The rapidity and low power consumption of superconducting electronics makes them an ideal substrate for physical reservoir computing, which commandeers the computational power inherent to the evolution of a dynamical system for the purposes of performing machine learning tasks. We focus on a subset of superconducting circuits that exhibit soliton-like dynamics in simple transmission line geometries. With numerical simulations we demonstrate the effectiveness of these circuits in performing higher-order parity calculations and channel equalization at rates approaching 100 Gb/s. The availability of a proven superconducting logic scheme considerably simplifies the path to a fully integrated reservoir computing platform and makes superconducting reservoirs an enticing substrate for high rate signal processing applications.

翻译：超导电子的快速和低功率消耗使超导电子成为物理储油层计算的理想基数,这种基数控制了为完成机器学习任务而演进动态系统所固有的计算能力。我们侧重于在简单的传输线地理特征中显示类似苏立特动态的一组超导电路。通过数字模拟,我们展示了这些电路在以接近100千兆字节/秒的速率进行较高级对等计算和引导均分方面的有效性。一个经证明的超导逻辑方法的可用性极大地简化了通往完全一体化储油层计算平台的道路,并使超导电路成为高速信号处理应用的诱导基。