Abstract
We propose a novel architecture for the implementation of Cellular Automata (CA). The novel architecture is based on graphene nanoribbons with magnetic contacts, which are used as building blocks. In this CA implementation, information processing is obtained through top-gates, back-gates and the angles and magnitudes of the polarizations of the magnetic contacts. We use tight-binding Hamiltonians and non-equilibrium Green’s functions to model and simulate the operation of the building blocks of the proposed CA implementation. Interconnections are local and CA cell states can be represented using top-gate and back-gate potentials, and the angles and magnitudes of the contact polarizations. We also describe the CA evolution rules. Our results showed that this CA implementation is capable of both digital and analog information processing. Furthermore, it can be effectively used for neuromorphic and in-memory computing.
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Acknowledgement
This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme Human Resources Development, Education and Lifelong Learning 2014–2020 in the context of the project “GRAPHENE NANOELECTRONIC AND QUANTUM CIRCUITS” (MIS 5049529).
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Rallis, K., Moysidis, S., Karafyllidis, I.G. (2021). Implementation of Cellular Automata Using Graphene Nanoribbons with Magnetic Contacts. In: Gwizdałła, T.M., Manzoni, L., Sirakoulis, G.C., Bandini, S., Podlaski, K. (eds) Cellular Automata. ACRI 2020. Lecture Notes in Computer Science(), vol 12599. Springer, Cham. https://doi.org/10.1007/978-3-030-69480-7_17
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DOI: https://doi.org/10.1007/978-3-030-69480-7_17
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