Many real life problems are combinatorial and solving them has actual practical applications. An intrinsic feature of these problems is that they can be formulated as minimization or maximization problems, i.e. with a cost function. At the same time finding the lowest energy of a physical system, represented by a cost Hamiltonian, is also a minimization problem. Due to this intimate relation, problems described with a cost function (QUBO) or a cost Hamiltonian (Ising) could be solved by simulating the process of finding their minimum energy. This lowest energy should encode the solution to our problem.