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.Bachelor of Science in Physic
Neuromorphic models are proving capable of performing complex machine learning tasks, overcoming the...
In this thesis, original theoretical and numerical investigations into the interaction of light with...
International audienceEach day, the available volume of numerical data increases. Collecting and ana...
We propose all-optical neural networks characterized by very high energy efficiency and performance...
Machine learning software applications are ubiquitous in many fields of science and society for thei...
In contrast to software simulations of neural networks, hardware implementations have often limited ...
We demonstrate that time-delayed nonlinear effects in exciton-polaritons can be used to construct ne...
Excitons are bound hydrogen-like states of electrons and holes, typically appear- ing in semiconduct...
In this report, I studied the behaviour of exciton polariton condensate system in the context of m...
We show theoretically that neural networks based on disordered exciton-polariton systems allow the r...
A light–matter hybrid quasiparticle, called a polariton, is formed when molecules are strongly coupl...
AbstractMicrocavity polaritons are mixed light–matter quasiparticles with extraordinary nonlinear pr...
A general scheme to realize a perceptron for hardware neural networks is presented, where multiple i...
We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss univer...
Exciton-polaritons are quasiparticles consisting of a linear superposition of photonic and excitonic...
Neuromorphic models are proving capable of performing complex machine learning tasks, overcoming the...
In this thesis, original theoretical and numerical investigations into the interaction of light with...
International audienceEach day, the available volume of numerical data increases. Collecting and ana...
We propose all-optical neural networks characterized by very high energy efficiency and performance...
Machine learning software applications are ubiquitous in many fields of science and society for thei...
In contrast to software simulations of neural networks, hardware implementations have often limited ...
We demonstrate that time-delayed nonlinear effects in exciton-polaritons can be used to construct ne...
Excitons are bound hydrogen-like states of electrons and holes, typically appear- ing in semiconduct...
In this report, I studied the behaviour of exciton polariton condensate system in the context of m...
We show theoretically that neural networks based on disordered exciton-polariton systems allow the r...
A light–matter hybrid quasiparticle, called a polariton, is formed when molecules are strongly coupl...
AbstractMicrocavity polaritons are mixed light–matter quasiparticles with extraordinary nonlinear pr...
A general scheme to realize a perceptron for hardware neural networks is presented, where multiple i...
We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss univer...
Exciton-polaritons are quasiparticles consisting of a linear superposition of photonic and excitonic...
Neuromorphic models are proving capable of performing complex machine learning tasks, overcoming the...
In this thesis, original theoretical and numerical investigations into the interaction of light with...
International audienceEach day, the available volume of numerical data increases. Collecting and ana...