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 2021
Lecture: Wednesdays, 3. DS (11:1012:40), location to be announced. NO LECTURES ON: MAY 5 (dies academicus), MAY 26, JUNE 2, JUNE 30
Exercises: Wednesdays, 1. DS (07:3009:00), location to be announced. NO TUTORIAL IN THE FIRST WEEK. First tutorial on April 21, 2021
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 other degree programs: via your respective study or examination office
Teachers
Lecture: Prof. Ivo F. Sbalzarini
Exercises: Dr. Sachin Krishnan
Exam 2020
Date/Time: 31. July 2020, 7:30h  9:00h
Place: HSZ/AUDI/H, Hörsaalzentrum, room Audimax
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)
Grade scale:
All exams are graded in absolute terms w.r.t. the following predefined grade scale that remains constant over the years:
 The top grade of 1.0 is reached with 80% of the maximum possible points
 Half of that, i.e., 40% of the maximum possible points, are required to pass
 Below 40%, or noshow, is a fail.
Registration to the exam
For students of the Master program Computational Modeling and Simulation: via CampusNet SELMA
For students of other degree programs: via your respective examination office
Exam Review 2020
You can come and look at your exam, and ask questions about its correction and the answers given during the exam review times. In order to accommodate for everyone's schedule, we offer three exam review dates at different times:
 October 12, 2020, 2pm CANCELED DUE TO RAIN. NEW DATE: October 19, 2020, 10am
 October 27, 10am
 November 4, 4pm
Location for all exam reviews: Outdoors in the seating area in front of the Center for Systems Biology Dresden, Pfotenhauerstr. 108 (yellow building) (Maps Link). The review only takes place if there is no rain. In case of rain, a new date will be found. In order to participate, You MUST wear a face mask and you are only allowed to come forward one by one.
IMPORTANT: All students attending an exam review must fill in and sign the exam review form they are going to receive during the review. Undocumented exam reviews are not permitted.
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
 Lecture 3  Time stepping algorithms: explicit and implicit
 Lecture 4  Error and stability of time stepping
 Lecture 5  Particle methods for itembased models with stochastic dynamics; examples: population dynamics and chemical reactions
 Lecture 6  Particle methods for itembased models with deterministic dynamics; example: granular flows and molecular dynamics
 Lecture 7  Discretizing differential operators on particles: Smooth Particle Hydrodynamics
 Lecture 8  Discretizing differential operators on particles: Particle Strength Exchange
 Lecture 9  DCPSE as a unifying framework for fieldbased particle simulations
 Lecture 10  Eulerian and Lagrangian simulations of fieldbased models
 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.