BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Date iCal//NONSGML kigkonsult.se iCalcreator 2.20.2//
METHOD:PUBLISH
X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:STANDARD
DTSTART:20231029T030000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20240331T020000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:calendar.27571.field_data.0@diag.uniroma1.it
DTSTAMP:20260413T235835Z
CREATED:20231216T154047Z
DESCRIPTION:AbstractThe continuous advancing in the technology for photonic
  integrated circuits (PICs) enabled the fabrication of larger circuit layo
 uts with increasing complexity. The state of the art addresses the fabrica
 tion of these circuits for specific applications\, targeting a photonic-AS
 ICs 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 rang
 e of functions\, where the basic reconfigurable building block is the opti
 cal coupler. Targeting a 2x2 reconfigurable logic gate as the most promisi
 ng candidate for this function\, we present an innovative approach based o
 n 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 algori
 thm was used to characterize the active-matrix configuration for operating
  the control of the output channels. The simulation results obtained in th
 e layout design will be presented and discussed\, together with the planne
 d workflow for a proof-of-concept prototype. Also on Zoom\, link: https://
 uniroma1.zoom.us/j/83237503068?pwd=b0lOMUdVeFZDTzliT1dVNUlJd0VhUT09Meeting
  ID: 832 3750 3068Access code: 584514 
DTSTART;TZID=Europe/Paris:20231221T120000
DTEND;TZID=Europe/Paris:20231221T120000
LAST-MODIFIED:20231219T180412Z
LOCATION:Aula A4
SUMMARY:A machine learning approach for the project of an amorphous silicon
  optical logic gate based on an Electrically Reconfigurable Metamaterial -
  Alessandro Fantoni
URL;TYPE=URI:http://diag.uniroma1.it/node/27571
END:VEVENT
END:VCALENDAR