Publication
CLEO/Europe-EQEC 2019
Conference paper

Non-volatile photonic weights and their impact on photonic reservoir computing systems

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Abstract

Reservoir computing (RC) is a promising implementation of a non-von Neumann computing architecture. It is well-suited to solve time-dependent and dynamic problems like speech recognition or bitwise operations [1]. In principal integrated photonic RC offers energy-efficient, high-speed signal processing capabilities [1,2]. However, current photonic RC systems perform the linear combination of the complex reservoir states in software. Software weights are ideal (high precision, no drift), but limit the processing speed and energy efficiency of the RC system [2]. Here, we discuss a hardware implementation of photonic weights compatible with silicon photonic RC architectures. First, we demonstrate non-volatile synaptic weights based on ferroelectric barium titanate (BTO) thin films. Second, we explore how imperfections in these hardware weights impact the reservoir performance.

Date

01 Jun 2019

Publication

CLEO/Europe-EQEC 2019

Authors

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