Particle Methods
This course teaches the foundations of Particle Methods. Particle methods are a numerical simulation framework that allows simulating both discrete and continuous systems. Particles can represent agents, such as cars in a traffic simulation, or mathematical discretization points, such as when numerically solving differential equations. Particle methods are the most versatile simulation framework and indeed the only one that allows seamless treatment of all types of models using the same algorithms and data structures. After this course, you will be able to implement and use particlebased simulations of both continuous and discrete systems.
Contents
particle methods for continuous systems, particle methods for discrete systems, time stepping schemes for particle methods, efficient data structures, efficient neighborfinding algorithms, discretizing differential operators on particles, hybrid particlemesh methods.
Time/Place
Summer Term
Lecture: Wednesdays, 3. DS (11:1012:40) in APBE006 (computer science building)
Exercises: upon agreement
NO LECTURE / NO EXERCISE ON: MAY 15, MAY 22 (Dies Academicus), JUNE 12 (Pentecoste break), JUNE 19 (Computer Science Anniversary)
Programs / Modules
M.Sc. Computational Modeling and Simulation, Modules: CMSCLSELG, CMSCMAELV1, CMSCMAELV2, CMSVCELV1, CMSVCELV2
M.Sc./Diplom Computer Science, Module: INFVERT7
M.Sc. Distributed Systems Engineering, Modules: DSE14E13, DSE14E14
Format
2 SWS lecture, 2 SWS exercise, selfstudy
Registration to the course
For students of the Master program "Computational Modeling and Simulation: via CampusNet SELMA
For students of the Computer Science programs: via jExam
Teachers
Lecture: Prof. Ivo F. Sbalzarini
Exercises: Pietro Incardona
Exam
Date/Time: July 16, 2019 / 9am11am
Place: APB/E005 and APB/E006
Format: written
Duration: 90 minutes
At the exam, the following may be used:
 4 A4 sheets (8 pages if you print duplex) of handwritten summary. We recommend writing the summary by hand, but it can also be machinewritten. In the latter case, the font size must be 8 points or larger throughout.
 A standard pocket calculator (devices with network or bluetooth access, as well as devices capable of storing and displaying documents are not allowed)
Learning goals

Know efficient data structures and algorithms for particle methods

Software engineering and abstractions for particle simulations

Practical implementation of particle methods for discrete and continuous models
Lecture language: ENGLISH
Please find below the lecture syllabus and the handouts:
 Lecture 1  Administration and Introduction: what is modeling and simulation? What are particle methods?
 Lecture 2  Efficient data structures for shortrange interactions: cell lists and Verlet lists (Exercise PDF, Solution ZIP)
 Lecture 3  Time stepping algorithms: explicit and implicit (Exercise PDF, Solution ZIP)
 Lecture 4  Error and stability of time stepping (Exercise PDF, Solution ZIP)
 Lecture 5  Particle methods for itembased models with stochastic dynamics; examples: population dynamics and chemical reactions (Exercise PDF, Solution ZIP)
 Lecture 6  Particle methods for itembased models with deterministic dynamics; example: granular flows and molecular dynamics (Exercise PDF, Solution ZIP)
 Lecture 7  Discretizing differential operators on particles: Smooth Particle Hydrodynamics (Exercise PDF, Solution ZIP)
 Lecture 8  Discretizing differential operators on particles: Particle Strength Exchange (Exercise PDF)
 Lecture 9  DCPSE as a unifying framework for fieldbased particle simulations
 Lecture 10  Eulerian and Lagrangian simulations of fieldbased models. LOCATION FOR LECTURE 10 ONLY: CSBD, Seminar Room Ground Floor (Pfotenhauerstr. 108)
 Lecture 11  Hybrid particlemesh methods and particlemesh interpolation.
Full lecture notes can be found here.
Project
The student project during the tutorials focuses on software engineering and on implementing a portable software library for particlebased simulations. Then, this library is used to perform different example simulation.