Abstract

Photorefractive materials exhibit an interesting plasticity under the influence of an optical field. By extending the finite-difference time-domain method to include the photorefractive effect, we explore how this property can be exploited in the context of neuromorphic computing for telecom applications. By first priming the photorefractive material with a random bit stream, the material reorganizes itself to better recognize simple patterns in the stream. We demonstrate this by simulating a typical reservoir computing setup, which gets a significant performance boost on performing the XOR on two consecutive bits in the stream after this initial priming step.

Highlights

  • Photorefractive materials exhibit an interesting plasticity under the influence of an optical field

  • This interplay between the charge carries in the material and the light propagating through the material make such photorefractive crystals ideal candidates for applications involving ­holography[3,4] and, as soon as these holographic properties were well understood, these crystals have been used for a variety of applications

  • The nonlinear photorefractive effect, which typically acts on a timescale of seconds is typically too slow to have any effect during inference and any charge distribution within the crystal can be considered constant during inference

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Summary

Introduction

Photorefractive materials exhibit an interesting plasticity under the influence of an optical field. Due to the Pockels effect, the varying space charge field has an influence on the refractive index of the material, which in turn will influence the propagation of the light through the crystal. This interplay between the charge carries in the material and the light propagating through the material make such photorefractive crystals ideal candidates for applications involving ­holography[3,4] and, as soon as these holographic properties were well understood, these crystals have been used for a variety of applications. The beauty of RC lies in its simplicity: the same reservoir is often used for a large number of different applications, while each time only a different readout must be found

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