A Random Matrix Theory of Pauli Tomography

TL;DR

This paper develops a random matrix theory approach to quantum state tomography, revealing deep connections with the Gaussian Unitary Ensemble and enabling analytic error analysis and sample complexity bounds.

Contribution

It introduces a novel RMT framework for QST errors, linking them to GUE spectra, and provides analytic tools for error and complexity analysis in quantum tomography.

Findings

Errors in QST can be modeled using GUE spectra.

Analytic expressions for mean and variance of tomography errors.

Bound on the sample complexity of quantum state tomography.

Abstract

Quantum state tomography (QST), the process of reconstructing some unknown quantum state $\hat\rho$ from repeated measurements on copies of said state, is a foundationally important task in the context of quantum computation and simulation. For this reason, a detailed characterization of the error $\Delta\hat\rho = \hat\rho-\hat\rho^\prime$ in a QST reconstruction $\hat\rho^\prime$ is of clear importance to quantum theory and experiment. In this work, we develop a fully random matrix theory (RMT) treatment of state tomography in informationally-complete bases; and in doing so we reveal deep connections between QST errors $\Delta\hat\rho$ and the gaussian unitary ensemble (GUE). By exploiting this connection we prove that wide classes of functions of the spectrum of $\Delta\hat\rho$ can be evaluated by substituting samples of an appropriate GUE for realizations of $\Delta\hat\rho$. This powerful and flexible result enables simple analytic treatments of the mean value and variance of the error as quantified by the trace distance $\|\Delta\hat\rho\|_\mathrm{Tr}$ (which we validate numerically for common tomographic protocols), allows us to derive a bound on the QST sample complexity, and subsequently demonstrate that said bound doesn't change under the most widely-used rephysicalization procedure. These results collectively demonstrate the flexibility, strength, and broad applicability of our approach; and lays the foundation for broader studies of RMT treatments of QST in the future.