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All-to-All Connected Oscillator Networks for Solving Combinatorial Optimization Problems

机译:用于解决组合优化问题的全面连接振荡器网络

摘要

An analog computing system with coupled non-linear oscillators can solve complex combinatorial optimization problems using the weighted Ising model. The system is composed of a fully-connected LC oscillator network with low-cost electronic components and compatible with traditional integrated circuit technologies. Each LC oscillator, or node, in the network can be coupled to each other node in the array with a multiply and accumulate crossbar array or optical interconnects. When implemented with four nodes, the system performs with single-run ground state accuracies of 98% on randomized MAX-CUT problem sets with binary weights and 84% with five-bit weight resolutions. The four-node system can obtain solutions within five oscillator cycles with a time-to-solution that scales directly with oscillator frequency. A scaling analysis suggests that larger coupled oscillator networks may be used to solve computationally intensive problems faster and more efficiently than conventional algorithms.
机译:具有耦合非线性振荡器的模拟计算系统可以使用加权ising模型解决复杂的组合优化问题。该系统由具有低成本电子元件的完全连接的LC振荡器网络组成,并与传统的集成电路技术兼容。网络中的每个LC振荡器或节点可以耦合到阵列中的彼此节点,其中乘法累积横杆阵列或光互连。当用四个节点实现时,系统在随机的最大切割问题集中以98%的单次接地状态精度执行,其中二进制权重和84%具有五位重量分辨率。四节点系统可以在五个振荡器周期内获得解决方案,该振荡器周期与振荡器频率直接缩放的时间。缩放分析表明,较大的耦合振荡器网络可以用于比传统算法更快且更高效地解决计算密集型问题。

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