https://doi.org/10.1140/epjp/s13360-023-03649-3
Regular Article
Towards single atom computing via high harmonic generation
1
Tulane University, 70118, Mew Orleans, LA, USA
2
United States Army Research Laboratory, 20783, Adelphi, MD, USA
3
Department of Physics, University of Massachusetts at Boston, 02125, Boston, MA, USA
Received:
11
August
2022
Accepted:
1
January
2023
Published online:
5
February
2023
The development of alternative platforms for computing has been a longstanding goal for physics, and represents a particularly pressing concern as conventional transistors approach the limit of miniaturization. A potential alternative paradigm is that of reservoir computing, which leverages unknown, but highly nonlinear transformations of input-data to perform computations. This has the advantage that many physical systems exhibit precisely the type of nonlinear input-output relationships necessary for them to function as reservoirs. Consequently, the quantum effects which obstruct the further development of silicon electronics become an advantage for a reservoir computer. Here we demonstrate that even the most basic constituents of matter–atoms–can act as a reservoir for computing where all input-output processing is optical, thanks to the phenomenon of High Harmonic Generation. A prototype single-atom computer for classification problems is proposed, where a classification model is mapped to an all-optical setup, with linear filters chosen to correspond to the trained model’s parameters. We numerically demonstrate that this ‘all-optical’ computer can successfully perform classification tasks, and does so with an accuracy that is strongly dependent on dynamical nonlinearities. This may pave the way for the development of petahertz information processing platforms.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023. corrected publication 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
