Search result: Catalogue data in Spring Semester 2021

Computational Science and Engineering Bachelor Information
For All Programme Regulations
Fields of Specialization
Physics
NumberTitleTypeECTSHoursLecturers
402-0812-00LComputational Statistical Physics Information W8 credits2V + 2UM. Krstic Marinkovic
AbstractComputer simulation methods in statistical physics. Classical Monte-Carlo-simulations: finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Application to Boltzmann machines. Simulation of non-equilibrium systems.

Molecular dynamics simulations: long range interactions, Ewald summation, discrete elements, parallelization.
ObjectiveThe lecture will give a deeper insight into computer simulation methods in statistical physics. Thus, it is an ideal continuation of the lecture
"Introduction to Computational Physics" of the autumn semester. In the first part students learn to apply the following methods: Classical Monte Carlo-simulations, finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Moreover, students learn about the application of statistical physics methods to Boltzmann machines and how to simulate non-equilibrium systems.

In the second part, students apply molecular dynamics simulation methods. This part includes long range interactions, Ewald summation and discrete elements.
ContentComputer simulation methods in statistical physics. Classical Monte-Carlo-simulations: finite-size scaling, cluster algorithms, histogram-methods, renormalization group. Application to Boltzmann machines. Simulation of non-equilibrium systems. Molecular dynamics simulations: long range interactions, Ewald summation, discrete elements, parallelization.
Lecture notesLecture notes and slides are available online and will be distributed if desired.
LiteratureLiterature recommendations and references are included in the lecture notes.
Prerequisites / NoticeSome basic knowledge about statistical physics, classical mechanics and computational methods is recommended.
402-0810-00LComputational Quantum Physics
Special Students UZH must book the module PHY522 directly at UZH.
W8 credits2V + 2UM. H. Fischer
AbstractThis course provides an introduction to simulation methods for quantum systems. Starting from the one-body problem, a special emphasis is on quantum many-body problems, where we cover both approximate methods (Hartree-Fock, density functional theory) and exact methods (exact diagonalization, matrix product states, and quantum Monte Carlo methods).
ObjectiveThrough lectures and practical programming exercises, after this course:
Students are able to describe the difficulties of quantum mechanical simulations.
Students are able to explain the strengths and weaknesses of the methods covered.
Students are able to select an appropriate method for a given problem.
Students are able to implement basic versions of all algorithms discussed.
Lecture notesA script for this lecture will be provided.
LiteratureA list of additional references will be provided in the script.
Prerequisites / NoticeA basic knowledge of quantum mechanics, numerical tools (numerical differentiation and integration, linear solvers, eigensolvers, root solvers, optimization), and a programming language (for the teaching assignments, you are free to choose your preferred one).
227-0161-00LMolecular and Materials Modelling Information W4 credits2V + 2UD. Passerone, C. Pignedoli
AbstractThe course introduces the basic techniques to interpret experiments with contemporary atomistic simulation, including force fields or ab initio based molecular dynamics and Monte Carlo. Structural and electronic properties will be simulated hands-on for realistic systems.
The modern methods of "big data" analysis applied to the screening of chemical structures will be introduced with examples.
ObjectiveThe ability to select a suitable atomistic approach to model a nanoscale system, and to employ a simulation package to compute quantities providing a theoretically sound explanation of a given experiment. This includes knowledge of empirical force fields and insight in electronic structure theory, in particular density functional theory (DFT). Understanding the advantages of Monte Carlo and molecular dynamics (MD), and how these simulation methods can be used to compute various static and dynamic material properties. Basic understanding on how to simulate different spectroscopies (IR, X-ray, UV/VIS). Performing a basic computational experiment: interpreting the experimental input, choosing theory level and model approximations, performing the calculations, collecting and representing the results, discussing the comparison to the experiment.
Content-Classical force fields in molecular and condensed phase systems
-Methods for finding stationary states in a potential energy surface
-Monte Carlo techniques applied to nanoscience
-Classical molecular dynamics: extracting quantities and relating to experimentally accessible properties
-From molecular orbital theory to quantum chemistry: chemical reactions
-Condensed phase systems: from periodicity to band structure
-Larger scale systems and their electronic properties: density functional theory and its approximations
-Advanced molecular dynamics: Correlation functions and extracting free energies
-The use of Smooth Overlap of Atomic Positions (SOAP) descriptors in the evaluation of the (dis)similarity of crystalline, disordered and molecular compounds
Lecture notesA script will be made available and complemented by literature references.
LiteratureD. Frenkel and B. Smit, Understanding Molecular Simulations, Academic Press, 2002.

M. P. Allen and D.J. Tildesley, Computer Simulations of Liquids, Oxford University Press 1990.

C. J. Cramer, Essentials of Computational Chemistry. Theories and Models, Wiley 2004

G. L. Miessler, P. J. Fischer, and Donald A. Tarr, Inorganic Chemistry, Pearson 2014.

K. Huang, Statistical Mechanics, Wiley, 1987.

N. W. Ashcroft, N. D. Mermin, Solid State Physics, Saunders College 1976.

E. Kaxiras, Atomic and Electronic Structure of Solids, Cambridge University Press 2010.
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