pith. sign in

arxiv: 0807.5058 · v2 · submitted 2008-07-31 · 🪐 quant-ph

Adaptive Bayesian and frequentist data processing for quantum tomography

classification 🪐 quant-ph
keywords operatorquantumstateadaptiveaveragingbayesiancompleteconvergence
0
0 comments X
read the original abstract

The outcome statistics of an informationally complete quantum measurement for a system in a given state can be used to evaluate the ensemble expectation of any linear operator in the same state, by averaging a function of the outcomes that depends on the specific operator. Here we introduce two novel data-processing strategies, non-linear in the frequencies, which lead to faster convergence to theoretical expectations.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.