Arbitrary State Preparation via Quantum Walks

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work we develop a mapping from dynamic CTQWs to the gate model of computation in the form of an algorithm to convert arbitrary single edge walks and single self loop walks, which are the fundamental building blocks of dynamic CTQWs, to their circuit model counterparts. We use this mapping to introduce an arbitrary quantum state preparation framework based on dynamic CTQWs. Our approach utilizes global information about the target state, relates state preparation to finding the optimal path in a graph, and leads to optimizations in the reduction of controls that are not as obvious in other approaches. Interestingly, classical optimization problems such as the minimal hitting set, minimum spanning tree, and shortest Hamiltonian path problems arise in our framework. We test our methods against uniformly controlled rotations methods, used by Qiskit, and find ours requires fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.10432
Citations
2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.69
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Arbitrary State Preparation via Quantum Walks

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Quantum Computing Algorithms and Architecture
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article

Arbitrary State Preparation via Quantum Walks

Alvin Gonzales, Zain H. Saleem, Igor Gaidai, Rebekah Herrman, Colin Campbell, Teague Tomesh, Ji Liu
article en
2 citations

Abstract

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work we develop a mapping from dynamic CTQWs to the gate model of computation in the form of an algorithm to convert arbitrary single edge walks and single self loop walks, which are the fundamental building blocks of dynamic CTQWs, to their circuit model counterparts. We use this mapping to introduce an arbitrary quantum state preparation framework based on dynamic CTQWs. Our approach utilizes global information about the target state, relates state preparation to finding the optimal path in a graph, and leads to optimizations in the reduction of controls that are not as obvious in other approaches. Interestingly, classical optimization problems such as the minimal hitting set, minimum spanning tree, and shortest Hamiltonian path problems arise in our framework. We test our methods against uniformly controlled rotations methods, used by Qiskit, and find ours requires fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

Argonne National Laboratory (US), Knoxville College (US), University of Tennessee at Knoxville (US)
Openalex Percentile: Top 22%
Quantum Computing Algorithms and Architecture
0.69
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