Xu Xiao-Yun, Huang Xuan-Lun, Li Zhan-Ming, Gao Jun, Jiao Zhi-Qiang, Wang Yao, Ren Ruo-Jing, Zhang H P, Jin Xian-Min
Center for Integrated Quantum Information Technologies (IQIT), School of Physics and Astronomy and State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, Shanghai 200240, China.
CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei 230026, China.
Sci Adv. 2020 Jan 31;6(5):eaay5853. doi: 10.1126/sciadv.aay5853. eCollection 2020 Jan.
The subset sum problem (SSP) is a typical nondeterministic-polynomial-time (NP)-complete problem that is hard to solve efficiently in time with conventional computers. Photons have the unique features of high propagation speed, strong robustness, and low detectable energy level and therefore can be promising candidates to meet the challenge. Here, we present a scalable chip built-in photonic computer to efficiently solve the SSP. We map the problem into a three-dimensional waveguide network through a femtosecond laser direct writing technique. We show that the photons sufficiently dissipate into the networks and search for solutions in parallel. In the case of successive primes, our approach exhibits a dominant superiority in time consumption even compared with supercomputers. Our results confirm the ability of light to realize computations intractable for conventional computers, and suggest the SSP as a good benchmarking platform for the race between photonic and conventional computers on the way toward "photonic supremacy."
子集和问题(SSP)是一个典型的非确定性多项式时间(NP)完全问题,用传统计算机很难在规定时间内有效解决。光子具有传播速度快、鲁棒性强和可检测能量水平低等独特特性,因此有望成为应对这一挑战的候选者。在此,我们展示了一种可扩展的片上光子计算机,用于高效解决子集和问题。我们通过飞秒激光直写技术将该问题映射到三维波导网络中。我们证明光子能够充分耗散到网络中并并行搜索解决方案。在连续素数的情况下,即使与超级计算机相比,我们的方法在时间消耗上也具有显著优势。我们的结果证实了光实现传统计算机难以处理的计算的能力,并表明子集和问题是光子计算机与传统计算机在迈向“光子霸权”竞赛中的一个良好基准平台。