Date of Award

9-2023

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Mathematics and Statistics

First Advisor

Benjamin F. Akers, PhD

Abstract

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the traditional method, making use of machine learning and comparisons with probability distributions. It also examines the robustness of these techniques to noise in simulated quantum computing circuits.

AFIT Designator

AFIT-ENC-MS-23-S-005

Comments

A 12-month embargo was observed for posting this thesis on AFIT Scholar.

Approved for public release. PA case number on file.

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