Page 41 - Undergraduate Research Opportunities Program Proceedings 2017-18

School of Science
Department of Physics

Maxwell Demon and Information Thermodynamics

Supervisor: SZETO Kwok Yip / PHYS
Student: CHEUNG Long Him / PHYS-IRE Course: UROP3100, Fall

The dynamics of opinion formation process in a social network is of great interest for many non-equilibrium systems,
such as election, competition of market share in advertising etc. By introducing local disturbance in the social network,
such as the implantation of an agent, we can use numerical simulation to measure the effect of this agent on the result
of the election, which has a deadline. By extending the statistical physics of damage spreading in spin models on lattice
to social network, we investigate the effect of one agent on a two-party election on the time to dominance as a function
of the given time to the deadline of the election. We find that certain rewiring mechanism of the social network will
enhance the speed to dominance by the party that implant the agent. Using genetic algorithm, we also find good
method of rewiring that can greatly increase the efficiency of the agent. Our model used is the Ising model and the
network used is Watts-Strogatz network. We perform Monte Carlo simulation on the effect of interaction and use a
genetic algorithm with a mutation matrix to find the best way of rewiring to amplify the effect of the agent in influencing
the result of the election. We also discuss the general topological feature of an optimal rewiring condition in maximizing
the effect of the local disturbance in opinion formation.

Supervisor: SZETO Kwok Yip / PHYS
Student: WANG Ziqi / PHYS Course: UROP1100, Spring

In this paper we will basic on the 2 model of networks: random graph networks and Watts-Strogatz (WS) model, study
the construction of them and the network property like its clustering coefficient. Then we develop an extended
definition of clustering coefficient to polygon expression, and explore how the parameter which construct the network
affect the clustering coefficient of nodes within the origin and extended clustering coefficient. Applying the node-
individual difference of clustering coefficient, we hope to find a strategy related to the clustering coefficient to spread
information, simulated by a bias random walker move on the 2 types of networks.

Damage Spreading in Networks

Supervisor: SZETO Kwok Yip / PHYS
Student: CHOW Chun Yu / PHYS-IRE Course: UROP1100, Fall

The first part of the paper discusses the Ising model for ferromagnetism and shows the results of an implementation.
The graphs of mean energy, mean magnetization are plotted as functions of temperature. Addition of spy in the Ising
model lattice has influence on the relations above, and the dominating time is investigated. The second part focuses on
using the genetic algorithm (GA) to solve an optimization problem, the result of traditional GA is compared with the
mutation only genetic algorithm (MOGA) approach.

Evolutionary Computation for Optimization

Supervisor: SZETO Kwok Yip / PHYS
Student: LAU Ka Ki / PHYS Course: UROP1100, Spring

This research mainly focuses on the problem of scheduling workers in different daily shifts for a company operating 24
hours per day and 7 days per week. By the preference of the workers, different time slots available will be assigned a
“satisfactory rating”, indicating the degree of satisfaction of that worker if he is scheduled to work on that shift. This
research simulates the arrangement of one week. The goal is to maximize the total satisfactory rating of the workers,

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