ELECTIVE COURSES

1) APPLIED MATHEMATICAL METHODS

  • First- and second-order ordinary differential equations.
  • Representation theory.
  • Group theory.
  • Variational Calculus

2) ADVANCED PROGRAMMING

  •  Advanced programming in high-level languages
  •  Parallel programming
  •  Programming complex scripts

3) ELECTRONIC STRUCTURE

  • Hartee Fock method
  • Post-Hartree Fock methods to account for the electron correlation. Multiconfigurational methods
  • Density Functional Theory
  • Semiempirical methods

4) QUANTUM DYNAMICS

  • Representation of the wave function. Finite Basis Representation (FBR) methods, Discrete Variable Representation (DVR) methods, Fast Fourier Transform
  • Wave Packets: construction and propagation
  • The Multi Configurational Time Dependent Hartree (MCTDH) scheme
  • Analysis of the wave function
  • Applications to chemical reactivity and molecular spectroscopy

5) INTRODUCTION TO EQUILIBRIUM STATISTICAL MECHANICS

  • Principle of Maximum Entropy.
  • Maxwell-Boltzmann Distribution.
  • Thermodynamic potentials.
  • Chemical potential.
  • Systems in interaction. Mean field.
  • Quantum Statistical Mechanics.
  • Multidisciplinary applications in physics, chemistry and biology

6) NON-EQUILIBRIUM STATISTICAL PHYSICS

  • Non-equilibrium thermodynamics. Entropy production
  • Fluctuation phenomena. Brownian motion. Langevin and Fokker-Planck equations. Fluctuation-dissipation theorem. Master equation. Kinetic theory.
  • Diffusion processes. Active transport.
  • Activated processes. Rate theory.
  • Multidisciplinary applications in chemistry and biology.

7) ADVANCED METHODS OF SIMULATION

  • Advanced techniques in Monte Carlo. Biased Monte Carlo methods. Calculation of free energies.
  • Quantum Monte Carlo
  • Advanced Molecular Dynamics. Thermostats and barostats. Calculation of free energies. Event Driven Molecular Dynamics
  • “Ab initio” Molecular Dynamics. Car-Parrinello method.
  • Introduction to advanced optimization methods in Statistical Physics.

8) MULTISCALE, COARSE-GRAINED METHODS AND MIXED METHODS

  • Introduction to multiscale problems
  • Classical algorithms in multiscale modeling
  • Simulation of rare events. Activated dynamics. Transition State Theory. Transition Path Sampling. Metadynamics
  • Mesoscopic dynamics
  • Hybrid methods. QM/MM

9) CONDENSED MATTER

  • Phases of matter. Structure and symmetry. Phase transitions.
  • Statistical field theories
  • The Renormalization Group in Condensed Matter.
  • Disordered phases of matter.
  • Quantum phases of matter
  • Bose gases. Fermi Gases.

10) ELECTRONIC STRUCTURE OF SOLIDS

  • Free electron model. Electron transport
  • Periodic systems. Bloch functions, electronic bands.
  • Distortions in one-dimensional systems
  • Electronic structure of solids: 2D systems. Symmetry and Brillouin zones. Fermi surface.
  • Electronic structure of solids: 3D systems. Chemical bonding and band structure
  • Applications

11) SURFACES AND CATALYSIS

  • Basic concepts in heterogeneous catalysis
  • Types of catalysts and design
  • Heterogeneous catalysis in the chemical industry
  • Heterogeneous catalysis and computational chemistry: simulation of spectra and STM images, study of reaction mechanisms, periodic models and nanoparticles.
  • Applications

12) MOLECULAR STRUCTURE AND CHEMICAL REACTIVITY

  • Electron density and quantitative description of the chemical bond
  • Born-Oppenheimer approximation. Topological features of potential energy surfaces. Reaction paths.
  • Geometry optimization algorithms. Localization of minima and transition states.
  • Applications

13) SOFT MATTER

  • Interactions and Phase Transitions
  • Macromolecules
  • Colloids
  • Supramolecular self-assembly
  • Interfacial phenomena
  • Deformation and Flow

14) COMPLEX SYSTEMS

  • Introduction to complex systems: dynamical systems and scaling laws
  • Spatio-temporal structures. Modelization, linear stability, simulation
  • Introduction to complex networks: structure and applications

15) STRUCTURE OF BIOMACROMOLECULES AND BIOPOLYMERS

  • Structure and function of DNA and RNA
  • Structure and function of proteins
  • Protein folding
  • Enzymatic reactions
  • Protein-ligand recognition; protein-protein recognition
  • Computer-aided drug design

16) COMPUTATIONAL SYSTEMS BIOLOGY

  • Introduction to the computational systems biology
  • Metabolic regulation. Concepts of enzymology, metabolic control analysis, macromolecular crowding
  • Flux balance analysis in metabolism
  • Processes in cell signaling and genetic regulation