Cheamsawat Krai, Chotibut Thiparat
Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Entropy (Basel). 2025 Jan 18;27(1):88. doi: 10.3390/e27010088.
Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet, identifying the mechanisms that underlie enhanced performance remains challenging, particularly in many-body open systems where nonlinear interactions and dissipation intertwine in complex ways. Here, we investigate a minimal model of a driven-dissipative quantum reservoir described by two coupled Kerr-nonlinear oscillators, an experimentally realizable platform that features controllable coupling, intrinsic nonlinearity, and tunable photon loss. Using Partial Information Decomposition (PID), we examine how different dynamical regimes encode input drive signals in terms of (information shared by each oscillator) and (information accessible only through their joint observation). Our key results show that, near a critical point marking a dynamical bifurcation, the system transitions from predominantly redundant to synergistic encoding. We further demonstrate that synergy amplifies short-term responsiveness, thereby enhancing immediate memory retention, whereas strong dissipation leads to more redundant encoding that supports long-term memory retention. These findings elucidate how the interplay of instability and dissipation shapes information processing in small quantum systems, providing a fine-grained, information-theoretic perspective for analyzing and designing QRC platforms.
量子储层计算（QRC）已成为一种很有前景的范式，用于利用近期量子设备来处理时间机器学习任务。然而，确定性能提升背后的机制仍然具有挑战性，特别是在多体开放系统中，非线性相互作用和耗散以复杂的方式交织在一起。在这里，我们研究了一个由两个耦合的克尔非线性振荡器描述的驱动耗散量子储层的最小模型，这是一个实验上可实现的平台，具有可控耦合、固有非线性和可调光子损失。使用部分信息分解（PID），我们研究了不同的动力学区域如何根据（每个振荡器共享的信息）和（仅通过它们的联合观测可访问的信息）对输入驱动信号进行编码。我们的关键结果表明，在标志着动力学分岔的临界点附近，系统从主要的冗余编码转变为协同编码。我们进一步证明，协同作用放大了短期响应能力，从而增强了即时记忆保留，而强耗散导致更多的冗余编码，支持长期记忆保留。这些发现阐明了不稳定性和耗散的相互作用如何塑造小量子系统中的信息处理，为分析和设计QRC平台提供了一个细粒度的、信息论的视角。
