Machine Learning Enabled Fault Detection and Diagnosis of Quantum Circuits
Description
This is an interdisciplinary data science project that involves aspects and requires expertise from quantum information theory and machine learning. In this project we plan to develop and implement a novel approach to substantially improving the performance of quantum computers using advancements in the area of machine learning enabled fault detection and diagnosis. We will adapt and further develop existing machine learning protocols to efficiently and reliably detect and diagnose faulty quantum circuits. The protocols are expected to reach beyond the capabilities of current arts in the error diagnosis of quantum circuits, and to provide detailed and transparent information about various sources of errors in the quantum circuits with significantly fewer queries to the quantum circuit and considerably fewer repeated experiments. This project will allow student to learn and acquire expertise in topics that cross quantum information theory, quantum computing, and machine learning.
Advisors
Skills Required by the team
- Python
- Machine Learning