Computational Methods in Physics

Simon Sirca was born on February 27, 1969, in Ljubljana, Slovenia. He is Professor of Physics at the Faculty of Mathematics and Physics, University of Ljubljana, where he has been teaching courses on Probability for Physicists, Computational Physics and Model Analysis. He is head of the research group Structure of Hadronic Systems active in the Hall A Collaboration at Thomas Jefferson National Accelerator Facility (USA) and the A1/MAGIX Collaborations at MAMI/MESA in Mainz (Germany). His main research field is the study of hadronic structure and dynamics by scattering of electrons on light nuclei, exploiting polarized beams, polarized targets, and recoil polarimetry. He is also involved in theoretical work on quark models of hadrons, with focus on electroweak processes.

Martin Horvat was born on April 25, 1977, in Maribor, Slovenia. He is Assistant Professor at the Faculty of Mathematics and Physics, University of Ljubljana, where he has led the Physical Laboratory Course and taught Basic Applied Mathematics and Physics.  The bulk of his research is devoted to classical and quantum non-linear dynamics, to transport properties in extended systems, to the quantum-classical correspondence, to theoretical and applied aspects of quantum mechanics on the classical phase space, as well as to statistical mechanics and its origin in dynamics. He is also involved in the development of methods for solving the time-dependent Schrödinger equation in atomic physics, in research of autonomic relativistic global navigation satellite systems (RGNSS) for the European Space Agency (ESA), in modeling of astrophysical bodies, mainly eclipsing binary stars and synthesis of their observable, for prominent astrophysical packages PHOEBE and in statistical analysis and modeling of uncertainty in normal-mode decomposition of weather forecasts from the European Centre for Medium-Range Weather Forecasts system (ECMWF).

Basics of Numerical Analysis.- Solving Non-linear Equations.- Numerical Integration and Differentiation.- Matrix Methods.- Transformations of Functions and Signals.- Statistical Analysis and Modeling of Data.- Modeling and Analysis of Time Series.- Initial-value Problems for ODE.- Boundary-value Problems for ODE.- Difference Methods for One-dimensional PDE.- Difference Methods for PDE in Two or more Dimensions.- Spectral Methods for ODE and PDE.- Inverse and Ill-posed Problems.