Although entanglement is a well studied property in the context of quantum systems, the ability to measure it in Monte Carlo methods is relatively new.
Through measures of the Renyi entanglement entropy and mutual information one is able to examine and characterize criticality, pinpoint phase transitions, and probe universality.
We describe the most basic algorithms for calculating these quantities in straightforward Monte Carlo methods and state of the art techniques used in high performance computing.
This description emphasizes the core principal of these measurements and allows one to both build an intuition for these quantities and how they are useful in numerical studies.
Using the Renyi entanglement entropy we demonstrate the ability to detect thermal phase transitions in the Ising model and XY model without use of an order parameter.
The scaling near the critical point also shows signatures identifying the universality class of the model.
Improved methods are explored using extended ensemble techniques that can increase calculation efficiency, and show good agreement with the standard approach.
We explore the "ratio trick" at finite temperature and use it to explore the quantum critical fan of the one dimensional transverse field Ising model, showing agreement with finite temperature and finite size scaling from field theory.
This same technique is used at zero temperature to explore the geometric dependence of the entanglement entropy and examine the universal scaling functions in the two dimensional transverse field Ising model.
All of this shows the multitude of ways in which the study of the Renyi entanglement entropy can be efficiently and practically used in conventional and exotic condensed matter systems, and should serve as a reference for those wishing to use it as a tool.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/7940 |
| Date | January 2013 |
| Creators | Inglis, Stephen |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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