02.12.2021NANO COLLOQUIA S3 Avinash Vikatakavi
Date and Time: December 2, 2021 - 15.00 ONLINE
25.11.2021Producing electricity from heat losses: engineered in Pisa the first device capable of achieving it in a controlled manner
It is now possible to create a new generation of “smart” thermoelectric systems to generate clea...
23.11.2021il progetto RIMMEL @ MECSPE - Bologna 2021
Si svolgerà martedì 23 novembre, dalle 16.45 alle 17.45 (Sala Concerto c/o Centro Servizi – Bolo...
19.11.2021Graphene as a solid lubricant becomes super-slippery
Cnr Nano researchers in collaboration with Sussex University and Rice University studied the frictio...
17.11.2021International Workshop on Advanced Materials-to-Device Solutions for Synaptic Electronics
CNR Nano and ICN2 organized the
03.11.2021The RIMMEL Project @ l'Europa è qui 2021 – VOTE THE VIDEO ONLINE
The RIMMEL project enters the “Europe is here ...
11.10.2021Quantum computers become an experimental physics laboratory
A quantum computer is a machine designed to do calculations. Now a group of physicists from CnrNano,...
05.10.20212021 Nobel Prize for the discoveries on TRPV1 and PIEZO receptors
The seminal discoveries by this year’s Nobel Laureates have explained how heat, cold and touch can...
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- 16.06.2021 - FIM-S3 SEMINAR - Prof Claudio ContiDate and Time: Wednesday June 16th, 16:00 (SHARP) LINK (Google Meet): https://meet.google.com/yud-upbp-mno Speaker: Prof Claudio Conti - La Sapienza University and ISC-CNR Title: Learning Photonic Machines Abstract: Machine learning is percolating the way we do science. Many new computational tools are emerging and changing our approach to open problems in physics. But if we examine these tools with attention, we find out that physics mostly inspires them. This implies that we can use physical systems to implement the models in modern artificial intelligence beyond programming them in a conventional computer. This opportunity is evident in photonics and is fostering a renaissance of photonic computing. Nowadays, we can surpass the historical limitations of light-driven processors, leading to new devices at the interface of classical and quantum technologies. We show here how to realize simple but powerful optical computing machines by using spatial light modulation within an introductory approach. Specifically, we describe “Ising Machines,” which solve combinatorial optimization problems and tackle well-known large-scale systems in condensed matter physics. Also, we report on “Extreme Learning Machines,” which implement a neuromorphic computing protocol. They can be trained to act as a classifier or a universal interpolator as a conventional machine learning model. We can improve these simple computing devices in several directions, for example, by using novel materials to increase the nonlinear response or nano-fabricated surfaces to engineer specific applications while opening a new generation of energetically efficient, ultrafast, and versatile photonic computing machines. Host: Marco Gibertini (FIM, UNIMORE) and Claudia Cardoso (S3, CNR-NANO) Flyer