Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147857
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dc.contributor.authorGo, Michaelen_US
dc.date.accessioned2021-04-18T14:03:11Z-
dc.date.available2021-04-18T14:03:11Z-
dc.date.issued2021-
dc.identifier.citationGo, M. (2021). Exciton-polariton multilayered neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147857en_US
dc.identifier.urihttps://hdl.handle.net/10356/147857-
dc.description.abstractExciton-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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectScience::Physics::Optics and lighten_US
dc.titleExciton-polariton multilayered neural networksen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLiew Chi Hin Timothyen_US
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.description.degreeBachelor of Science in Physicsen_US
dc.contributor.supervisoremailTimothyLiew@ntu.edu.sgen_US
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Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)
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