Speaker: Daniele Malpetti. Title: Numerics and quantum physics: a stochastic computational method for cold atoms in optical lattices. Abstract: At very small scale, of the order of the nanometer, classical physics becomes insufficient for describing matter, because quantum effects emerge prominently. Studying this physics can be a very challenging task, both experimentally and theoretically, because of the complexity of matter itself. For this reason, in 1982, Richard Feynman proposed not to study matter directly, but to simulate it, using a so-called quantum simulator [Int. J. Theor. Physics, 21:467]. This would amount to studying some “simple” experimental quantum systems, which can be mapped onto more complex ones. More than twenty years later, thanks to great technological advances, the existence of quantum simulators was made possible. In this talk we will focus on a specific class of quantum simulators, namely cold atoms in optical lattices, which constitute a highly controllable experimental setup for the study of quantum effects. Despite their controllability, due to their quantum nature, an exact mathematical study of these systems remains inaccessible to the computational capacity of current technology. For this reason most approaches rely either on approximations or on stochastic methods. We will present a new computational approach based both on an approximation and a stochastic (Monte Carlo) method. At the end of the talk we will also briefly review the relations between quantum physics and machine learning.