Speaker: Weichao Yu
Title: Intelligent magnetic textures
Abstract: Macroscopic spin ensembles with brain-like features, such as nonlinearity, stochasticity, self-oscillations, memory effects and plasticity, form attractive platforms for neuromorphic computing. We propose an artificial neural network, consisting of electric contacts on conducting films with tunable magnetic textures, that is superior to conventional implementations, because it does not require resource-demanding external computations during training. Simulations show that the feedback between anisotropic magnetoresistance and current-induced spin-transfer torque in malleable magnetic textures autonomously trains the network according to the Hebbian learning principle. We illustrate the idea by simulating the pattern recognition by a four-node Hopfield neural network.
2009–2013: Bachelor's degree of Science, Tongji University, Shanghai, China
2013–2019: PhD and PostDoc, Fudan University, Shanghai China
2019–2021: Assistant Professor, Institute for Materials Research, Tohoku University, Sendai, Japan
2021–now: Associate Professor, Institute for Nanoelectronic devices and Quantum computing, Fudan University, Shanghai, China
See email invitation for Zoom and venue details. Many thanks to Jeremy Bourhill for organising.
The Australian Research Council Centre of Excellence for Engineered Quantum Systems (EQUS) acknowledges the Traditional Owners of Country throughout Australia and their continuing connection to lands, waters and communities. We pay our respects to Aboriginal and Torres Strait Islander cultures and to Elders past and present.