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SDS 419: Modeling and Simulation for Scientific Applications

Course Title

Modeling and Simulation for Scientific Applications

Course Code

SDS 419

Course Type




Year / Semester

1st / 2nd (subject to change)

Instructor’s Name

Constantia Alexandrou (Lead Instructor), Kyriacos Hadjiyiannakou, Jacob Finkenrath



Lectures / week

1 (2h)

Laboratories / week

1 (2h)

Course Purpose and Objectives

To teach students to use simulation algorithms and to analyze their results in order to study complex systems.  

Learning Outcomes

The students will be able to use state-of-the-art supercomputers to perform simulations of real life applications. 


SDS 401, SDS 402

 Requirements  -

Course Content

Iterative solvers for linear systems: iterative methods for solving systems of equations and eigenvalue problems, Krylov subspace methods including Conjugate Gradient, Lanczos and Arnoldi methods and preconditioners including deflation and multi-grid. 

Statistical methods and sampling: Importance sampling, Markov Chain Monte Carlo, Metropolis algorithm and autocorrelation analysis, molecular dynamics. These concepts will be applied to practical applications, such as the Ising model, and water models.   

The course will consist of exercises and a project worked out in groups. Each group will have to give a talk on the methodology and the results. 

Teaching Methodology

Lectures, exercises


1) Building Software for Simulation (Wiley) by James J. Nutaro

2) Computer Simulation in Physics and Engineering, by Steinhauser, Martin Oliver


25% coursework, 75% exam