Abstract
Finding the ground states of the Ising model is a classical example for non-deterministic polynomial-time (NP)-hard problems [1], and maps to various combinatorial optimization problems in many fields, for which no efficient classical or quantum algorithm is known. An alternative computing approach for these problems is to use an Ising machine, i.e. an artificial Ising spin system that can simulate arbitrary Ising models, which is expected to converge to a ground state in a successful computation run. A configurable network of degenerate optical parametric oscillators (OPOs) is a promising Ising machine that is expected to simulate arbitrary Ising models and find their absolute or approximate ground states in a reasonably short time [2, 3],
© 2015 IEEE
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