Abstract
One of the challenges for reservoir computing is the robustness of the implementation in the face of fabrication error. If a system is too sensitive to fabrication error, then each manufactured reservoir becomes a unique artefact with unique computational properties. Under most circumstances, this is undesirable as it makes reproduction of results, or useful systems, complicated. This paper uses simulation to examine the properties of nano-scale magnetic ring arrays as reservoir computers under parameters corresponding to a wide variety of physically derived parameters, and investigates the effectiveness of linear field calibration to minimise the difference in unexpected behaviour of the systems.
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Notes
- 1.
This differs from controlled behaviours, which under normal circumstances it is desirable to have as many different types of behaviour as possible.
- 2.
For brevity some details, such as penalty terms on selecting the partition to explore that ensure that all areas of the behaviour space are explored rather than focusing on a infinitesimally small but interesting area, are omitted.
- 3.
These limits are somewhat arbitrary, but approximately reflect the limitations of the current physical implementation with regard to sustained magnetic fields.
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Acknowledgments
The authors wish to thank Chalres Vidamour for sharing insight into challenges of the fabrication process of the magnetic ring arrays used in prior work [17]. DG and SS acknowledge funding from the MARCH project, EPSRC grant numbers EP/V006029/1 and EP/V006339/1. IV acknowledges a DTA-funded PhD studentship from EPSRC.
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Griffin, D., Stepney, S., Vidamour, I. (2023). Exploring the Robustness of Magnetic Ring Arrays Reservoir Computing with Linear Field Calibration. In: Genova, D., Kari, J. (eds) Unconventional Computation and Natural Computation. UCNC 2023. Lecture Notes in Computer Science, vol 14003. Springer, Cham. https://doi.org/10.1007/978-3-031-34034-5_7
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