Quantum process tomography via completely positive and trace-preserving projection

TL;DR

This paper introduces a new algorithm for quantum process tomography that efficiently projects superoperators onto the set of physically valid quantum channels, improving speed and accuracy over existing methods.

Contribution

The paper presents a novel projection algorithm for quantum process tomography that outperforms previous methods in speed and accuracy while ensuring physical validity.

Findings

The new algorithm is significantly faster than existing methods.

It provides more accurate quantum process estimates.

The algorithm guarantees physically valid quantum channels.

Abstract

We present an algorithm for projecting superoperators onto the set of completely positive, trace-preserving maps. When combined with gradient descent of a cost function, the procedure results in an algorithm for quantum process tomography: finding the quantum process that best fits a set of sufficient observations. We compare the performance of our algorithm to the diluted iterative algorithm as well as second-order solvers interfaced with the popular CVX package for MATLAB, and find it to be significantly faster and more accurate while guaranteeing a physical estimate.