Date of Award

1-1-2018

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Physics

Content Description

1 online resource (ii, xvi, 183 pages)

Dissertation/Thesis Chair

Ariel Caticha

Committee Members

Ariel Caticha, Oleg Lunin, Kevin Knuth, Herbert Fotso, Carlo Cafaro

Keywords

Contextuality, Entropy, Inference, Quantum Entropy, Quantum Information, Quantum Measurement, Quantum entropy, Quantum measure theory, entropy

Subject Categories

Other Physics | Quantum Physics | Statistical, Nonlinear, and Soft Matter Physics

Abstract

This thesis synthesizes probability and entropic inference with Quantum Mechanics and quantum measurement [1-6]. It is shown that the standard and quantum relative entropies are tools \emph{designed} for the purpose of updating probability distributions and density matrices, respectively [1]. The derivation of the standard and quantum relative entropy are completed in tandem following the same inferential principles and design criteria. This provides the first design derivation of the quantum relative entropy while also reducing the number of required design criteria to two.

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