Reservoir computing with magnons – ANR MARIN Project
Project coordinated by C2N – Center for Nanosciences and Nanotechnologies
Whether on the surface of a lake, in the colorful patterns of atmospheric halos and coronas, or in the form of fringes in optical or gravitational waves, wave interference is a phenomenon that plays an important role in our daily lives. It enables us to tackle the most complex questions.
But what about the computations? Suppose we take a bucket of water and drop a series of pebbles of different weights into it. By observing the resulting interference patterns—which contain information about past and present events—can we deduce the original sequence of these pebbles? And the answer is yes!
It is known that the interference of water waves can be an effective mechanism for a “liquid state machine,” an example of the neuro-inspired paradigm of reservoir computing. Here, the pebbles represent a complex temporal waveform, such as a speech signal; to recognize such signals, one must know not only the constituent frequencies but also the order in which they arrive. This project proposes using spin waves—elementary excitations of magnetic systems—as a new implementation of reservoir computing at the submicron scale.
Due to their intrinsic nonlinearities and their ability to interact with transport phenomena, there are plans to perform advanced pattern recognition tasks in magnonic devices operating at frequencies in the GHz range.
This MARIN ANR project therefore aims to experimentally build such a magnonic reservoir computer.