Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147857
Title: Exciton-polariton multilayered neural networks
Authors: Go, Michael
Keywords: Science::Physics::Optics and light
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Go, M. (2021). Exciton-polariton multilayered neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147857
Abstract: Exciton-polaritons are hybrid light-matter quasiparticles. Being such hybrid, they inherit the fast dynamics of light and strong nonlinearities of matter. Nonlinearity is essential for neural network models to solve high complexity tasks. Thus, excitonpolaritons are believed to be a promising platform for realising high throughput neural network hardware. In this thesis, we present a theoretical scheme for multilayered neural network realization using exciton-polaritons. We then demonstrate the system’s ability to emulate multilayer perceptron and solve the nonlinear XOR problem.
URI: https://hdl.handle.net/10356/147857
Schools: School of Physical and Mathematical Sciences 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

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