activity
20182022
most citedLarge-scale photonic Ising machine by spatial light modulation

363 citations · 544 across the 7 of their papers we have counts for

collaborators

15 papers

physics.optics2021

Anomalous Optical Drag

Chitram Banerjee, Yakov Solomons, A. Nicholas Black +5

A moving dielectric medium can displace the optical path of light passing through it, a phenomenon known as the Fresnel-Fizeau optical drag effect. The resulting displacement is pr…

cs.ET2021100 cited

Photonic extreme learning machine by free-space optical propagation

Davide Pierangeli, Giulia Marcucci, Claudio Conti

Photonic brain-inspired platforms are emerging as novel analog computing devices, enabling fast and energy-efficient operations for machine learning. These artificial neural networ…

physics.optics20203 cited

Adiabatic evolution on a spatial-photonic Ising machine

D. Pierangeli, G. Marcucci, C. Conti

Combinatorial optimization problems are crucial for widespread applications but remain difficult to solve on a large scale with conventional hardware. Novel optical platforms, know…

physics.optics202075 cited

Noise-enhanced spatial-photonic Ising machine

Davide Pierangeli, Giulia Marcucci, Daniel Brunner +1

Ising machines are novel computing devices for the energy minimization of Ising models. These combinatorial optimization problems are of paramount importance for science and techno…

physics.optics2020

Multidimensional topological strings by curved potentials: Simultaneous realization of mobility edge and topological protection

Chun-Yan Lin, Giulia Marcucci, Gang Wang +3

By considering a cigar-shaped trapping potential elongated in a proper curvilinear coordinate, we discover a new form of wave localization which arises from the interplay of geomet…

physics.optics2019

Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons

Giulia Marcucci, Davide Pierangeli, Claudio Conti

We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss universality and the conditions to learn a dataset in terms of output channels and non…