Randomized Compiling for Scalable Quantum Computing on a Noisy Superconducting Quantum Processor

Bibliographic Details
Title: Randomized Compiling for Scalable Quantum Computing on a Noisy Superconducting Quantum Processor
Authors: Akel Hashim, Ravi K. Naik, Alexis Morvan, Jean-Loup Ville, Bradley Mitchell, John Mark Kreikebaum, Marc Davis, Ethan Smith, Costin Iancu, Kevin P. O’Brien, Ian Hincks, Joel J. Wallman, Joseph Emerson, Irfan Siddiqi
Source: Physical Review X, Vol 11, Iss 4, p 041039 (2021)
Publisher Information: American Physical Society, 2021.
Publication Year: 2021
Collection: LCC:Physics
Subject Terms: Physics, QC1-999
More Details: The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scale quantum (NISQ) computing, systematic miscalibrations, drift, and crosstalk in the control of qubits can lead to a coherent form of error that has no classical analog. Coherent errors severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable quantum computations. Moreover, the average error rates measured by randomized benchmarking and related protocols are not sensitive to the full impact of coherent errors and therefore do not reliably predict the global performance of quantum algorithms, leaving us unprepared to validate the accuracy of future large-scale quantum computations. Randomized compiling is a protocol designed to overcome these performance limitations by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of algorithmic performance from error rates measured via cycle benchmarking. In this work, we demonstrate significant performance gains under randomized compiling for the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. Additionally, we accurately predict algorithm performance using experimentally measured error rates. Our results demonstrate that randomized compiling can be utilized to leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2160-3308
Relation: https://doaj.org/toc/2160-3308
DOI: 10.1103/PhysRevX.11.041039
Access URL: https://doaj.org/article/4a5aaf0acc4a4a6d8c8af2ac41e8de58
Accession Number: edsdoj.4a5aaf0acc4a4a6d8c8af2ac41e8de58
Database: Directory of Open Access Journals
More Details
ISSN:21603308
DOI:10.1103/PhysRevX.11.041039
Published in:Physical Review X
Language:English