Monte Carlo methods:
Classical spins systems can reveal a lot about a particular system. Monte Carlo is a method that can be applied to a vast number of systems, even those beyond the local interactions where tensor networks are best applied.
The strategy we use is to compute many independent (with some interaction between) threads in order to achieve better precision with our methods.
Mainly we apply Monte Carlo onto classical spin systems, sometimes for materials considerations:
C. Gauvin-Ndiaye, T.E. Baker, P. Karan, E. Massé, M. Balli, N. Brahiti, M.A. Eskandari, P. Fournier, A.M.S. Tremblay, and R. Nourafkan, "Electronic and magnetic properties of the candidate magnetocaloric-material double perovskites La2MnCoO6, La2MnNiO6, and La2MnFeO6" Phys. Rev. B 98, 125132 (2018) [online] [pdf] [bibtex]
T.E. Baker, "Selecting initial states from Genetic Tempering for efficient Monte Carlo sampling" [online] [arXiv:1801.0937] [pdf] [bibtex]