Moire synaptic transistor for homogeneous-architecture reservoir computing
arXiv:2310.11743 · doi:10.1088/0256-307X/40/11/117201
Abstract
Reservoir computing has been considered as a promising intelligent computing paradigm for effectively processing complex temporal information. Exploiting tunable and reproducible dynamics in the single electronic device have been desired to implement the reservoir and the readout layer of reservoir computing system. Two-dimensional moire material, with an artificial lattice constant many times larger than the atomic length scale, is one type of most studied artificial quantum materials in community of material science and condensed-matter physics over the past years. These materials are featured with gate-tunable periodic potential and electronic correlation, thus varying the electric field allows the electrons in the moire potential per unit cell to exhibit distinct and reproducible dynamics, showing great promise in robust reservoir computing. Here, we report that a moire synaptic transistor can be used to implement the reservoir computing system with a homogeneous reservoir-readout architecture. The synaptic transistor is fabricated based on a h-BN/bilayer graphene/h-BN moire heterostructure, exhibiting ferroelectricity-like hysteretic gate voltage dependence of resistance. Varying the magnitude of the gate voltage enables the moire transistor to be switched between long-term memory and short-term memory with nonlinear dynamics. By employing the short- and long-term memory as the reservoir nodes and weights of the readout layer, respectively, we construct a full-moire physical neural network and demonstrate that the classification accuracy of 90.8% can be achieved for the MNIST handwritten digit database. Our work would pave the way towards the development of neuromorphic computing based on the moire materials.
References in corpus (25)
- Magic-angle graphene superlattices: a new platform for unconventional superconductivity
- Correlated Insulator Behaviour at Half-Filling in Magic Angle Graphene Superlattices
- Tuning superconductivity in twisted bilayer graphene
- Recent Advances in Physical Reservoir Computing: A Review
- Superconductors, Orbital Magnets, and Correlated States in Magic Angle Bilayer Graphene
- Optical detection of Mott and generalized Wigner crystal states in WSe2/WS2 moiré superlattices
- Stacking-engineered ferroelectricity in bilayer boron nitride
- Tunable Phase Boundaries and Ultra-Strong Coupling Superconductivity in Mirror Symmetric Magic-Angle Trilayer Graphene
- Interfacial Ferroelectricity by van-der-Waals Sliding
- Signatures of Gate-Tunable Superconductivity in Trilayer Graphene/Boron Nitride Moiré Superlattice
- Evidence of Gate-Tunable Mott Insulator in Trilayer Graphene-Boron Nitride Moiré Superlattice
- Interfacial ferroelectricity in rhombohedral-stacked bilayer transition metal dichalcogenides
- Electric field tunable unconventional superconductivity in alternating twist magic-angle trilayer graphene
- Strongly Correlated Chern Insulators in Magic-Angle Twisted Bilayer Graphene
- Physical reservoir computing -- An introductory perspective
- Nematicity and Competing Orders in Superconducting Magic-Angle Graphene
- Interfacial ferroelectricity in marginally twisted 2D semiconductors
- Continuous Mott transition in semiconductor moiré superlattices
- A magnetic skyrmion as a non-linear resistive element - a potential building block for reservoir computing
- Cumulative Polarization Coexisting with Conductivity at Interfacial Ferroelectrics
- Physical reservoir computing built by spintronic devices for temporal information processing
- Electrical switching of a moiré ferroelectric superconductor
- Tunable quantum criticalities in an isospin extended Hubbard model simulator
- Electric field-tunable layer polarization in graphene/boron nitride twisted quadrilayer superlattices
- Electronic ratchet effect in a moiré system: signatures of excitonic ferroelectricity