Reservoir Computing with Superconducting Electronics

03/03/2021
by   Graham E. Rowlands, et al.
0

The rapidity and low power consumption of superconducting electronics makes them an ideal substrate for physical reservoir computing, which commandeers the computational power inherent to the evolution of a dynamical system for the purposes of performing machine learning tasks. We focus on a subset of superconducting circuits that exhibit soliton-like dynamics in simple transmission line geometries. With numerical simulations we demonstrate the effectiveness of these circuits in performing higher-order parity calculations and channel equalization at rates approaching 100 Gb/s. The availability of a proven superconducting logic scheme considerably simplifies the path to a fully integrated reservoir computing platform and makes superconducting reservoirs an enticing substrate for high rate signal processing applications.

READ FULL TEXT
research
02/23/2018

Reservoir computing with simple oscillators: Virtual and real networks

The reservoir computing scheme is a machine learning mechanism which uti...
research
12/20/2022

Hopf Physical Reservoir Computer for Reconfigurable Sound Recognition

The Hopf oscillator is a nonlinear oscillator that exhibits limit cycle ...
research
03/16/2021

Frustrated Arrays of Nanomagnets for Efficient Reservoir Computing

We simulated our nanomagnet reservoir computer (NMRC) design on benchmar...
research
06/16/2020

Higher-Order Quantum Reservoir Computing

Quantum reservoir computing (QRC) is an emerging paradigm for harnessing...
research
08/31/2020

The Computational Capacity of Memristor Reservoirs

Reservoir computing is a machine learning paradigm in which a high-dimen...
research
10/08/2018

Training Passive Photonic Reservoirs with Integrated Optical Readout

As Moore's law comes to an end, neuromorphic approaches to computing are...
research
05/19/2023

Energy-efficient memcapacitive physical reservoir computing system for temporal data processing

Reservoir computing is a highly efficient machine learning framework for...

Please sign up or login with your details

Forgot password? Click here to reset