Giulia Marcucci

University of Glasgow | UofG · School of Physics and Astronomy

Fully describing light propagation in a rotating, anisotropic medium with thermal nonlinearity requires modeling the interplay between nonlinear refraction, birefringence, and the nonlinear group index. Incorporating these factors into a generalized coupled nonlinear Schrödinger equation and fitting them to recent experimental results reveals two k...

Nonlinear waves have played a significant role in the development of the science of complexity throughout history. More recently, they have also contributed to the emergence of a novel paradigm in reservoir computing called neuromorphic computing by waves. In this paradigm, information is transmitted through wave dynamics, which process the data to...

Light propagating in a moving medium is subject to light drag. While the light drag effect due to the linear refractive index is often negligibly small, the light drag can be enhanced in materials with a large group index. Here we show that the nonlinear refractive index can also play a crucial role in the propagation of light in moving media and r...

As demand for computational resources reaches unprecedented levels, research is expanding into the use of complex material substrates for computing. In this study, we interface with a model of a hydrodynamic system, under development by a startup, as a computational reservoir and optimize its properties using an evolution in materio approach. Input...

Nonlinear waves have played a historical role in laying the foundations of the science of complexity. Recently, they have also allowed the development of a new reservoir computing paradigm: neuromorphic computing by waves. In these systems, the information transmission acts as the excitation of wave dynamics, whose evolution processes the informati...

Clay Mathematical Institute, in the year 2000, formulated a list of seven unsolved mathematical problems which might influence and direct the course of the research in the 21st century. Navier-Stokes regularity problem is one of the seven problems and has not been solved till date. These equations govern the motion of the viscous fluids, such as li...

This article attempts to use the ideas from the field of complexity sciences to revisit the classical field of fluid mechanics. For almost a century, the mathematical self-consistency of Navier-Stokes equations has remained elusive to the community of functional analysts, who posed the Navier-Stokes problem as one of the seven millennium problems i...

Light propagating in a moving medium with refractive index other than unity is subject to light drag. While the light drag effect due to the linear refractive index is often negligibly small, it can be enhanced in materials with a large group index. Here we show that the nonlinear refractive index can also play a crucial role in propagation of ligh...

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 proportional to the medium's velocity. In this paper, we report on the observation of an anomalous optical drag effect, where the displacement is still proportional to the...

In order to transport information with topological protection, we reveal and demonstrate experimentally the existence of a characteristic length $L_c$, coined as the transport length, in the bulk size for edge states in one-dimensional Su-Schrieffer-Heeger (SSH) chains. In spite of the corresponding wavefunction amplitude decays exponentially, char...

We apply the theory of nonlinear waves in optics and hydrodynamics to the design of a neuromorphic computer. In our device, light-water interaction is the leading phenomenon, and the electronics is limited to the detection.

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 proportional to the medium's velocity. In this article, we report on an anomalous optical drag effect, where the displacement is still proportional to the medium's speed bu...

We experimentally demonstrate an optical machine learning scheme that uses spatial dispersive shock waves for performing classification and regression tasks. The non-linear optical device is easy-to-train and reaches accuracies comparable to digital reservoir machines.

Photonic brain-inspired platforms are emerging as novel analog computing devices, enabling fast and energy-efficient operations for machine learning. These artificial neural networks generally require tailored optical elements, such as integrated photonic circuits, engineered diffractive layers, nanophotonic materials, or time-delay schemes, which...

Photonic brain-inspired platforms are emerging as novel analog computing devices, enabling fast and energyefficient operations for machine learning. These artificial neural networks generally require tailored optical elements, such as integrated photonic circuits, engineered diffractive layers, nanophotonic materials, or time-delay schemes, which a...

By considering a cigar-shaped trapping potential elongated in a proper curvilinear coordinate, we discover a new form of wave localization that arises from the interplay of geometry and topological protection. The potential is undulated in its shape such that local curvature introduces a geometrical potential. The curvature varying along the trap c...

We propose the use of artificial neural networks to design and characterize photonic topological insulators. As a hallmark, the band structures of these systems show the key feature of the emergence of edge states, with energies lying within the energy gap of the bulk materials and localized at the boundary between regions of distinct topological i...

We study theoretically neural networks embedding a nonlinear wave as a computing reservoir. We demonstrate interpolation of large datasets and Boolean logic. We discuss the existence of a critical nonlinearity for learning.

We model waveguide lattices by vortex-beam arrays in turbulent Kerr media. We investigate localized probe states as flat bands, topological edge states, and Anderson localization. By four-wave mixing, we control the excitation and localization robustness.

Dispersive shock waves in thermal optical media are nonlinear phenomena whose intrinsic irreversibility is described by time asymmetric quantum mechanics. Recent studies demonstrated that the nonlocal wave breaking evolves in an exponentially decaying dynamics ruled by the reversed harmonic oscillator, namely, the simplest irreversible quantum syst...

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-know...

Optical neural networks process information at the speed of light and are energetically efficient. Photonic artificial intelligence allows speech recognition, image classification, and Ising machines. Modern machine learning paradigms, as extreme learning machines, reveal that disordered and biological materials may realize optical neural networks...

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 nonlinearity. A feed-forward three-layered model, with an encoding input layer, a wave layer, and a decoding readout, behaves as a conventional neural network in approximati...

Ising machines are novel computing devices for the energy minimization of Ising models. These combinatorial optimization problems are of paramount importance for science and technology, but remain difficult to tackle on large scale by conventional electronics. Recently, various photonics-based Ising machines demonstrated fast computing of a Ising g...

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-know...

Novel machine learning computational tools open new perspectives for quantum information systems. Here we adopt the open-source programming library TensorFlow to design multi-level quantum gates, including a computing reservoir represented by a random unitary matrix. In optics, the reservoir is a disordered medium or a multi-modal fiber. We show th...

We use split-ring resonators to demonstrate topologically protected edge states in the Su-Schieffer-Heeger model experimentally, but in a slow-light wave with the group velocity down to $\sim 0.1$ of light speed in free space. A meta-material formed by an array of complementary split-ring resonators with controllable hopping strength enables the di...

Ising machines are novel computing devices for the energy minimization of Ising models. These combinatorial optimization problems are of paramount importance for science and technology, but remain difficult to tackle on large scale by conventional electronics. Recently, various photonics-based Ising machines demonstrated ultra-fast computing of Isi...

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 geometry and topological protection. The potential is modulated in its shape such that local curvature introduces a trapping potential. The curvature varies along the trap curv...

Nonlinear quantum optics describes rogue wave emergence in faint light propagation through Kerr media. We apply phase-space methods to the quantum nonlinear Schrödinger equation to show that the generation efficiency increases at low photon numbers.

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 nonlinearity. A feed-forward three-layer model, with an encoding input layer, a wave layer, and a decoding readout, behaves as a conventional neural network in approximating...

We show that quantum fluids enable experimental analogs of relativistic orbital precession in the presence of non-paraxial effects. The analysis is performed by the hydrodynamic limit of the Schrödinger equation. The non-commutating variables in the phase-space produce a precession and an acceleration of the orbital motion. The precession of the or...

From optics to hydrodynamics, shock and rogue waves are widespread. Although they appear as distinct phenomena, transitions between extreme waves are allowed. However, these have never been experimentally observed because control strategies are still missing. We introduce the new concept of topological control based on the one-to-one correspondence...

Dispersive shock waves in thermal optical media belong to the third-order nonlinear phenomena, whose intrinsic irreversibility is described by time asymmetric quantum mechanics. Recent studies demonstrated that nonlocal wave breaking evolves in an exponentially decaying dynamics ruled by the reversed harmonic oscillator, namely, the simplest irreve...

From optics to hydrodynamics, shock and rogue waves are widespread. Although they appear as distinct phenomena, new theories state that transitions between extreme waves are allowed. However, these have never been experimentally observed because of the lack of control strategies. We introduce a new concept of nonlinear wave topological control, bas...

Dispersive shock waves are fascinating phenomena occurring when nonlinearity overwhelms linear effects, such as dispersion and diffraction. Many features of shock waves are still under investigation, as the interplay with noninstantaneity in temporal pulses transmission and nonlocality in spatial beams propagation. Despite the rich and vast literat...

Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving the way to new ultrafast hardware for machine learning. However, the proposed systems are either tricky to sca...

Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving the way to new ultra-fast hardware for machine learning. However, the proposed systems are either tricky to sc...

Novel computational tools in machine learning open new perspectives in quantum information systems. Here we adopt the open-source programming library Tensorflow to design multi-level quantum gates including a computing reservoir represented by a random unitary matrix. In optics, the reservoir is a disordered medium or a multimodal fiber. We show th...

Recently P.G. Grinevich and P.M. Santini suggested simple approximate formulas for solving periodic Cauchy problem for the focusing Nonlnear Schrodinger Equation (NLS) under assumption that one starts from a small perturbation of the unstable condensate and the number of unstable modes is not too large. With the help of these results, optical exper...

In optics, nonlinear Schroedinger equation rules many phenomena, including dispersive shock waves (DSWs). We report experimental evidence of optical DSWs with an anisotropic zero-singularity in m-cresol/nylon, and theoretical describe it by time asymmetric quantum mechanics.

We propose and experimentally demonstrate the use of spatial light modulation for calculating the ground state of an Ising Hamiltonian. We realize configurations with thousands of interacting spins that settle in a low-temperature ferromagnetic-like phase.

We introduce the topological control, based on correspondences between phases and genus of toroidal surfaces associated with nonlinear Schroedinger equation. We prove it experimentally and report observations of controlled transitions from shock to rogue waves.

We report the observation of more than three Fermi-Pasta-Ulam-Tsingou recurrences in nonlinear optical wave propagation and experimentally demonstrate that the recurrent behavior is governed by the exact solution of the nonlinear Schrodinger integrable dynamics.

We employ living three-dimensional tumour brain models to demonstrate a bio-inspired optical neural network trained via image transmission to detect cancer mor-phodynamics inaccessible by optical imaging.

Dispersive shock waves are fascinating phenomena occurring when nonlinearity overwhelms linear effects, such as dispersion and diffraction. Many features of shock waves are still under investigation, as the interplay with noninstantaneity in temporal pulses transmission and nonlocality in spatial beams propagation. Despite the rich and vast literat...

The new era of artificial intelligence demands large-scale ultrafast hardware for machine learning. Optical artificial neural networks process classical and quantum information at the speed of light, and are compatible with silicon technology, but lack scalability and need expensive manufacturing of many computational layers. New paradigms, as rese...

One of the most controversial phenomena in nonlinear dynamics is the reappearance of initial conditions. Celebrated as the Fermi-Pasta-Ulam-Tsingou problem, the attempt to understand how these recurrences form during the complex evolution that leads to equilibrium has deeply influenced the entire development of nonlinear science. The enigma is rend...

Topological concepts open many new horizons for photonic devices, from integrated optics to lasers. The complexity of large scale topological devices asks for an effective solution of the inverse problem: how best to engineer the topology for a specific application? We introduce a novel machine learning approach to the topological inverse problem....

The intriguing connection between black holes' evaporation and physics of solitons is opening novel roads to finding observable phenomena. It is known from the inverse scattering transform that velocity is a fundamental parameter in solitons theory. Taking this into account, the study of Hawking radiation by a moving soliton gets a growing relevanc...

Modified uncertainty principle and non-commutative variables may phenomenologically account for quantum gravity effects, independently of the considered theory of quantum gravity. We show that quantum fluids enable experimental analogs and direct tests of the modified uncertainty principle expected to be valid at the Planck scale. We consider a qua...

A dynamical system defined by a metriplectic structure is a dissipative model characterized by a specific pair of tensors, which defines the Leibniz brackets. Generally, these tensors are Poisson brackets tensor and a symmetric metric tensor that models purely dissipative dynamics. In this paper, the metriplectic system describing a simplified two-...

Controlling quantum nonlinear optical processes is a major challenge in optics. We apply novel quantum control techniques to optical solitons. By phase-space methods, we show that a proper control function alters the soliton evolution.

A landmark of statistical mechanics, spin-glass theory describes critical phenomena in disordered systems that range from condensed matter to biophysics and social dynamics. The most fascinating concept is the breaking of replica symmetry: identical copies of the randomly interacting system that manifest completely different dynamics. Replica symme...

The description of irreversible phenomena is a still debated topic in quantum mechanics. Still nowadays, there is no clear procedure to distinguish the coupling with external baths from the intrinsic irreversibility in isolated systems. In 1928 Gamow introduced states with exponentially decaying observables not belonging to the conventional Hilbert...

The intriguing connection between Black holes' evaporation and the physics of solitons is opening novel roads to finding observable phenomena. In particular, due to the recent observation of gravitational waves, Hawking radiation of moving black holes is one of the first candidates to investigate. However, a theoretical context for the description...

Time-reversal symmetry in quantum mechanics has been debated by many authors, like Gamow, Prigogine and others. We show that intrinsically irreversible quantum theories can be simulated by nonlinear optical shock waves in nonlocal media.

It is well known that a state with complex energy cannot be the eigenstate of a self-adjoint operator, like the Hamiltonian. Resonances, i.e. states with exponentially decaying observables, are not vectors belonging to the conventional Hilbert space. One can describe these resonances in an unusual mathematical formalism, based on the so-called Rigg...

More than thirty years ago Glauber suggested that the link between the reversible microscopic and the irreversible macroscopic world can be formulated in physical terms through an inverted harmonic oscillator describing quantum amplifiers. Further theoretical studies have shown that the paradigm for irreversibility is indeed the reversed harmonic o...

Dispersive shock waves dominate wave-breaking phenomena in Hamiltonian systems. In the absence of loss, these highly irregular and disordered waves are potentially reversible. However, no experimental evidence has been given about the possibility of inverting the dynamics of a dispersive shock wave and turn it into a regular wave-front. Nevertheles...