Experiments on adiabatic evolution in Ising machines in Optica

Combinatorial optimization problems are crucial for widespread applications but remain difficult to solve on a large scale with conventional hardware. Novel optical platforms, known as coherent or photonic Ising machines, are attracting considerable attention as accelerators on optimization tasks formulable as Ising models. Annealing is a well-known technique based on adiabatic evolution for finding optimal solutions in classical and quantum systems made by atoms, electrons, or photons. Although various Ising machines employ annealing in some form, adiabatic computing on optical settings has been only partially investigated. Here, we realize the adiabatic evolution of frustrated Ising models with 100 spins programmed by spatial light modulation. We use holographic and optical control to change the spin couplings adiabatically, and exploit experimental noise to explore the energy landscape. Annealing enhances the convergence to the Ising ground state and allows to find the problem solution with probability close to unity. Our results demonstrate a photonic scheme for combinatorial optimization in analogy with adiabatic quantum algorithms and classical annealing methods but enforced by optical vector-matrix multiplications and scalable photonic technology.

https://www.osapublishing.org/optica/fulltext.cfm?uri=optica-7-11-1535&id=442147

See also https://arxiv.org/abs/2005.08690

Electric directional steering of cathodoluminescence from graphene-based hydrid nanostructures

Controlling directional emission of nanophotonic radiation sources is fundamental to tailor radiation-matter interaction and to conceive highly efficient nanophotonic devices for on-chip wireless communication and information processing. Nanoantennas coupled to quantum emitters have proven to be very efficient radiation routers, while electrical control of unidirectional emission has been achieved through inelastic tunneling of electrons. Here we prove that the radiation emitted from the interaction of a high-energy electron beam with a graphene-nanoparticle composite has beaming directions which can be made to continuously span the full circle even through small variations of the graphene Fermi energy. Emission directionality stems from the interference between the double cone shaped electron transition radiation and the nanoparticle dipolar diffraction radiation. Tunability is enabled since the interference is ruled by the nanoparticle dipole moment whose amplitude and phase are driven by the hybrid plasmonic resonances of the composite and the absolute phase of the graphene plasmonic polariton launched by the electron, respectively. The flexibility of our method provides a way to exploit graphene plasmon physics to conceive improved nanosources with ultrafast reconfigurable radiation patterns.

Ciattoni, Conti, Marini in https://arxiv.org/abs/2010.09017

Press release on the AI of waves

https://www.uniroma1.it/it/notizia/lintelligenza-delle-onde-1

https://www.cnr.it/en/press-release/9652/l-intelligenza-delle-onde

https://www.phys.uniroma1.it/fisica/archivionotizie/theory-neuromorphic-computing-waves

https://www.virgilio.it/italia/enna/notizielocali/l_intelligenza_delle_onde-63443731.html

https://www.virgilio.it/italia/enna/notizielocali/l_intelligenza_delle_onde-63443731.html

https://it.finance.yahoo.com/notizie/da-cnr-modello-intelligenza-artificiale-che-sfrutta-onde-124603891.html

https://www.e-gazette.it/sezione/tecnologia/incredibol-sapienza-cnr-studiano-intelligenza-onde

https://electomagazine.it/lintelligenza-delle-onde-e-il-risparmio-energetico/
Electomagazine.it

https://ilcorrieredelweb.blogspot.com/2020/09/scienza-cnr-lintelligenza-delle-onde.html

https://www.lescienze.it/news/2020/09/22/news/l_intelligenza_delle_onde-4800586/

https://it.notizie.yahoo.com/da-cnr-modello-intelligenza-artificiale-che-sfrutta-onde-124603891.html

Nuove Direzioni numero 62, Nov-Dic 2020, pag. 75 “L’intelligenza delle onde”

Messaggero, 5 October 2020

Interview of Claudio Conti (podcast)

https://rbe.it/2020/10/22/allenare-le-intelligenze-artificiali-con-le-onde/