Reservoir computing is an analog bio-inspired computation model for efficiently processing time-dependent signals, the photonic implementations of which promise a combination of massive parallel information processing, low power consumption, and high speed operation. However, most implementations, especially for the case of time-delay reservoir computing (TDRC), require signal attenuation in the reservoir to achieve the desired system dynamics for a specific task, often resulting in large amounts of power being coupled outside of the system. We propose a novel TDRC architecture based on an asymmetric Mach-Zehnder interferometer (MZI) integrated in a resonant cavity which allows the memory capacity of the system to be tuned without the need for an optical attenuator block. Furthermore, this can be leveraged to find the optimal value for the specific components of the total memory capacity metric. We demonstrate this approach on the temporal bitwise XOR task and conclude that this way of memory capacity reconfiguration allows optimal performance to be achieved for memory-specific tasks.

翻译：储层计算是一种用于高效处理时间依赖信号的模拟生物启发计算模型，其光子实现有望兼具大规模并行信息处理、低功耗和高速运行等优势。然而，大多数实现方案（尤其是基于时间延迟的储层计算（TDRC））需要在储层中对信号进行衰减，以达到特定任务所需的系统动力学特性，这往往导致大量能量被耦合至系统外部。我们提出一种基于集成在谐振腔内的非对称马赫-曾德尔干涉仪（MZI）的新型TDRC架构，该架构可在无需光衰减器模块的情况下实现系统记忆容量的调谐。此外，这一特性可被用于为总记忆容量度量的特定分量寻找最优值。我们在时域按位XOR任务上验证了该方法，并得出结论：这种记忆容量重构方式能够为记忆特定任务实现最优性能。