Discrete Polynomial Optimization with Coherent Networks of Condensates and Complex Coupling Switching

Abstract

Gain-dissipative platforms consisting of lasers, optical parametric oscillators and nonequilibrium condensates operating at the condensation/coherence threshold have been recently proposed as efficient analog simulators of 2-local spin Hamiltonians with continuous or discrete degrees of freedom. We show that nonequilibrium condensates above the threshold arranged in an interacting network may realise k-local Hamiltonians with k>2 and lead to nontrivial phase configurations. The principle of the operation of such a system lays the ground for physics-inspired computing and the new efficient methods for finding solutions to the higher order binary optimization problems. We show how to facilitate the search for the global solution by invoking complex couplings in the system and demonstrate the efficiency of the method on tensors with million entries. This approach offers a highly flexible new kind of computation based on gain-dissipative simulators with complex coupling switching. g.