Optimal large-scale quantum state tomography with Pauli measurements
Abstract
Quantum state tomography aims to determine the state of a quantum system as represented by a density matrix. It is a fundamental task in modern scientific studies involving quantum systems. In this paper, we study estimation of high-dimensional density matrices based on Pauli measurements. In particular, under appropriate notion of sparsity, we establish the minimax optimal rates of convergence for estimation of the density matrix under both the spectral and Frobenius norm losses; and show how these rates can be achieved by a common thresholding approach. Numerical performance of the proposed estimator is also investigated.
Keywords
Cite
@article{arxiv.1603.07559,
title = {Optimal large-scale quantum state tomography with Pauli measurements},
author = {Tony Cai and Donggyu Kim and Yazhen Wang and Ming Yuan and Harrison H. Zhou},
journal= {arXiv preprint arXiv:1603.07559},
year = {2016}
}
Comments
Published at http://dx.doi.org/10.1214/15-AOS1382 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)