Prospectus

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Complex network (BM)

Course
2016-2017

Description

Transportation, traffic, energy, communication and social networks form the backbone of modern society. In recent years, there has been a growing fascination with the complex “connectedness” such networks provide. This connectedness manifests itself in many ways: in the rapid growth of the Internet and the World Wide Web, in the ease with which global communication takes place, in the speed at which news and information travels around the world, and in the spread of an epidemics or a financial crisis. These phenomena are based on the links that connect people and their decisions, and have global consequences. The course aims to provide students with a concise introduction into this lively area, and covers both theoretical principles and practical applications from a variety of different directions. Complex Networks is a multi-disciplinary course: it exposes views on Complex Networks from Physics, Mathematics and Computer Science, is aimed at students of and is taught by faculty from these disciplines.
Topics:

  • Introduction to real-world networks: concepts, challenges;

  • Random graphs, preferential attachment, small worlds;

  • Network ensembles: null models, maximum-entropy models;

  • Network Algorithms and computational networks;

  • Percolation & epidemiology on networks;

  • Ecological and Economic Networks;

  • Dynamic physical/biological/social systems with Netlogo

Programme form

  • 13 lectures – 6 practical assignment sessions

Literature

  • Course Notes/Diktaat (provided) – Netlogo Manual (provided)

Schedule

Physics Schedule

Form of examination

  • written examination (70%) – assignments (30%)

Prerequisites

The course is open to third-year bachelor Mathematics students and first-year master students of all programs of Physics, Mathematics and Computer Science (including Bioinformatics, ICT&Business, Informatica&Economie).

The course assumes basic knowledge of physics, mathematics and computer science at the bachelor level. In particular, familiarity with elementary notions from calculus, probability theory and statistical physics are helpful. Some light computer programming will be involved as well.

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