Next Article in Journal
An Improved Chaotic Optimization Algorithm Applied to a DC Electrical Motor Modeling
Next Article in Special Issue
Robust Macroscopic Quantum Measurements in the Presence of Limited Control and Knowledge
Previous Article in Journal
Label-Driven Learning Framework: Towards More Accurate Bayesian Network Classifiers through Discrimination of High-Confidence Labels
Previous Article in Special Issue
Quantum Information: What Is It All About?
Open AccessArticle

Entropic Updating of Probabilities and Density Matrices

Department of Physics, University at Albany (SUNY), Albany, NY 12222, USA
Entropy 2017, 19(12), 664; https://doi.org/10.3390/e19120664
Received: 2 November 2017 / Revised: 1 December 2017 / Accepted: 2 December 2017 / Published: 4 December 2017
(This article belongs to the Special Issue Quantum Information and Foundations)
We find that the standard relative entropy and the Umegaki entropy are designed for the purpose of inferentially updating probabilities and density matrices, respectively. From the same set of inferentially guided design criteria, both of the previously stated entropies are derived in parallel. This formulates a quantum maximum entropy method for the purpose of inferring density matrices in the absence of complete information. View Full-Text
Keywords: probability theory; entropy; quantum relative entropy; quantum information; quantum mechanics; inference probability theory; entropy; quantum relative entropy; quantum information; quantum mechanics; inference
MDPI and ACS Style

Vanslette, K. Entropic Updating of Probabilities and Density Matrices. Entropy 2017, 19, 664.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop