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Intrinsic Disordered Network in Multiferroic YMnO3 Single Crystals for In-Materio Physical Reservoir Computing

Muzhen Xu1, Kyoka Furuta2, Ahmet Karacali3

  • 1Research Center for Neuromorphic AI Hardware, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu, Kitakyushu, 808-0196, Japan.

Small (Weinheim an Der Bergstrasse, Germany)
|September 12, 2025
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Summary
This summary is machine-generated.

Multiferroic YMnO3 single crystals show promise for physical reservoir computing (PRC) due to their inherent nonlinearity. These materials achieve high accuracy and low power consumption in complex tasks like speech recognition.

Keywords:
YMnO3domain structurein‐materio reservoir computingphysical reservoir computingyttrium manganese oxide

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Area of Science:

  • Condensed Matter Physics
  • Materials Science
  • Computational Science

Background:

  • Physical reservoir computing (PRC) utilizes physical system nonlinearities for efficient computation.
  • Multiferroic YMnO3 exhibits intrinsic nonlinearity from its disordered domain structure, suggesting potential for PRC.
  • High-temperature functionality and tuneability are key requirements for advanced PRC systems.

Purpose of the Study:

  • To explore the potential of YMnO3 single crystals as a platform for physical reservoir computing.
  • To systematically evaluate the PRC performance of YMnO3 based on its nonlinear properties.

Main Methods:

  • Analysis of nonlinear responses, phase shifts, and high dimensionality of YMnO3.
  • Benchmark tasks including waveform generation (WG), memory capacity (MC), and NARMA2 time-series prediction.
  • Evaluation of low-power speech recognition capabilities.

Main Results:

  • YMnO3 single crystals demonstrated superior performance in benchmark PRC tasks.
  • Achieved high accuracy with remarkably low power consumption (≈1.77 µW and ≈0.02 nW/domain).
  • Successfully applied to low-power speech recognition tasks.

Conclusions:

  • YMnO3 single crystals are a viable and promising material for next-generation physical reservoir computing.
  • The material's properties address critical challenges in PRC, including efficiency and high-temperature operation.
  • This work establishes a foundation for developing advanced, functional PRC devices.