Students in physics or chemistry normally have a solid theoretical background but very little (if any) experience with computer simulations. Moreover, they normally have no idea of the importance of computer simulations in understanding the behavior of real systems. While there are many schools targeting young students/researchers who are already experienced in the field, the present activity represents a unique opportunity to provide a comprehensive introduction to atomistic simulations without any pre-requisite. The purpose of this School will be threefold: (i) providing undergraduate students with a basic but detailed overview of the theoretical foundations of computer simulations of molecular systems, with a focus on molecular dynamics and Monte Carlo methods; (ii) giving an overview of the domains of interesting applications; (iii) providing the basics for running in practice a simple simulations using molecular dynamics and Monte Carlo codes. At the end of the school the students should have a clear idea of the importance of computer simulations; moreover, they should be aware of the problems that are still open and are at the center of current research effort and should have the capability of writing a code for performing a simple simulation or an analysis.

With respect to the previous editions, we decided to split the school in two parts, one devoted to classical methods and the other one to quantum mechanics related algorithms. From now on, these two activities will run at alternating years. We think that this will improve the organization of the school and students will benefit of this fact. In 2016, we will organize the activity on classical simulations. An initial week (from Tuesday to Friday) will be devoted to an introduction to numerical methods: this is not mandatory to all students, but highly recommended to those who are not familiar with simple concepts of computations.The second and third week, which will be mandatory, are devoted to Monte Carlo and molecular dynamics (see below).

WEEK 1: Introduction of numerical methods
Introduction to Fortran 90 and C++
Introduction to AWK and Phyton
Numerical integration and differentiation

WEEK 2: Monte Carlo
Introduction on probability theory
Direct sampling
Markov chains
Advanced sampling techniques: reweighting and parallel tempering
Stochastic processes: Wiener processes and Brownian motion
Langevin equation and connection to quantum mechanics
Variational and projection quantum Monte Carlo

WEEK 3: Molecular dynamics
Introduction to molecular dynamics
Integrators
Analyzing a MD trajectory: Computing thermodynamic averages and structural quantities
Constraints
Thermostats and barostats
Pair lists and periodic boundary conditions
Long range forces