Verification of Diagnostic Circuits on IBM Quantum Circuits: Using Hybrid Machine Learning for Fault Classification

Previous projects proposed an fault identification scheme to isolate faulty quantum logic gates, using hybrid machine learning. This procedure was implemented onto real IBM quantum computers through the IBM Quantum Experience, cloud based open access network of quantum computers. We demonstrate that through the use of neural networks, the project was actualized. The presentation will focus on the creation and implementation of an appropriate neural network, capable of properly identifying gate faults on circuits of multiple gates and varying types.