davide-mapelli / numeric_simulation_laboratory

Numerical Simulation Laboratory at Unimi in 2020-2021 (D.E. Galli). Advanced Monte Carlo methods: Markov chains, Metropolis algorithm. Numerical simulations in statistical mechanics. Stochastic calculus and stochastic differential equation. Computational intelligence, stochastic optimization. Parallel computing and parallel programming. Machine learning and deep neural networks

Numeric_Simulation_Laboratory

Numerical Simulation Laboratory III year optional course at Università degli Studi di Milano (Unimi) in 2020-2021 (held by Prof. Davide E. Galli).

Davide Mapelli

e-mail : [email protected]

The simulations are written in C++, the main code is in the main.cpp file, the makefile can be called just with the make command, the header files are the ".h" ones, and the class files can be found in other ".cpp" files. The results are in the Jupyter Notebook (".ipynb"). Each compiled Jupyter Notebook can be found in every folder with the name: "NN-Mapelli".

Topics:

• Sampling of random variables and Monte Carlo integration, Importance Sampling (LSN_01-LSN_02-LSN_03)
• Advanced Monte Carlo methods: Markov chains, Metropolis algorithm on MolDyn, Ising model, QM (LSN_06 - LSN_07 - LSN_08)
• Numerical simulations in statistical mechanics on MolDyn and QM (LSN_04 - LSN_05)
• Stochastic calculus and stochastic differential equation on Schrödinger equation (LSN_08)
• Genetic algorithms applied on the Travelling salesman problem (LSN_09)
• Parallel computing and parallel programming on TSP (LSN_10)
• Machine learning and deep neural networks (LSN_11 - LSN_12)