Physics

The course of Computational Statistical Mechanics aims to provide the necessary knowledge to understand and implement classical molecular dynamics and Monte Carlo techniques. The methods, that allow us to generate trajectories in phase space for sampling distinct statistical ensembles, will be studied. Some techniques which offer the possibility to calculate the free energy will be also discussed and it will be shown how the use of such results can provide a description of the atoms and molecules phase diagrams. At the end of the course, students will develop the ability of a quantitative reasoning and numerical skills useful for studying, modeling and understanding a large class of atomic and molecular systems as well as supramolecular aggregates. In addition, the student will be able to utilize the most common simulation packages which are available for a numerical study of complex systems, such as colloidal and bio-molecular systems, due to the acquired full knowledge of algorithms and numerical techniques on which these programs are built. Particular emphasis will be given to object-oriented and generic programming in the implementation of a computer simulation code. In particular, the modern C++ programming language will be introduced and discussed in the context of atomistic simulations. It will be also illustrated the use of the Python language, through the NumPy and MatPlotLib libraries, to analyze and visualize the data produced by computer simulations. During the course there will be also hands-on lectures, so that students will be able to put into practice the acquired knowledge through the implementation of their own simulation code. Students will be also stimulated to present the results obtained from the simulations, so as to test their ability to communicate clearly and effectively such results. The development of a numerical simulation code will be an opportunity for the students to design and develop their own project. This way they will be able to show their learning level and ability to apply independently the theoretical concepts acquired in the course. OBJECTIVES A - Knowledge and understanding OF 1) Know common techniques to carry out computer simulations OF 2) Know object oriented programming for scientific computations. OF 3) Know common methods for analyzing data obtained from computer simulations. OF 4) Understand data produced by computer simulations. B - Application skills OF 5) Ability to implement a simulation code. OF 6) Ability to exploit simulations to obtain information about the physical properties of investigated systems. OF 7) Be able to develop computer codes for analyzing data produced by computer simulations. C - Autonomy of judgment OF 8) Be able to critically analyze the results of “numerical experiments”. OF 9) Be able to integrate autonomously the acquired knowledge in order to face new problems that require additional numeric techniques. OF 10) Be able to identify the best technique to solve and study a physical problem numerically. D - Communication skills OF 11) Know how to communicate clearly to specialists and non-specialists, through manuscripts and presentations, the results obtained. OF 12) Know how to clearly discuss a scientific topic. OF 13) Know how to reproduce calculations related to a given scientific topic in a critical and informed manner. E - Ability to learn OF 14) Have the ability to learn new algorithms and numerical techniques by exploiting the scientific literature. OF 15) Be able to conceive and develop their own project consisting of writing a simulation code or implementing a numerical technique. OF 16) Be able to overcome difficulties and setbacks in the implementation of numerical techniques through original ideas and solutions.