Impact of filtering on photonic time-delay reservoir computing

Abstract

We analyze the modification of the computational properties of a time-delay photonic reservoir computer with a change in its feedback bandwidth. For a reservoir computing configuration based on a semiconductor laser subject to filtered optoelectronic feedback, we demonstrate that bandwidth selection can lead to a flat-topped eigenvalue spectrum for which a large number of system frequencies are weakly damped as a result of the attenuation of modulational instability by feedback filtering. This spectral configuration allows for the optimization of the reservoir in terms of its memory capacity, while its computational ability appears to be only weakly affected by the characteristics of the filter.

Exploring physical and digital architectures in magnetic nanoring array reservoir computers

“…While the task-independent metrics KR, GR, and CQ provide a good means for comparing between similar reservoir initialisations, many design choices and experimental factors can make direct comparisons between different devices difficult. For example, past studies have shown stark differences between calculated metrics for nominally similar nodes depending upon their input/and output granularity from binary to analogue input/outputs [24], the filtering of noise [33], or the number of output nodes which acts as a hard bound for KR and GR [25]. However, to provide context, the 'peak' metric scores listed here (32 output nodes for SSR, 50 for SDN/RNR, all analogue inputs and outputs) can be tentatively compared with simulations of spintronic systems in the literature, such as a CQ of 7 for spin-wave interference based RC with 20 nodes with analogue input/output [34], and a CQ of 130 for an artificial spin ice with 220 nodes for binary inputs but analogue readouts [27].…”