Results 181 to 190 of about 128,537,122 (247)

Q‐LEAP: Millisecond Hyperdimensional Optimization for Full‐Spectrum Optical Metamaterials

open access: yesAdvanced Science, EarlyView.
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Zikang Guo   +3 more
wiley   +1 more source

Morphology‐Defined Entropy Streams for Random‐Bit Generation and Probabilistic Sampling in Memristor Arrays

open access: yesAdvanced Science, EarlyView.
Au nanoisland morphology defines stochastic high‐resistance‐state transport in Ag/TiO2 memristor arrays, transforming nanoscale structural disorder into a tunable physical entropy resource. Morphology‐controlled field hotspots and reset‐modulated nanogaps generate statistically validated random‐bit streams, which further serve as device‐derived ...
Hyunjun Kim   +5 more
wiley   +1 more source

Analytical Prediction of Critical Transitions in Oscillator Networks With Non‐Local Links

open access: yesAdvanced Science, EarlyView.
An analytical framework reveals how global coupling, second‐harmonic strength, noise, and network structure govern oscillator‐based Ising dynamics. Spectral reduction predicts stability boundaries, while Fokker–Planck analysis captures one‐ to two‐cluster transitions and identifies conditions favoring low‐energy configurations.
Qiang Li   +5 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez   +10 more
wiley   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels   +4 more
wiley   +1 more source

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