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© 2016

The Landscape of Free Fermionic Gauge Models

Benefits

  • Recognised as Baylor University’s Outstanding STEM Dissertation for the 2013-2014 academic year

  • Provides an introduction to heterotic strings and the spin-structure construction of free fermionic models

  • Presents a collection of metaheuristic algorithms which provide the groundwork for extended generic free fermionic surveys

Book
  • 1.5k Downloads

Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Douglas G. Moore
    Pages 1-7
  3. Douglas G. Moore
    Pages 9-34
  4. Douglas G. Moore
    Pages 47-66
  5. Back Matter
    Pages 79-102

About this book

Introduction

In this thesis, the author describes the development of a software framework to systematically construct a particular class of weakly coupled free fermionic heterotic string models, dubbed gauge models. In their purest form, these models are maximally supersymmetric (N = 4), and thus only contain superpartners in their matter sector. This feature makes their systematic construction particularly efficient, and they are thus useful in their simplicity.  The thesis first provides a brisk introduction to heterotic strings and the spin-structure construction of free fermionic models. Three systematic surveys are then presented, and it is conjectured that these surveys are exhaustive modulo redundancies. Finally, the author presents a collection of metaheuristic algorithms for searching the landscape for models with a user-specified spectrum of phenomenological properties, e.g. gauge group and number of spacetime supersymmetries. Such algorithms provide the groundwork for extended generic free fermionic surveys.

Keywords

Conformal Anomaly Free Fermionic Gauge Models Gauge Fixing Heterotic String Models Superstring Action

Authors and affiliations

  1. 1.Southwestern MedicalUniversity of TexasDallasUSA

About the authors

Dr Douglas Moore is currently with the University of Texas Southwestern Medical Center, having gained his Ph.D. at Baylor University in 2014.

Bibliographic information