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README.md

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In this repository there are the exercises made during the Numerical Simulation Laboratory. Every folder has a READ_ME file with informations about compilation and execution of the resepective program.

EXN = Lecture N

-Lecture 1: Pseudo random numbers, generalized central limit theorem, Buffon experiment simulation

-Lecture 2: Monte Carlo integration and importance sampling, random walks

-Lecture 3: Stochastic calculus applied to European call and put option prize estimates

-Lecture 4: Molecular Dynamics by numerical integration

-Lecture 5: Metropolis algorithm and Hydrogen atom's first two orbitals wavefunctions

-Lecture 6: Metropolis and Gibbs sampling applied to Ising model in 1 dimension

-Lecture 7: Molecular Dyanamics with Monte Carlo methods

-Lecture 8: Stochastic optimization by simulated annealing applied to estimate the parameters of a ground state wavefunction

-Lecture 9: Stochastic optimization by genetic algorithms applied to the Travelling Salesman Problem (TSP)

-Lecture 10: Parallel computing with MPI standard applied to the TSP code

-Lecture 11: Deep Neural Networks with Keras

-Lecture 12: Convolutional Neural Networks with Keras