A divide-and-conquer algorithm for quantum state preparation

Abstract Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states requir...

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Main Authors: Israel F. Araujo, Daniel K. Park, Francesco Petruccione, Adenilton J. da Silva
Format: Article
Language:English
Published: Nature Publishing Group 2021-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-85474-1
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spelling doaj-a136e05410b94f9092cfe162388ad9602021-03-21T12:36:14ZengNature Publishing GroupScientific Reports2045-23222021-03-0111111210.1038/s41598-021-85474-1A divide-and-conquer algorithm for quantum state preparationIsrael F. Araujo0Daniel K. Park1Francesco Petruccione2Adenilton J. da Silva3Centro de Informática, Universidade Federal de PernambucoSungkyunkwan University Advanced Institute of NanotechnologySchool of Electrical Engineering, KAISTCentro de Informática, Universidade Federal de PernambucoAbstract Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with exponential time advantage using a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.https://doi.org/10.1038/s41598-021-85474-1
collection DOAJ
language English
format Article
sources DOAJ
author Israel F. Araujo
Daniel K. Park
Francesco Petruccione
Adenilton J. da Silva
spellingShingle Israel F. Araujo
Daniel K. Park
Francesco Petruccione
Adenilton J. da Silva
A divide-and-conquer algorithm for quantum state preparation
Scientific Reports
author_facet Israel F. Araujo
Daniel K. Park
Francesco Petruccione
Adenilton J. da Silva
author_sort Israel F. Araujo
title A divide-and-conquer algorithm for quantum state preparation
title_short A divide-and-conquer algorithm for quantum state preparation
title_full A divide-and-conquer algorithm for quantum state preparation
title_fullStr A divide-and-conquer algorithm for quantum state preparation
title_full_unstemmed A divide-and-conquer algorithm for quantum state preparation
title_sort divide-and-conquer algorithm for quantum state preparation
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-03-01
description Abstract Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with exponential time advantage using a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.
url https://doi.org/10.1038/s41598-021-85474-1
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