Takata Kenta, Marandi Alireza, Hamerly Ryan, Haribara Yoshitaka, Maruo Daiki, Tamate Shuhei, Sakaguchi Hiromasa, Utsunomiya Shoko, Yamamoto Yoshihisa
ImPACT, Japan Science and Technology Agency, Gobancho 7, Chiyoda-ku, Tokyo 102-0076, Japan.
National Institute of Informatics, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8403, Japan.
Sci Rep. 2016 Sep 23;6:34089. doi: 10.1038/srep34089.
Many tasks in our modern life, such as planning an efficient travel, image processing and optimizing integrated circuit design, are modeled as complex combinatorial optimization problems with binary variables. Such problems can be mapped to finding a ground state of the Ising Hamiltonian, thus various physical systems have been studied to emulate and solve this Ising problem. Recently, networks of mutually injected optical oscillators, called coherent Ising machines, have been developed as promising solvers for the problem, benefiting from programmability, scalability and room temperature operation. Here, we report a 16-bit coherent Ising machine based on a network of time-division-multiplexed femtosecond degenerate optical parametric oscillators. The system experimentally gives more than 99.6% of success rates for one-dimensional Ising ring and nondeterministic polynomial-time (NP) hard instances. The experimental and numerical results indicate that gradual pumping of the network combined with multiple spectral and temporal modes of the femtosecond pulses can improve the computational performance of the Ising machine, offering a new path for tackling larger and more complex instances.
我们现代生活中的许多任务,如规划高效旅行、图像处理和优化集成电路设计,都被建模为具有二进制变量的复杂组合优化问题。此类问题可映射为寻找伊辛哈密顿量的基态,因此人们研究了各种物理系统来模拟和解决这个伊辛问题。最近,相互注入光振荡器网络,即相干伊辛机,已被开发成为解决该问题的有前途的求解器,受益于可编程性、可扩展性和室温操作。在此,我们报告一种基于时分复用飞秒简并光学参量振荡器网络的16位相干伊辛机。该系统在实验上对于一维伊辛环和非确定性多项式时间(NP)难实例给出了超过99.6%的成功率。实验和数值结果表明,对网络进行逐步泵浦并结合飞秒脉冲的多个光谱和时间模式,可以提高伊辛机的计算性能,为解决更大、更复杂的实例提供了一条新途径。