Date of Award

1-1-2021

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Physics

Content Description

1 online resource (viii, 261 pages)

Dissertation/Thesis Chair

Ariel Caticha

Committee Members

Ariel Caticha, Oleg Lunin, Philip Goyal, Kevin Knuth, Marcel Reginatto

Keywords

Entropy, General Relativity, Quantum field theory, Quantum Gravity, Quantum physics, Entropy (Information theory), Quantum gravity, Bayesian statistical decision theory, Space and time

Subject Categories

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

Abstract

It has often been the case in history that the laws of physics have been used as the framework for understanding and implementing information processing. The tacit assumption is that the laws of physics are fundamental and that the notion of information is derived from these laws. Here we take the opposite view: the laws of physics are an application of the rules for processing information. The inferential framework of entropic dynamics (ED) has previously been developed by A. Caticha for the purposes of understanding and deriving quantum theory, in much the same way that E.T. Jaynes used the MaxEnt approach to derive the formalism of statistical mechanics. In this thesis we apply the ED framework to construct a quantum dynamics for scalar fields in space-time.

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