University of Illinois Urbana-Champaign

Summer Research Opportunities Report: A Neural Network approach to the Many Body Localized Phase

Villarreal, David

Content Files
SROP_report.pdf

Permalink

https://hdl.handle.net/2142/98888

Description

Title
Summer Research Opportunities Report: A Neural Network approach to the Many Body Localized Phase
Author(s)
Villarreal, David
Issue Date
2017-07-27
Keyword(s)
  • Many-body localization
  • Neural network
Date of Ingest
2017-12-06T21:32:16Z
Abstract
The Many Body Localized Phase (MBL) is a phase that exists in distinction to the Ergodic phase. As such, the MBL phase violates the Eigenstate Thermalization Hypothesis and does not undergo thermalization. In this paper, the Ergodic to MBL phase transition will be explored with Artificial Neural Networks (ANNs) trained on a Heisenberg spin chain with disorder. One of the main aspects explored in this article is if neural networks can in fact be trained to perceive a difference in both of these phases, and moreover, examine the as-of-now unanswered question of whether or not information about the MBL phase is encoded in the many-body density matrix at infinite temperature ρeq(T → ∞). A phase diagram is generated, along with probability curves that predict MBL given a level of disorder. Finally, reverse engineering is done to understand the ANN and evidence is found that the ANN is learning about the entanglement entropy.
Type of Resource
text
Genre of Resource
Technical Report
Language
en
Permalink
http://hdl.handle.net/2142/98888

Owning Collections

SROP 2017 PRIMARY