Parameterized process characterization with reduced resource requirements

TL;DR

This paper introduces a resource-efficient method for quantum process characterization that reduces experimental requirements and mitigates SPAM errors, demonstrated through simulations and IBM quantum processor experiments.

Contribution

It presents a novel approach for unitary process characterization that requires fewer resources and includes built-in SPAM error mitigation, without prior process knowledge.

Findings

Significantly fewer experiments needed compared to standard QPT

Improved gate fidelity through noise reduction in the process matrix

Effective process reconstruction on IBM quantum processors

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 process 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 $\chi$ 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.