Spatial photonic Ising machines,as emerging artificial intelligence hardware solutions by leveraging unique physical phenomena,have shown promising results in solving large-scale combinatorial problems.However,spatial...Spatial photonic Ising machines,as emerging artificial intelligence hardware solutions by leveraging unique physical phenomena,have shown promising results in solving large-scale combinatorial problems.However,spatial light modulator enabled Ising machines still remain bulky,are very power demanding,and have poor stability.In this study,we propose an integrated XY Ising sampler based on a highly uniform multimode interferometer and a phase shifter array,enabling the minimization of both discrete and continuous spin Hamiltonians.We elucidate the performance of this computing platform in achieving fully programmable spin couplings and external magnetic fields.Additionally,we successfully demonstrate the weighted full-rank Ising model with a linear dependence of 0.82 and weighted MaxCut problem solving with the proposed sampler.Our results illustrate that the developed structure has significant potential for larger-scale,reduced power consumption and increased operational speed,positioning it as a versatile platform for commercially viable high-performance samplers of combinatorial optimization problems.展开更多
基金National Natural Science Foundation of China(62175146,62235011)。
文摘Spatial photonic Ising machines,as emerging artificial intelligence hardware solutions by leveraging unique physical phenomena,have shown promising results in solving large-scale combinatorial problems.However,spatial light modulator enabled Ising machines still remain bulky,are very power demanding,and have poor stability.In this study,we propose an integrated XY Ising sampler based on a highly uniform multimode interferometer and a phase shifter array,enabling the minimization of both discrete and continuous spin Hamiltonians.We elucidate the performance of this computing platform in achieving fully programmable spin couplings and external magnetic fields.Additionally,we successfully demonstrate the weighted full-rank Ising model with a linear dependence of 0.82 and weighted MaxCut problem solving with the proposed sampler.Our results illustrate that the developed structure has significant potential for larger-scale,reduced power consumption and increased operational speed,positioning it as a versatile platform for commercially viable high-performance samplers of combinatorial optimization problems.
