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Massachusetts Institute of Technology

Free approximation of transport properties in organic system using Stochastic Random Matrix Theory

Abstract

dc:description.abstract

The proposed research is a study and application of Stochastic analysis- Random Matrix Theory(RMT) to fast calculate the transport properties of large static systems with relatively large disorder in mesoscopic size. As a major topic of Random Matrix Theory(RMT), free convolution managed to approximate the distribution of eigenvalues in an Anderson Model.So the next step is trying to expand RMT to approximate other quantities, such as transmission probability, conductivity and etc. Due to the eigenvectors' shifts, RMT works well only for small disorder. System with larger disorder requires to take in account of the changes in eigenvectors directly or through other approximations of the eigenvectors.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Chemistry.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Xie, Wanqin, Ph. D. Massachusetts Institute of Technology
Advisor dc:contributor.advisor
  • Troy Van Voorhis.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/93040
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/93040

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Xie, Wanqin, Ph. D. Massachusetts Institute of Technology. Free approximation of transport properties in organic system using Stochastic Random Matrix Theory. Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/93040