial python=3.9
conda activate qufi_tutorial
pip3 install -r tutorial_requirements.txt
Simply import qufi as a library and call its methods.
import qufi
from qufi import execute, save_results, IQFTA simple usage example is available in run_circuits.py.
A load distributed campaign example is available in launch_campaign.py.
Contribution to the project is welcome, however for opening issues please refer to the original repository by Oliveira.
The project has been developed by Marzio Vallero as part of the Computer Engineering Masters Degree thesis work Quantum Machine Learning Fault Injection under the guidance of professors B. Montrucchio, P. Rech and assistant researcher Edoardo Giusto, during the second semester of the academic year 2021/2022 at the Politecnico di Torino University.
For right to use, copyright and warranty of this software, refer to this project's License.