Digital MemComputing machines (DMMs), which employ nonlinear dynamical systems with memory (time non-locality), have proven to be a robust and scalable unconventional computing approach for solving a wide variety of combinatorial optimization problems. However, most of the research so far has focused on the numerical simulations of the equations of motion of DMMs. This inevitably subjects time to discretization, which brings its own (numerical) issues that would be absent in actual physical systems operating in continuous time. Although hardware realizations of DMMs have been previously suggested, their implementation would require materials and devices that are not so easy to integrate with traditional electronics. In this study, we propose a novel hardware design for DMMs that leverages only conventional electronic components. Our findings suggest that this design offers a marked improvement in speed compared to existing realizations of these machines, without requiring special materials or novel device concepts. Moreover, the absence of numerical noise promises enhanced stability over extended periods of the machines' operation, paving the way for addressing even more complex problems.

翻译：数字记忆计算（Digital MemComputing）机器（DMMs）采用具有记忆（时间非局域性）的非线性动力学系统，已被证明是一种稳健且可扩展的非常规计算方法，适用于解决各类组合优化问题。然而，迄今为止的大多数研究聚焦于DMMs运动方程的数值模拟。这不可避免地需要对时间进行离散化处理，而离散化会引入实际连续时间物理系统所不存在的（数值）问题。尽管此前已有研究提出DMMs的硬件实现方案，但其实现需要难以与传统电子器件集成的材料与设备。在本研究中，我们提出一种仅利用常规电子元件的DMMs新型硬件设计。我们的研究结果表明，相较于现有DMMs实现方案，该设计在速度上具有显著提升，且无需特殊材料或新型器件概念。此外，数值噪声的消除有望增强系统在长时间运行中的稳定性，为应对更复杂的问题铺平道路。