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Small-world complex network generation on a digital quantum processor
Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of their neighborhoods and model how rich physical complexity can emerge from a simple set of underlying dynamical rules. The inability of classical computers to simulate large quantum systems hinders the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345974/ https://www.ncbi.nlm.nih.gov/pubmed/35918333 http://dx.doi.org/10.1038/s41467-022-32056-y |
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author | Jones, Eric B. Hillberry, Logan E. Jones, Matthew T. Fasihi, Mina Roushan, Pedram Jiang, Zhang Ho, Alan Neill, Charles Ostby, Eric Graf, Peter Kapit, Eliot Carr, Lincoln D. |
author_facet | Jones, Eric B. Hillberry, Logan E. Jones, Matthew T. Fasihi, Mina Roushan, Pedram Jiang, Zhang Ho, Alan Neill, Charles Ostby, Eric Graf, Peter Kapit, Eliot Carr, Lincoln D. |
author_sort | Jones, Eric B. |
collection | PubMed |
description | Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of their neighborhoods and model how rich physical complexity can emerge from a simple set of underlying dynamical rules. The inability of classical computers to simulate large quantum systems hinders the elucidation of quantum cellular automata, but quantum computers offer an ideal simulation platform. Here, we experimentally realize QCA on a digital quantum processor, simulating a one-dimensional Goldilocks rule on chains of up to 23 superconducting qubits. We calculate calibrated and error-mitigated population dynamics and complex network measures, which indicate the formation of small-world mutual information networks. These networks decohere at fixed circuit depth independent of system size, the largest of which corresponding to 1,056 two-qubit gates. Such computations may enable the employment of QCA in applications like the simulation of strongly-correlated matter or beyond-classical computational demonstrations. |
format | Online Article Text |
id | pubmed-9345974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93459742022-08-04 Small-world complex network generation on a digital quantum processor Jones, Eric B. Hillberry, Logan E. Jones, Matthew T. Fasihi, Mina Roushan, Pedram Jiang, Zhang Ho, Alan Neill, Charles Ostby, Eric Graf, Peter Kapit, Eliot Carr, Lincoln D. Nat Commun Article Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of their neighborhoods and model how rich physical complexity can emerge from a simple set of underlying dynamical rules. The inability of classical computers to simulate large quantum systems hinders the elucidation of quantum cellular automata, but quantum computers offer an ideal simulation platform. Here, we experimentally realize QCA on a digital quantum processor, simulating a one-dimensional Goldilocks rule on chains of up to 23 superconducting qubits. We calculate calibrated and error-mitigated population dynamics and complex network measures, which indicate the formation of small-world mutual information networks. These networks decohere at fixed circuit depth independent of system size, the largest of which corresponding to 1,056 two-qubit gates. Such computations may enable the employment of QCA in applications like the simulation of strongly-correlated matter or beyond-classical computational demonstrations. Nature Publishing Group UK 2022-08-02 /pmc/articles/PMC9345974/ /pubmed/35918333 http://dx.doi.org/10.1038/s41467-022-32056-y Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jones, Eric B. Hillberry, Logan E. Jones, Matthew T. Fasihi, Mina Roushan, Pedram Jiang, Zhang Ho, Alan Neill, Charles Ostby, Eric Graf, Peter Kapit, Eliot Carr, Lincoln D. Small-world complex network generation on a digital quantum processor |
title | Small-world complex network generation on a digital quantum processor |
title_full | Small-world complex network generation on a digital quantum processor |
title_fullStr | Small-world complex network generation on a digital quantum processor |
title_full_unstemmed | Small-world complex network generation on a digital quantum processor |
title_short | Small-world complex network generation on a digital quantum processor |
title_sort | small-world complex network generation on a digital quantum processor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345974/ https://www.ncbi.nlm.nih.gov/pubmed/35918333 http://dx.doi.org/10.1038/s41467-022-32056-y |
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