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The University of Southampton
Courses

MATH6140 Structure and Dynamics of Networks

Module Overview

Networks are ubiquitous in the modern world: from the biological networks that regulate cell behaviour, to technological networks such as the Internet and social networks such as Facebook. Typically real-world networks are large, complex, and exhibit both random and regular properties, making them both challenging and interesting to model. This course is an introduction to the structure and dynamics of networks, as a modelling tool in applied mathematics.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Define basic network properties, compute them in theoretical and practical situations, and explain their significance in network modelling
  • Explain the relation between some network structural and spectral properties, and their significance for real-world networks
  • Utilise graph theoretical tools to determine the stability of complex dynamical systems
  • Explain real world phenomena in complex dynamical networks, such as synchronisation and scale-free network structures
  • Express stochastic processes mathematically as dynamical equations on networks for the probability of stochastic outcomes.
  • Extract information about stochastic processes, such as the probability distribution and critical phenomena.
  • Investigate a topic related to networks and present your results.

Syllabus

Part I: Network structure and eigenvalues • Network terminology • Network eigenvalues and eigenvectors, and their relation to structural network properties Part II: Dynamics of and on networks • Generative network models: random graphs, small worlds, Barabasi-Albert model • Examples of dynamical processes on networks: random walks, models of coupled oscillators Part III: Stochastic dynamics on networks • Overview of general stochastic differential equations, including the chemical master equation • Biochemical reaction networks

Learning and Teaching

Teaching and learning methods

Lectures, tutorials, guided reading and private study. The lectures will be based on selected material from the reading list. Lectures will give an overview of the topic and introduce the main references and students are expected to demonstrate in-depth independent learning through private study. The module is organised in three blocks of four weeks each.

TypeHours
Teaching48
Independent Study102
Total study time150

Resources & Reading list

A.-L.Barabasi (2016). Network Science. 

M.E.J.Newman (2010). Networks: An Introduction. 

Assessment

Summative

MethodPercentage contribution
In-class Test  (40 minutes) 26.66%
In-class Test  (40 minutes) 26.67%
In-class Test  (40 minutes) 26.67%
Oral presentation 20%

Referral

MethodPercentage contribution
Essay/report 20%
Final Exam 80%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre requisites: MATH1048 and MATH1049 and MATH1059

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