Stochastic $\mathrm{\Sigma }$-convergence in Orlicz setting and Applications

This paper aims to extend the concept of stochastic $\mathrm{\Sigma }$-convergence to the framework of Orlicz-Sobolev spaces in order to deals with coupled stochastic and deterministic homogenization problems in this type of spaces. Thus, this concept is a combination of both well-known $\mathrm{\Sigma }$-convergence [$\mathit{\text{Acta}}\mathit{\text{Math.}}\mathit{\text{Sinica,}}\mathit{\text{English}}\mathit{\text{Series}}$ $\mathbf{\text{30}}$(9) 1621-1654] and stochastic two-scale convergence in the mean schemes [$\mathit{\text{Asympt.}}\mathit{\text{Anal.}}\mathit{\text{(2025)}}$ $\mathbf{\text{142}}$, 291-320]. An application to the stochastic-deterministic homogenization (in the context of ergodic $H$-supralgebra) of a class of highly oscillatory minimizations problems involving integral functionals with convex and nonstandard growth integrands is also given, and some concrete homogenization problems following varied structure hypothesis are deduce from this latter.