Martínez-Peña Rodrigo, Giorgi Gian Luca, Nokkala Johannes, Soriano Miguel C, Zambrini Roberta
Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC, UIB-CSIC), Campus Universitat de les Illes Balears, E-07122 Palma de Mallorca, Spain.
Phys Rev Lett. 2021 Sep 3;127(10):100502. doi: 10.1103/PhysRevLett.127.100502.
Closed quantum systems exhibit different dynamical regimes, like many-body localization or thermalization, which determine the mechanisms of spread and processing of information. Here we address the impact of these dynamical phases in quantum reservoir computing, an unconventional computing paradigm recently extended into the quantum regime that exploits dynamical systems to solve nonlinear and temporal tasks. We establish that the thermal phase is naturally adapted to the requirements of quantum reservoir computing and report an increased performance at the thermalization transition for the studied tasks. Uncovering the underlying physical mechanisms behind optimal information processing capabilities of spin networks is essential for future experimental implementations and provides a new perspective on dynamical phases.
封闭量子系统表现出不同的动力学状态，如多体局域化或热化，这些状态决定了信息传播和处理的机制。在此，我们探讨这些动力学相在量子储层计算中的影响，量子储层计算是一种非常规计算范式，最近已扩展到量子领域，它利用动力系统来解决非线性和时间任务。我们确定热相自然地适应了量子储层计算的要求，并报告了在所研究任务的热化转变处性能有所提高。揭示自旋网络最佳信息处理能力背后的潜在物理机制对于未来的实验实现至关重要，并为动力学相提供了新的视角。
