Characterizing large-scale quantum computers via cycle benchmarking.

ABSTRACT: Quantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits,

SUBMITTER: Erhard A 

PROVIDER: S-EPMC6877623 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature