http://hdl.handle.net/2123/9891
Title: | Relativistic quantum information theory and quantum reference frames |
Authors: | Palmer, Matthew |
Keywords: | WKB curved spacetime spin covariant |
Issue Date: | 24-Apr-2013 |
Publisher: | University of Sydney. Faculty of Science School of Physics |
Abstract: | This thesis is a compilation of research in relativistic quantum information theory, and research in quantum reference frames. The research in the former category provides a fundamental construction of quantum information theory of localised qubits in curved spacetimes. For example, this concerns quantum experiments on free-space photons and electrons in the vicinity of the Earth. From field theory a description of localised qubits that traverse classical trajectories in curved spacetimes is obtained, for photons and massive spin-1/2 fermions. The equations governing the evolution of the two-dimensional quantum state and its absolute phase are determined. Quantum information theory of these qubits is then developed. The Stern-Gerlach measurement formalism for massive spin-1/2 fermions is also derived from field theory. In the latter category of research, I consider the process of changing reference frames in the case where the reference frames are quantum systems. I find that, as part of this process, decoherence is necessarily induced on any quantum system described relative to these frames. I explore this process with examples involving quantum reference frames for phase and orientation. Quantifying the effect of changing quantum reference frames provides a theoretical description for this process in quantum experiments, and serves as a first step in developing a relativity principle for theories in which all objects including reference frames are necessarily quantum. |
URI: | http://hdl.handle.net/2123/9891 |
Type of Work: | PhD Doctorate |
Type of Publication: | Doctor of Philosophy Ph.D. |
Appears in Collections: | Sydney Digital Theses (Open Access) |
File | Description | Size | Format | |
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palmer_mc_thesis.pdf | PhD Thesis | 1.53 MB | Adobe PDF |
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