Parisi Nobel lecture mentioning our experiments

This is the extended version of the Giorgio Parisi Nobel lecture mentioning our experiments in nonlinear optics and random laser with the first observation of Replica Symmetry Breaking

See also Coloquio at the University of Pernambuco on youtube

See also Observation of replica symmetry breaking in disordered nonlinear wave propagation

See also The Experimental Observation of Replica Symmetry Breaking in Random Lasers

Supervised single-shot polarimetry in Nature Communications

DOI 10.1038/s41467-023-37474-0

States of light encoding multiple polarizations – vector beams – offer unique capabilities in metrology and communication. However, their practical application is limited by the lack of methods for measuring many polarizations in a scalable and compact way. Here we demonstrate polarimetry of vector beams in a single shot without any polarization optics. We map the beam polarization content into a spatial intensity distribution through light scattering and exploit supervised learning for single-shot measurements of multiple polarizations. We characterize structured light encoding up to nine polarizations with accuracy beyond 95% on each Stokes parameter. The method also allows us to classify beams with an unknown number of polarization modes, a functionality missing in conventional techniques. Our findings enable a fast and compact polarimeter for polarization-structured light, a general tool that may radically impact optical devices for sensing, imaging, and computing.

Launching optical tsunamis against tumor cells

We demonstrate the excitation of giant rogue waves of light inside human pancreatic tumor cells; they can be used for deep light transport and local heating for cancer treatment.

Rogue waves are intense and unexpected wavepackets ubiquitous in complex systems. In optics, they are promising as robust and noise-resistant beams for probing and manipulating the underlying material. Localizing large optical power is crucial, especially in biomedical systems, where extremely intense beams have not yet been observed. We here discover that tumor-cell spheroids manifest optical rogue waves when illuminated by randomly modulated laser beams. The intensity of light transmitted through bio-printed three-dimensional tumor models follows a signature Weibull statistical distribution, where extreme events correspond to spatially-localized optical modes propagating within the cell network. Experiments varying the input beam power and size indicate that rogue waves have a nonlinear origin. We show these optical filaments form high-transmission channels with enhanced transmission. They deliver large optical power through the tumor spheroid, which can be exploited to achieve a local temperature increase controlled by the input wave shape. Our findings shed new light on optical propagation in biological aggregates and demonstrate how extreme event formation allows light concentration in deep tissues, paving the way to using rogue waves in biomedical applications such as light-activated therapies

The Hyperspin Machine in Nature Communications !

From condensed matter to quantum chromodynamics, multidimensional spins are a fundamental paradigm, with a pivotal role in combinatorial optimization and machine learning. Machines formed by coupled parametric oscillators can simulate spin models, but only for Ising or low-dimensional spins. Currently, machines implementing arbitrary dimensions remain a challenge. Here, we introduce and validate a hyperspin machine to simulate multidimensional continuous spin models. We realize high-dimensional spins by pumping groups of parametric oscillators, and show that the hyperspin machine finds to a very good approximation the ground state of complex graphs. The hyperspin machine can interpolate between different dimensions by tuning the coupling topology, a strategy that we call “dimensional annealing”. When interpolating between the XY and the Ising model, the dimensional annealing substantially increases the success probability compared to conventional Ising simulators. Hyperspin machines are a new computational model for combinatorial optimization. They can be realized by off-the-shelf hardware for ultrafast, large-scale applications in classical and quantum computing, condensed-matter physics, and fundamental studies.

See also The hyperspin machine: simulating QCD models and dimensional annealing