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Learning programs for the quantum computer

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posted on 23.05.2021, 12:17 by Olivia-Linda Enciu
Manual quantum programming is generally diffcult for humans, due to the often hard-to-grasp properties of quantum mechanics and quantum computers. By outlining the target (or desired) behaviour of a particular quantum program, the task of programming can be turned into a search and optimization problem. A flexible evolutionary technique known as genetic programming may then be used as an aid in the search for quantum programs. In this work a genetic programming approach uses an estimation of distribution algorithm (EDA) to learn the probability distribution of optimal solution(s), given some target behaviour of a quantum program.



Master of Science


Computer Science

Granting Institution

Ryerson University

LAC Thesis Type