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University of York

Mutually Unbiased Bases in Low Dimensions

Abstract

dc:description.abstract

The density matrix of a qudit may be reconstructed with optimal efficiency if the expectation values of a specific set of observables are known. The required observables only exist if it is possible to identify d mutually unbiased (MU) complex (d×d) Hadamard matrices, defining a complete set of d+1 MU bases. This thesis is an exploration of sets of r≤d+1 MU bases in low dimensions. We derive all inequivalent sets of MU bases in dimensions two to five confirming that in these dimensions, the complete sets of (d+1) MU bases are unique. In dimension six, we prescribe a first Hadamard matrix and construct all others mutually unbiased to it, using algebraic computations performed by a computer program. We repeat this calculation many times, sampling all known complex Hadamard matrices, and never find more than two that are mutually unbiased. We also study subsets of a complete set of MU bases by considering sets of pure states which satisfy the desired properties. We use this concept to provide the strongest numerical evidence so far that no seven MU bases exist in dimension six. In the final part of the thesis, we introduce a new quantum key distribution protocol that uses d-level quantum systems to encode an alphabet with c letters. It has the property that the error rate introduced by an intercept-and-resend attack is higher than the BB84 or six-state protocols when the legitimate parties use a complete set of MU bases.

Degree

thesis:*
Name dc:type.qualificationname
Ph.D
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
University of York
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Brierley, Stephen
Advisor dc:contributor.advisor
  • Weigert, S

Identifiers

dc:identifier.*
Identifier
uk.bl.ethos.516399
OAI identifier oai:identifier
oai:etheses.whiterose.ac.uk:587

Chain of custody

source
Harvested from
White Rose University Consortium
Base URL
etheses.whiterose.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Brierley, Stephen. Mutually Unbiased Bases in Low Dimensions. doctoral thesis, University of York, 2009.