Boson sampling solitons by quantum machine learning

We use a neural network variational ansatz to compute Gaussian quantum discrete solitons in an array of waveguides described by the quantum discrete nonlinear Schroedinger equation. By training the quantum machine learning model in the phase space, we find different quantum soliton solutions varying the number of particles and interaction strength. The use of Gaussian states enables measuring the degree of entanglement and the boson sampling patterns. We compute the probability of generating different particle pairs when varying the soliton features and unveil that bound states of discrete solitons emit correlated pairs of photons. These results may have a role in boson sampling experiments with nonlinear systems and in developing quantum processors to generate entangled many-photon nonlinear states.

Ciao Erasmo

Two days ago, on the 14th of July 2021, one of the most influential professors I met in my career had passed away. Erasmo Recami has been an example of what being a scientist means. Never looking for the scene, but always studying, doing research, and answering by knowledge and writing.

Erasmo has contributed to so many subjects that are difficult to summarize. From the problem of time to the discovery of tachyons, which inspired the research on X-waves in optics and other fields. He started the legend of Majorana by his investigations and his famous books.

I have always appreciated his way of interacting with young scientists, discussing friendly and open-minded on many subjects. How important is confronting expert people for motivated young researchers!

Years ago, in 2008, he participated in a workshop on nonlinear waves I organized in Rome. I still remember him presenting old-school slides in a lamp projector. Those slides were dense with historical references and knowledge. Thanks, Erasmo! I hope to meet many other persons like you in my life.

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