Efficient flexible characterization of quantum processors with nested error models. (13th September 2021)

• Record Type: Journal Article
• Authors: Nielsen, Erik; Rudinger, Kenneth; Proctor, Timothy; Young, Kevin; Blume-Kohout, Robin
• Is Part Of: New journal of physics. Volume 23:Number 9(2021)
• Publication Date: 2021-09-13
• Subjects: quantum characterization -- model selection -- QCVV; Physics -- Periodicals; Physics; Periodicals; 530.05
• DOI: 10.1088/1367-2630/ac20b9
• Languages: English
• ISSNs: 1367-2630

Abstract

Abstract: We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.