用不同尺寸纳米点组合，让储层计算在5-35°C下性能稳定，不惧温度变化。想了解新型低功耗计算硬件的人可以看看。
这篇论文研究了超顺磁纳米点集合在储层计算中的温度敏感性。由于系统动力学受热激活效应支配，环境温度波动会降低任务性能。通过模拟发现，引入不同尺寸纳米点的异质图案可稳定性能。在NARMA-10基准任务上，优化异质性使储层在5-35°C范围内性能稳定。研究还揭示了性能与温度稳定性之间的可调权衡。
Reproducible Reservoir Computing with Thermally Driven Superparamagnets: Controlling Temperature Sensitivity
Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We have recently proposed superparamagnetic nanodot ensembles driven by strain-induced magnetoelectric coupling as exciting candidates for use as ultra-low energy consumption reservoir computing substrates. However, because their dynamics are governed by thermal activation effects, these systems are intrinsically sensitive to ambient temperature fluctuations, leading to degraded task performance when operated outside the temperature range used during training. In this paper we simulate how temperature variations affect the magnetization dynamics of such superparamagnetic ensembles, and quantify how this affects task performance. We then show how heterogeneous nanodot patterns that incorporate different sizes of nanodots with different characteristic timescales for thermal activation mitigate this problem. Benchmark results on the NARMA-10 task show that introducing optimized heterogeneity stabilizes performance of the reservoirs across a wide range of ambient temperatures (5-35°C), with little loss of ultimate performance. We also characterize the trade-off between performance and temperature stability and show that it can be tuned via reservoir hyperparameters. Our study demonstrates a key step in making these novel devices suitable for real-world deployment.