Vanwege het Corona virus is het nog onduidelijk hoe het onderwijs precies verzorgd gaat worden. Zie voor de actuele informatie de betreffende vakpagina’s op Blackboard/Brightspace.

Studiegids

nl en

Complex Networks (BM)

Vak
2020-2021

Admission requirements

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.

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

### Course objectives

### Timetable

Physics Schedule
For detailed information go to Timetable in Brightspace

Mode of instruction

Zie Brightspace

Assessment method

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

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

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

Registration

Registration for Brightspace occurs via uSis

How to sign up for classes click here

Contact

Dr. Diego Garlaschelli