# Bootstrapping quantum process tomography via a perturbative ansatz

## TL;DR

This paper introduces a physically motivated, efficient method for quantum process tomography that leverages pairwise two-qubit data to accurately characterize multi-qubit quantum processes, reducing error sensitivity.

## Contribution

The authors propose a novel bootstrapping approach for quantum process tomography that uses a perturbative ansatz to efficiently reconstruct multi-qubit processes from two-qubit data, improving accuracy and robustness.

## Key findings

- Numerical simulations show high accuracy in characterizing noisy three-qubit gates.
- Experimental results demonstrate successful three-qubit gate reconstruction from two-qubit data.
- Method exhibits insensitivity to system preparation and measurement errors.

## Abstract

Quantum process tomography has become increasingly critical as the need grows for robust verification and validation of candidate quantum processors. Here, we present an approach for efficient quantum process tomography that uses a physically motivated ansatz for an unknown quantum process. Our ansatz bootstraps to an effective description for an unknown process on a multi-qubit processor from pairwise two-qubit tomographic data. Further, our approach can inherit insensitivity to system preparation and measurement error from the two-qubit tomography scheme. We benchmark our approach using numerical simulation of noisy three-qubit gates, and show that it produces highly accurate characterizations of quantum processes. Further, we demonstrate our approach experimentally, building three-qubit gate reconstructions from two-qubit tomographic data.