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Pattern storage in qubit arrays using entanglement and quantum annealing
Samarakoon, Bathiya
Samarakoon, Bathiya
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2019-05
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Abstract
Multiqubit arrays can be prepared in any state by adjusting the parameters in the
Hamiltonian that governs their time evolution. In this work we show that these arrays can
be used for pattern storage and recall, using techniques of machine learning. Any shape of a
character or letter can be encoded as a collection of line segments, represented by the pairwise
entanglement between neighboring qubits. We did this in two ways: first, by training the
real time evolution; and second, by training to a ground state as a quantum annealing (QA)
algorithm, by lowering the effective temperature of the system. In the real time training we
succeeded in creating the letters X, M, N, and O, in a four-qubit system, with 2.09 % RMS
error. With the QA we trained fifteen different characters on a four- five-, and then six-qubit
system, with comparable RMS errors. We also showed that the pattern storage was robust
to both classical and quantum noise.
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Thesis (M.S.)-- Wichita State University, College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and Physics
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Wichita State University
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Copyright 2019 by Bathiya Samarakoon
All Rights Reserved