Quantum State Tomography as a Bilevel Problem, Utilizing I-Q Plane Data

TL;DR

This paper introduces a bilevel optimization approach for quantum state tomography that directly utilizes IQ-plane measurement data, improving efficiency over traditional methods.

Contribution

It formulates quantum state estimation as a bilevel problem using actual measurement data, offering a novel joint discrimination and tomography framework.

Findings

Enhanced sample complexity compared to traditional methods

Direct use of IQ-plane data improves reconstruction accuracy

Bilevel optimization effectively combines discrimination and tomography

Abstract

It is natural to ask how to utilize actual measurements, such as the so-called IQ-plane data obtained in the dispersive readout of transmon qubits, in the estimation of the state of a quantum system. We formulate the joint problem of discrimination and quantum state tomography as a bilevel optimization problem and show how to solve it. The use of the joint problem can improve the sample complexity (or the reconstruction error for a fixed number of measurements) compared with traditional techniques that decompose the problem into the discrimination and state tomography based on the estimated expectation values of certain projective measurement operators.