Quantum analogues of classical optimization algorithms.
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Date
2017
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Abstract
This thesis explores the quantum analogues of algorithms used in mathematical optimization.
The thesis focuses primarily on the iterative gradient search algorithm (algorithm
for finding the minimum or maximum of a function) and the Newton-Raphson
algorithm. The thesis introduces a new quantum gradient algorithm suggested by
Professor Thomas Konrad and colleagues and a quantum analogue of the Newton-Raphson
Method, a method for finding approximations to the roots or zeroes of a real-valued function.
The quantum gradient algorithm and the quantum Newton-Raphson are shown to
give a polynomial speed up over their classical analogues.
Description
Master of Science in Physics. University of KwaZulu-Natal, Durban 2017.