Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

CHUNG-YAU INVARIANTS AND RANDOM WALK ON GRAPHS

Sun, Xiaojuan (2020) CHUNG-YAU INVARIANTS AND RANDOM WALK ON GRAPHS. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF
Download (481kB) | Preview

Abstract

The Chung-Yau graph invariants were originated from Chung-Yau’s work on discrete Green’s function. They are useful to derive explicit formulas and estimates for hitting times of random walks on discrete graphs. In this thesis, we study properties of Chung-Yau invariants and apply them to study some questions:
(1) The relationship of Chung-Yau invariants to classical graph invariants; (2) The change of hitting times under natural graph operations;
(3) Properties of graphs with symmetric hitting times;
(4) Random walks on weighted graphs with different weight schemes.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sun, Xiaojuanxis41@pitt.eduxis41
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairHajlasz, Piotrhajlasz@pitt.edu
Committee MemberSparling, Georgesparling@pitt.edu
Committee MemberDeBlois, Jasonjdeblois@pitt.edu
Committee MemberRen, Zhaozren@pitt.edu
Committee MemberXu, Hao
Date: 16 September 2020
Date Type: Publication
Defense Date: 26 June 2020
Approval Date: 16 September 2020
Submission Date: 23 August 2020
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 86
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Mathematics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: random walk, hitting time, spanning tree, Chung-Yau invariants, Kemeny’s constants, reversible graph.
Date Deposited: 16 Sep 2020 15:06
Last Modified: 16 Sep 2020 15:06
URI: http://d-scholarship.pitt.edu/id/eprint/39670

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item