Simulation Methods in Physics I WS 2016/2017
- Lecture (2 SWS) and Tutorials (2 SWS)
- Prof. Dr. Christian Holm
- Course language
- Location and Time
- Lecture: Thu, 14:00 - 15:30; ICP, Allmandring 3, Seminar Room (room 01.079)
- Tutorials: tba.
- We expect the participants to have basic knowledge in classical and statistical mechanics, thermodynamics, and partial differential equations, as well as knowledge of a programming language (Python and C).
The lecture is accompanied by hands-on tutorials which will take place in the CIP-Pool of the ICP, Allmandring 3 (room 01.033). They consist of practical exercises at the computer such as small programming tasks, simulations, visualization and data analysis. The tutorials build upon each other, therefore continuous attendance is expected.
The first part of the course intends to give an overview about modern simulation methods used in physics today. The focus of the lecture will be to introduce different approaches to simulating a problem, hence we will not go too to deep into specific details but rather try to cover a broad range of methods. In more detail, the lecture will consist of:
- Molecular Dynamics
- The first problem that comes to mind when thinking about simulating physics is solving Newtons equations of motion for particles with given interactions. From that perspective, we first introduce the most common numerical integrators. This approach quickly leads us to Molecular Dynamics (MD) simulations. Many of the complex problems of practical importance require us to take a closer look at statistical properties, ensembles and the macroscopic observables.
- The goal is to be able to set up and run real MD simulations for different ensembles and understand and interpret the output.
- Error Analysis
- Autocorrelation, Jackknifing, Bootstrapping
- Monte Carlo Simulations
- Since their invention, the importance of Monte Carlo (MC) sampling has grown constantly. Nowadays it is applied to a wide class of problems in modern computational physics. We want to present the general idea and theory behind MC simulations and show some more properties using simple toy models such as the Ising model.
- Critical exponents
- Finite-size scaling, universality concept, how to determine critical exponent with lattice spin models
|20.10.2016||Course Content, Organization, Introduction|
|03.11.2016||Basics of Statistical Mechanics|
|10.11.2016||MD: Potentials, Units|
|17.11.2016||MD - continued|
|24.11.2016||PBC, cell-lists, Observables|
|01.12.2016||RDF, D, Brownian motion|
|08.12.2016||Green-Kubo, Langevin Dynamics, Thermostats|
|22.12.2016||B.Sc. / M.Sc. thesis @ ICP: information & research topics|
|26.01.2017||Monte-Carlo and Critical Phenomena|
|02.02.2017||Finite Size Scaling|
A preliminary version of the script can be downloaded here (929 kB).
If you find any kind of mistake / error / typo / bad formatting / etc. in the script (you surely will!), please send an email to Johannes Zeman.
Daan Frenkel, Berend Smit.
Understanding Molecular Simulation: From Algorithms to Applications.
Part of Computational Science, volume 1. Edition 2.
Academic Press, San Diego, 2002. ISBN: 978-0-12-267351-1.
Mike P. Allen, Dominik J. Tildesley.
Computer Simulation of Liquids.
Part of Oxford Science Publications. Edition 1.
Clarendon Press, Oxford, 1987.
D. C. Rapaport.
The Art of Molecular Dynamics Simulation.
Cambridge University Press, 2004. ISBN: 9780511816581.
D. P. Landau, K. Binder.
A guide to Monte Carlo Simulations in Statistical Physics.
Edition second edition.
M. E. J. Newman, G. T. Barkema.
Monte Carlo Methods in Statistical Physics.
Edition 2002 edition.
Oxford University Press, 1999.
Useful online resources
- Thermostats: Philippe H. Hünenberger, Thermostat Algorithms for Molecular Dynamics Simulations, Adv. Polym. Sci. (2005) 173:105–149.
- Error analysis: W. Janke, Statistical Analysis of Simulations:Data Correlations and Error Estimation, Quantum Simulations of Complex Many-Body Systems:
From Theory to Algorithms, Lecture Notes, (2002).
- Be careful when using Wikipedia as a resource. It may contain a lot of useful information, but also a lot of nonsense, because anyone can write it.
Location and Time
- The tutorials take place in the CIP-Pool on the first floor of the ICP (Room 01.033, Allmandring 3) on
- tba. (Tutor: Michael Kuron)
- tba. (Tutor: Florian Weik)
|0. First steps with Linux, Python, and C||2016-10-31 12:00||Worksheet 0 (269 KB)|
|1. Integrators||2016-11-14 12:00||available on 2016-11-02
|2. Statistical mechanics and Molecular Dynamics||2016-11-28 12:00||available on 2016-11-16
|3. Molecular Dynamics and Observables||2016-12-12 12:00||available on 2016-11-30
|4. Error Analysis, Langevin Thermostat||2017-01-09 12:00||available on 2016-12-14
|5. Other Thermostats, Monte-Carlo||2017-01-23 12:00||available on 2017-01-11
|6. Ising Model and Finite Size Scaling||2017-02-06 12:00||available on 2017-01-25|
- For the tutorials, you will get a personal account for the ICP machines.
- All material required for the tutorials can also be found on the ICP computers in the directory
- For the reports, we have a nice latex-template.tex (7 KB).
- You can do the exercises in the CIP-Pool when it is not occupied by another course. The pool is accessible on all days, except weekends and late evenings.
- If you do the exercises in the CIP-Pool, all required software and tools are available.
- If you want to do the exercises on your own computer, the following tools are required. All of these packages should be readily available from your OS distribution, if it is not Windows.
- The following Python packages:
- A C compiler (e.g. GCC)
- We only have experience with Unix/Linux machines. Although most tools will probably also work on Windows, we cannot guarantee it, and we can also not help you to get it running there.
- The worksheets are to be solved in groups of two or three people. We will not accept hand-in-exercises that only have a single name on it.
- A written report (between 5 and 10 pages) has to be handed in for each worksheet. We recommend using LaTeX to prepare the report.
- You have two weeks to prepare the report for each worksheet.
- The report has to be sent to your tutor via email.
- Most participants need 50% of the points in the hands-in exercises to be admitted to the oral examination (see Examination for details).
What happens in a tutorial
- The tutorials take place every week.
- The new worksheet will be available for download on the days before the tutorial.
- In the first tutorial after you received a worksheet, the solutions of the previous worksheet will be presented (see below) and the new worksheet will be discussed.
- In the second tutorial after you received the worksheet, there is time to work on the exercises and to ask questions.
- You will have to hand in the reports on Monday after the second tutorial.
- In the third tutorial after you received the worksheet, the solutions will be discussed:
- The tutor will ask a team to present their solution.
- The tutor will choose one of the members of the team to present each task.
- This means that each team member should be able to present any task.
- At the end of the term, everybody should have presented at least once.
- Linux Cheat Sheet (2.27 MB) (source (42 KB)) - the most important linux commands on a single page
- Use the existing documentation of Python itself! To get help on the command
- Or use the Web browser to read it. Start
pydoc -p 4242
- and visit the page http://localhost:4242
- http://python.org/doc/ - the official Python documentation (including tutorials etc.)
- Byte_of_Python.pdf (546 KB) - the free eBook "A byte of Python" , also available in German
- first of all, try to use
- http://numpy.scipy.org/ - the homepage of NumPy contains a lot of documentation
- Script of the lecture "Physik auf dem Computer" (German) (3.42 MB) - Numerics in Python using Numpy
Running Python on your own computer
If you want to solve the problems on your own computer, you need to install Python along with a few extensions. This works differently depending on your operating system.
Debian und Ubuntu Linux
sudo apt-get update sudo apt-get install python python-numpy python-scipy \ python-matplotlib ipython ipython-notebook mkdir -p ~/.config/matplotlib echo 'backend: TkAgg' > ~/.config/matplotlib/matplotlibrc
sudo zypper install python python-numpy python-scipy \ python-matplotlib IPython mkdir -p ~/.config/matplotlib echo 'backend: TkAgg' > ~/.config/matplotlib/matplotlibrc
Mac OS X
First, install the C compiler:
xcode-select --install xcodebuild -license accept
Now download and install MacPorts. Next, you can install the Python packages.
sudo port selfupdate sudo port install python27 py27-numpy py27-scipy \ py27-matplotlib py27-ipython py27-jupyter sudo port select python python27 sudo port select ipython py27-ipython
For Windows, we recommend Anaconda Python, an all-in-one package that includes all required Python modules.
Depending on the module that this lecture is part of, there are differences on how to get the credits for the module:
- BSc/MSc Physik, Modul "Simulationsmethoden in der Physik" (36010) and Erasmus Mundus International Master FUSION-EP
- Obtain 50% of the possible points in the hand-in excercises of this lecture and the second part of the lecture as a prerequisite for the examination (USL-V)
- 60 min of oral examination (PL)
- After the lecture "Simulation Methods in Physics II" in summer term (i.e. Summer 2016)
- Contents: both lectures and the excercises of "Simulation Methods in Physics I"
- International MSc Physics, Elective Module "Simulation Techniques in Physics I, II" (240918-005)
- Obtain 50% of the possible points in the hand-in excercises of this lecture as a prerequisite for the examination
- 30 min of oral examination (PL) about the lecture and the excercises
- BSc/MSc SimTech, Modul "Simulationsmethoden in der Physik für SimTech I" (40520)
- Obtain 50% of the possible points in the hand-in excercises of this lecture as a prerequisite for the examination (USL-V)
- 40 min of oral examination (PL) about the lecture and the excercises
- MSc Chemie, Modul "Simulationsmethoden in der Physik für Chemiker I" (35840)
- The marks for the module are the marks obtained in the excercises (BSL)