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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Nature Publishing Group
2021-03-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-85474-1 |
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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 |
work_keys_str_mv |
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