Bootstrapping quantum process tomography via a perturbative ansatz

Abstract

Quantum process tomography represents one of the workhorses of quantum information processing, but suffers from exponential resource scaling. Here, the authors propose to efficiently infer general processes by approximating them through a sequence of two-qubit processes, and demonstrate it on a three-qubit case.