Reconfigurable integrated photonic processor for NP-complete problems
Xiao-Yun Xu, Tian-Yu Zhang, Ziwei Wang +2 more
Nondeterministic-polynomial-time (NP)-complete problems are widely involved in various real-life scenarios but are still intractable in being solved efficiently on conventional computers. It is of great practical significance to construct versatile computing architectures that solve NP-complete problems with computational advantage. Here, we present a reconfigurable integrated photonic processor to efficiently solve a benchmark NP-complete problem, the subset sum problem. We show that in the case of successive primes, the photonic processor has genuinely surpassed electronic processors launched recently by taking advantage of the high propagation speed and vast parallelism of photons and state-of-the-art integrated photonic technology. Moreover, we are able to program the photonic processor to tackle different problem instances, relying on the tunable integrated modules, variable split junctions, which can be used to build a fully reconfigurable architecture potentially allowing 2N configurations at most. Our experiments confirm the potential of the photonic processor as a versatile and efficient computing platform, suggesting a possible practical route to solving computationally hard problems at a large scale.
Advanced Photonics•Sep 24, 2024•11 citations