Numerical Simulation Laboratory
A.Y. 2026/2027
Learning objectives
Simulation is an essential tool in studying complex systems, anticipating, complementing and reinforcing both experimental and
theoretical approaches. The purpose of this computing laboratory is to introduce and apply advanced Monte Carlo sampling and other
techniques to perform simulations of complex systems and to solve complex numerical tasks.
theoretical approaches. The purpose of this computing laboratory is to introduce and apply advanced Monte Carlo sampling and other
techniques to perform simulations of complex systems and to solve complex numerical tasks.
Expected learning outcomes
1) advanced techniques for sampling random variables and simulate stochastic processes
2) familiarity with the applications of these techniques to the simulation of complex systems
3) an introduction to some computational intelligence techniques
4) an introduction to parallel computation and parallel programming
Expected learning outcomes
The course aims to provide students with:
· advanced techniques for sampling random variables and simulate stochastic processes
· familiarity with the applications of these techniques to the simulation of complex systems
· an introduction to some computational intelligence techniques, machine learning and deep neural networks
· an introduction to parallel computation and parallel programming
2) familiarity with the applications of these techniques to the simulation of complex systems
3) an introduction to some computational intelligence techniques
4) an introduction to parallel computation and parallel programming
Expected learning outcomes
The course aims to provide students with:
· advanced techniques for sampling random variables and simulate stochastic processes
· familiarity with the applications of these techniques to the simulation of complex systems
· an introduction to some computational intelligence techniques, machine learning and deep neural networks
· an introduction to parallel computation and parallel programming
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Course currently not available
PHYS-02/A - Theoretical Physics of Fundamental Interactions, Models, Mathematical Methods and Applications - University credits: 3
PHYS-04/A - Theoretical Physics of Matter, Models, Mathematical Methods and Applications - University credits: 3
PHYS-04/A - Theoretical Physics of Matter, Models, Mathematical Methods and Applications - University credits: 3
Laboratories: 36 hours
Lessons: 24 hours
Lessons: 24 hours