Genetic-tunneling driven energy optimizer for spin systems

Abstract Finding the ground state of complex many-body systems, such as magnetic materials containing topological textures, like skyrmions, is a fundamental and long-standing problem. We present here genetic-tunneling-driven variance-controlled optimization method, that efficiently identifies two-dimensional skyrmionic systems. The approach combines local energy-minimizer backend metaheuristic global search frontend. method shown to perform significantly better than simulated annealing. Specifically, we demonstrate for Pd/Fe/Ir(111) system, our correctly experimentally observed spin spiral geometry, skyrmion lattice ferromagnetic states function external field. To knowledge, no other has until now succeeded in doing this. envision findings will pave way evolutionary computing mapping out phase diagrams systems general.