Reservoir Computing with Nanowire Exchange-Coupled Spin Torque Oscillator Arrays

TY - GEN

T1 - Reservoir Computing with Nanowire Exchange-Coupled Spin Torque Oscillator Arrays

AU - Dale, Matt

AU - Evans, Richard F.L.

AU - Sebald, Angelika

AU - Stepney, Susan

N1 - Funding Information: Acknowledgements. The author acknowledges the emmy.network foundation under the aegis of the Fondation de Luxembourg for its financial support. Funding Information: This research was partially supported by the National Science Foundation SEALS grant DMS-1362273. The work was done partially while the latter two authors were visiting the Institute for Mathematical Sciences, National University of Singapore, in 2017. The visits were supported by the Institute. This material is partially based upon work supported by the National Science Foundation under grant DMS-1928930 while all three authors participated in a program hosted by the Mathematical Sciences Research Institute in Berkeley, California during the Fall 2020 semester. Harizanov was partially supported by the Simons Foundation grant 853762 and NSF grant DMS-2152095. Funding Information: Acknowledgements. This work was supported by JSPS KAKENHI Grant Numbers JP21H05052, JP21K11881, and JST, CREST Grant Number JPMJCR22M1, Japan. Funding Information: Acknowledgements. MD, SS, and AS acknowledge funding from the SpInspired project, EPSRC grant EP/R032823/1. We thank Jed Bye for performing the preliminary coupling simulations of Sect. 2.2. All experiments were carried out using the University of York’s Super Advanced Research Computing Cluster (Viking). Funding Information: Acknowledgements. This research was partially supported by SYNCH project funded by the European Commission under the H2020 FET Proactive programme (Grant agreement ID: 824162) and by the CHIST-ERA grant CHIST-ERA-18-ACAI-004, by the Austrian Science Fund (FWF) project number I 4670-N (project SMALL). Funding Information: Acknowledgments. The authors wish to thank Chalres Vidamour for sharing insight into challenges of the fabrication process of the magnetic ring arrays used in prior work [17]. DG and SS acknowledge funding from the MARCH project, EPSRC grant numbers EP/V006029/1 and EP/V006339/1. IV acknowledges a DTA-funded PhD studentship from EPSRC. Funding Information: Acknowledgement. This work was made possible by PhD studentship funding from the Computer Science Department of the University of York. Funding Information: in part by National Science Foundation Grant CCF- Funding Information: This research was partially supported by the National Science Foundation SEALS grant DMS-1362273. Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PY - 2023/6/1

Y1 - 2023/6/1

N2 - Spin torque oscillators (STOs) feature transient non-linear behaviour that can be exploited for computation. When combined in arrays, they can be networked to produce more complex collective behaviours than single devices alone. We simulate a physical reservoir computer comprising an array of STOs, using a macro spin approximation. We demonstrate that STOs can be networked together in arrays using nanowires, and that by altering the properties of these nanowires we can optimise the magnetic exchange coupling between the oscillators for computational purposes. We train a simulated array of coupled oscillators to compute various time-independent and time-dependent benchmark tasks. We explore the effects of array size, heterogeneous coupling, and connection topologies. We demonstrate the computational potential of programming the exchange coupling in arrays of oscillators through nanowires.

AB - Spin torque oscillators (STOs) feature transient non-linear behaviour that can be exploited for computation. When combined in arrays, they can be networked to produce more complex collective behaviours than single devices alone. We simulate a physical reservoir computer comprising an array of STOs, using a macro spin approximation. We demonstrate that STOs can be networked together in arrays using nanowires, and that by altering the properties of these nanowires we can optimise the magnetic exchange coupling between the oscillators for computational purposes. We train a simulated array of coupled oscillators to compute various time-independent and time-dependent benchmark tasks. We explore the effects of array size, heterogeneous coupling, and connection topologies. We demonstrate the computational potential of programming the exchange coupling in arrays of oscillators through nanowires.

UR - http://www.scopus.com/inward/record.url?scp=85173569651&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-34034-5_5

DO - 10.1007/978-3-031-34034-5_5

M3 - Conference contribution

AN - SCOPUS:85173569651

SN - 9783031340338

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 64

EP - 78

BT - Unconventional Computation and Natural Computation - 20th International Conference, UCNC 2023, Proceedings

A2 - Genova, Daniela

A2 - Kari, Jarkko

PB - Springer Science and Business Media Deutschland GmbH

T2 - 20th International Conference on Unconventional Computation and Natural Computation, UCNC 2023

Y2 - 13 March 2023 through 17 March 2023

ER -