Quantum Brain
← Back to papers

Parametrized process characterization with reduced resource requirements

Vicente Leyton-Ortega, Tyler Kharazi, R. Pooser·September 22, 2021·DOI: 10.1103/PhysRevA.105.052408
Physics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Quantum Process Tomography (QPT) is a powerful tool to characterize quantum operations, but it requires considerable resources making it impractical for more than 2-qubit systems. This work proposes an alternative approach that requires significantly fewer resources for unitary processes characterization without prior knowledge of the process and provides a built-in method for state preparation and measurement (SPAM) error mitigation. By measuring the quantum process as rotated through the X and Y axes on the Bloch Sphere, we can acquire enough information to reconstruct the quantum process matrix χ and measure its fidelity. We test the algorithm’s performance against standard QPT using simulated and physical experiments on several IBM quantum processors and compare the resulting process matrices. We demonstrate in numerical experiments that the method can improve gate fidelity via a noise reduction in the imaginary part of the process matrix, along with a stark decrease in the number of experiments needed to perform the characterization.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.