Quantum error mitigation via quantum principal component analysis

Abstract

This thesis presents an application of quantum principal component analysis (qPCA) in mitigating error for quantum sensing. qPCA is a quantum version of principal component analysis that offers faster and more efficient analysis of large datasets. It is a powerful method that allows for dimensionality reduction while retaining the most important information in the data. In this thesis, we utilize the ablity of dimensionality reduction to mitigate error in quantum evolution, demonstrate the effectiveness of extracting principal states from mixed states, and achive error mitigation on magnetic field sensing.

Date of Award	2024
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Bei ZENG (Supervisor)