Taniguchi Tomohiro
National Institute of Advanced Industrial Science and Technology (AIST), Research Center for Emerging Computing Technologies, Tsukuba, Ibaraki, 305-8568, Japan.
Sci Rep. 2025 Mar 17;15(1):9073. doi: 10.1038/s41598-025-93189-w.
Physical reservoir computing by using artificial spin ice (ASI) has been proposed on the basis of both numerical and experimental analyses. ASI is a many-body system consisting of ferromagnets with various interactions. Recently, fabricating magnetic tunnel junctions (MTJs) as ferromagnets in an ASI was achieved in the experiment, which enables an electrical detection of magnetic state of each MTJ independently. However, performing a recognition task of time-dependent signal by such an MTJ-based ASI has not been reported yet. In this work, we examine numerical simulation of a recognition task of time-dependent input and evaluate short-term memory and parity-check capacities. These capacities change significantly when the magnitude of the input magnetic field is comparable to a value around which the magnetization alignment is greatly affected by the dipole interaction. It implies that the presence of the dipole interaction results in a loss of echo state property. This point was clarified by evaluating Lyapunov exponent and confirming that the drastic change of the memory capacities appears near the boundary between negative and zero exponents, which corresponds to the edge of echo state property.
基于数值分析和实验分析，提出了利用人工自旋冰（ASI）进行物理储层计算。ASI是一个由具有各种相互作用的铁磁体组成的多体系统。最近，在实验中实现了将磁性隧道结（MTJ）制作成ASI中的铁磁体，这使得能够独立地对每个MTJ的磁状态进行电学检测。然而，尚未有基于这种MTJ的ASI执行随时间变化信号的识别任务的报道。在这项工作中，我们研究了随时间变化输入的识别任务的数值模拟，并评估了短期记忆和奇偶校验能力。当输入磁场的大小与一个值相当时，这些能力会发生显著变化，在该值附近，磁化排列受到偶极相互作用的极大影响。这意味着偶极相互作用的存在导致了回声状态特性的丧失。通过评估李雅普诺夫指数并确认记忆能力的急剧变化出现在负指数和零指数之间的边界附近，这一点得到了阐明，该边界对应于回声状态特性的边缘。
