This research unveils a mechanism enabling linear conductance updates in neuromorphic computing, highlighting its potential for synaptic control.
From the very inception of neuromorphic computing, the quest for linear and symmetric weight updates has lingered as its most coveted yet untamed ambition. We now unveil a kinetically tuned, molecular-level mechanism that enables conductance modulation with near-ideal linearity across 16,500 analog states spanning four orders of magnitude. By orchestrating inherently nonlinear phenomena, such as nucleation, within finely controlled small-perturbation regimes, we realize what once seemed paradoxical: linearity emerging from nonlinearity. This advance offers a generalizable blueprint for instilling precise synaptic control into the very fabric of future neuromorphic materials.
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Kundu et al. (2025) studied this question.
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