Zurück zur Auswahl
33227-01 - Vorlesung: Molecular dynamics simulations with applications in soft matter (2 KP)
| Semester | Frühjahrsemester 2016 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Martin Steinhauser (martin.steinhauser@unibas.ch, BeurteilerIn) |
| Inhalt | This lecture provides a comprehensive introduction to the foundations of Molecular Dynamics and Monte Carlo simulations. Application examples from Soft Matter Physics, in particular Polymer Physics are used. Programming skills are not required and will be developed in the lecture as necessary. Important basic data structures and algorithms will be introduced and analysed in terms of their complexity. An elementary introduction to biological structures and their basic interactions will be provided. The students will learn how to organize and write their own simulation code and how to model, simulate and analyze basic properties of molecular fluids and macromolecules. The simulation approach is based on coarse-grained (i.e. not atomistic) models of fluids and macromolecules which allow for covering much larger length and time scales than is possible in atomistic or electronic structure simulation approaches. |
| Lernziele | Planing, organisation and implementation of a scientific molecular dynamics program from scratch. Programming skills. Knowledge of important basic data structures and how to analyse the efficiency of algorithms. Understanding basic potential functions used in MD codes for the simulation of molecular fluids, polymers and biomolecules. Understanding the statistical, physical foundations of the Molecular Dynamics and the Monte Carlo methods. |
| Literatur | M. O. Steinhauser, Computer Simulation in Physics and Engineering, de Gruyter, Berlin, Boston (2012) K. Binder and D. W. Heermann, Monte Carlo Simulation in Statistical Physics, Springer (2010) M. O. Steinhauser, Computational Multiscale Modeling of Fluids and Solids. Theory and Applications, Springer Verlag (2008) D. Frenkel and B. Smit, Understanding Molecular Simulation, Academic Press (2002) J. M. Thijssen, Computational Physics, Cambridge, New York, Melbourne, Cambridge University Press (1999) |
| Weblink | Homepage of Instructor |
| Teilnahmevoraussetzungen | The lecture is open to all graduate and PhD students interested in learning from scratch the foundations of the Molecular Dynamics and Monte Carlo methods and how to implement these methods on a computer using efficient algorithms and data structures in a high-level language. Bachelor students with basic knowledge of classical mechanics and statistical physics are also welcome. Programming skills are not necessary and will be developed in the language C during the lecture and in the homework assignments: Learning by doing! In order to do the programming exercises you will need access to a computer system, preferably UNIX or any variant of a Linux system. |
| Anmeldung zur Lehrveranstaltung | Belegen via MOnA. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|
Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Doktorat Chemie: Empfehlungen (Promotionsfach: Chemie) Modul Geology (Master Geowissenschaften) Modul Vertiefungsfach Chemie (Master Nanowissenschaften) Vertiefungsmodul (Master Chemie) Wahlbereich Master Informatik: Empfehlungen (Master Informatik) |
| Prüfung | Lehrveranst.-begleitend |
| Hinweise zur Prüfung | The final grade is based on a scale from 1-6. In order to just pass, the students must have attained at least 50% of all credit points in the weekly homework assignments. The assignments will be of theoretical/mathematical nature plus programming exercises. |
| An-/Abmeldung zur Prüfung | Anmelden: Belegen; Abmelden: Dozierende |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,5 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch |
| Anbietende Organisationseinheit | Departement Chemie |