Operator Splitting Methods

    Operator splitting is a powerful method for numerical investigation of complex models. The basic idea of the operator splitting methods based on splitting of complex problem into a sequence of simpler tasks, called split sub-problems. The sub operators are usually chosen with regard to different physical process. Then instead of the original problem, a sequence of sub-models is solved, which gives rise to a splitting error. In practice, splitting procedures are associated with different numerical methods for solving the sub-problems, which also causes a certain amount of error.

Machine Learning and Physics

Machine Learning - A very short introduction

Machine Learning (ML) is a particular branch of a very broad discipline called Artificial Intelligence (AI). Whereas AI tries to solve the fundamental problem of "creating" a sentient or intelligent being from a silicon-based machine, or anything you could define as artificial in general, the problem with ML is somehow simpler.

Turing machines, Memcomputing and High Performance Computing

Many of us have seen The Imitation Game, a movie describing the life of Alan Turing, considered the father of theoretical Computer Science. In 1936 Turing wrote an incredible piece of art: a paper titled On Computable Numbers, with an Application to the Entscheidungsproblem.