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A machine learning approach for the project of an amorphous silicon optical logic gate based on an Electrically Reconfigurable Metamaterial

Alessandro Fantoni
Data dell'evento: 
Thursday, 21 December, 2023 - 12:00
Aula A4
Paolo Di Giamberardino


The continuous advancing in the technology for photonic integrated circuits (PICs) enabled the fabrication of larger circuit layouts with increasing complexity. The state of the art addresses the fabrication of these circuits for specific applications, targeting a photonic-ASICs class of devices. An interesting and alternative route, led recently to the conception of a new class of programmable photonic circuits. These circuits can be flexibly configured using software to serve a diverse range of functions, where the basic reconfigurable building block is the optical coupler. Targeting a 2x2 reconfigurable logic gate as the most promising candidate for this function, we present an innovative approach based on an electrically controlled metamaterial-like functionality, induced by an array of MOS structures on an amorphous silicon MMI structure.

A phyton integration of the Synopsys RSOFT simulator with a machine learning algorithm was used to characterize the active-matrix configuration for operating the control of the output channels. The simulation results obtained in the layout design will be presented and discussed, together with the planned workflow for a proof-of-concept prototype.


Also on Zoom, link: https://uniroma1.zoom.us/j/83237503068?pwd=b0lOMUdVeFZDTzliT1dVNUlJd0VhUT09

Meeting ID: 832 3750 3068

Access code: 584514


gruppo di ricerca: 
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