The course is divided into four parts which together aim to provide essential modeling and simulation skills for physicists. Part 1 is an introduction to dynamical systems. Among other things, we will analyze Lotka-Volterra and Lorentz equations, with a focus on fixed points and time development. In connection with models in discrete time, period doubling, bifurcation and chaos are also introduced. In part 2, we apply the knowledge from part 1 to introduce disease propagation on networks. These networks can represent flight routes between cities or social connections between people. In part 3, we introduce stochastic simulation methods such as Langevin dynamics, Brownian motion (diffusion) and Monte Carlo methods where the implementation takes its starting point in deterministic molecular dynamics. In part 4, we give a brief introduction to Machine Learning. We mainly focus on applications based on given training datasets, for example classification problems.
90 credits including single variable calculus, linear algebra, introductory mathematical statistics, introductory programming methodology and introductory numerical methods. Proficiency in English and Swedish equivalent to the level required for basic eligibility for higher studies. Requirements for Swedish only apply if the course is held in Swedish.
Academic credits
Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.
Application code
UMU-53009
Application
Application deadline was
15 April 2024.
The application period is closed.
Application and tuition fees
As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.
