Measuring the Tensorial Flow of Mosaic Vector Beams in Disordered Media.

Optical beams with nonuniform polarization offer enhanced capabilities for information transmission, boasting increased capacity, security, and resilience. These beams possess vectorial features that are spatially organized within localized three-dimensional regions, forming tensors that can be harnessed across a spectrum of applications spanning quantum physics, imaging, and machine learning. However, when subjected to the effect of the transmission channel, the tensorial propagation leads to a loss of data integrity due to the entanglement of spatial and polarization degrees of freedom. The challenge of quantifying this spatial-polarization coupling poses a significant obstacle to the utilization of vector beams in turbulent environments, multimode fibers, and disordered media. Here, we introduce and experimentally investigate mosaic vector beams, which consist of localized polarization tesserae that propagate in parallel, demonstrating accurate measurement of their behavior as they traverse strongly disordered channels and decoding their polarization structure in single-shot experiments. The resultant transmission tensor empowers polarization-based optical communication and imaging in complex media. These findings also hold promise for photonic machine learning, where the engineering of tensorial flow can enable optical computing with high throughput.

Hyperscaling in the Coherent Hyperspin Machine.

Classical and quantum systems are used to simulate the Ising Hamiltonian, an essential component in large-scale optimization and machine learning. However, as the system size increases, devices like quantum annealers and coherent Ising machines face an exponential drop in their success rate. Here, we introduce a novel approach involving high-dimensional embeddings of the Ising Hamiltonian and a technique called "dimensional annealing" to counteract the decrease in performance. This approach leads to an exponential improvement in the success rate and other performance metrics, slowing down the decline in performance as the system size grows. A thorough examination of convergence dynamics in high-performance computing validates the new methodology. Additionally, we suggest practical implementations using technologies like coherent Ising machines, all-optical systems, and hybrid digital systems. The proposed hyperscaling heuristics can also be applied to other quantum or classical Ising devices by adjusting parameters such as nonlinear gain, loss, and nonlocal couplings.

Referenceless characterization of complex media using physics-informed neural networks.

In this work, we present a method to characterize the transmission matrices of complex scattering media using a physics-informed, multi-plane neural network (MPNN) without the requirement of a known optical reference field. We use this method to accurately measure the transmission matrix of a commercial multi-mode fiber without the problems of output-phase ambiguity and dark spots, leading to up to 58% improvement in focusing efficiency compared with phase-stepping holography. We demonstrate how our method is significantly more noise-robust than phase-stepping holography and show how it can be generalized to characterize a cascade of transmission matrices, allowing one to control the propagation of light between independent scattering media. This work presents an essential tool for accurate light control through complex media, with applications ranging from classical optical networks, biomedical imaging, to quantum information processing.

Observation of terahertz transition from Fano resonances to bound states in the continuum.

Bound states in the continuum (BIC) in metamaterials have recently attracted attention for their promising applications in photonics. Here, we investigate the transition from Fano resonances to BIC, at terahertz (THz) frequencies, of a one-dimensional photonic crystal slab made of rectangular dielectric rods. Simulations performed by an analytical exact solution of the Maxwell equations showed that symmetry-protected, high-quality factor (Q), BIC emerge at normal incidence. For non-normal incidence, BIC couple with the freely propagating waves and appear in the scattering field as a Fano resonance. Simulations were verified by realizing the photonic crystal slab by 3D-printing technique. THz time-domain spectroscopy measurements as a function of the incidence angle matched the simulation to good accuracy and confirmed the evolution of Fano resonances to high-Q resonances typical of BIC. These results point out the design of highly sensitive and low-cost THz devices for sensing for a wide range of applications.

Metriplectic Structure of a Radiation-Matter-Interaction Toy Model.

A dynamical system defined by a metriplectic structure is a dissipative model characterized by a specific pair of tensors, which defines a Leibniz bracket; and a free energy, formed by a "Hamiltonian" and an entropy, playing the role of dynamics generator. Generally, these tensors are a Poisson bracket tensor, describing the Hamiltonian part of the dynamics, and a symmetric metric tensor, that models purely dissipative dynamics. In this paper, the metriplectic system describing a simplified two-photon absorption by a two-level atom is disclosed. The Hamiltonian component is sufficient to describe the free electromagnetic radiation. The metric component encodes the radiation-matter coupling, driving the system to an asymptotically stable state in which the excited level of the atom is populated due to absorption, and the radiation has disappeared. First, a description of the system is used, based on the real-imaginary decomposition of the electromagnetic field phasor; then, the whole metriplectic system is re-written in terms of the phase-amplitude pair, named Madelung variables. This work is intended as a first result to pave the way for applying the metriplectic formalism to many other irreversible processes in nonlinear optics.

Evidence of Chaotic Dynamics in Three-Soliton Collisions.

We observe chaotic optical wave dynamics characterized by erratic energy transfer and soliton annihilation and creation in the aftermath of a three-soliton collision in a photorefractive crystal. Irregular dynamics are found to be mediated by the nonlinear Raman effect, a coherent interaction that leads to nonreciprocal soliton energy exchange. Results extend the analogy between solitons and particles to the emergence of chaos in three-body physics and provide new insight into the origin of the irregular dynamics that accompany extreme and rogue waves.

Topological nanophotonics and artificial neural networks.

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 invariants. We consider different structures such as one-dimensional photonic crystals, [Formula: see text]-symmetric chains and cylindrical systems and show how, through a machine learning application, one can identify the parameters of a complex topological insulator to obtain protected edge states at target frequencies. We show how artificial neural networks can be used to solve the long-standing quest for a solution to inverse problems solution and apply this to the cutting edge topic of topological nanophotonics.

The importance of immunity in the development of reliable animal models for psoriasis and atopic dermatitis.

Psoriasis (PS) and atopic dermatitis (AD) are common inflammatory skin diseases characterized by an imbalance in specific T-cell subsets, resulting in a specific cytokine profile in patients. Obtaining models closely resembling both pathologies along with a relevant clinical impact is crucial for the development of new therapies because of the high prevalence of these diseases. Single-gene mouse models developed until now do not fully reflect the complexity of these disorders, in part not only because of inherent differences between mice and humans but also because of the multifactorial nature of these pathologies. The skin-humanized mouse model developed by our group, based on a tissue engineering approach, has been used to test therapeutic strategies, although this methodology is still technically challenging and not widely available. The skin-humanized mouse models for PS and AD reproduce human skin phenotypes, providing valuable tools for drug development and testing in the preclinical setting. The tissue engineering approach allows the development of personalized medicine, covering the broad genotypic spectrum of these pathologies. This review highlights the main differences between available murine models focusing on the tissue-specific immunity of PS and AD. We discuss their contribution to unravel the complex pathophysiology of these diseases and to translate this knowledge into more accurate therapies.

Programming multi-level quantum gates in disordered computing reservoirs via machine learning.

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 that trainable operators at the input and the readout enable one to realize multi-level gates. We study various qudit gates, including the scaling properties of the algorithms with the size of the reservoir. Despite an initial low slop learning stage, TensorFlow turns out to be an extremely versatile resource for designing gates with complex media, including different models that use spatial light modulators with quantized modulation levels.

Nonlinear Optics: feature issue introduction.

This joint issue of Optics Express and Optical Materials Express features 18 state-of-the art articles that witness actual developments in nonlinear optics, including those by authors who participated in the international conference Nonlinear Optics held in Waikoloa, Hawaii from July 15 to 19, 2019. As an introduction, the editors provide a summary of these articles that cover all aspects of nonlinear optics, from basic nonlinear effects and novel frequency windows to innovative nonlinear materials and devices, thereby paving the way for new nonlinear optical concepts and forthcoming applications.

Topological photonic crystal fibers and ring resonators.

With an exact recursive approach, we study photonic crystal fibers and resonators with topological features induced by Aubry-Andre-Harper cladding modulation. We find nontrivial gaps and edge states at the interface between regions with different topological invariants. These structures show topological protection against symmetry-preserving local perturbations that do not close the gap and sustain strong field localization and energy concentration at a given radial distance. As topological light guiding and trapping devices, they may bring about many opportunities for both fundamentals and applications unachievable with conventional devices.

Theory of Neuromorphic Computing by Waves: Machine Learning by Rogue Waves, Dispersive Shocks, and Solitons.

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 approximating mathematical functions, real-world datasets, and universal Boolean gates. The rank of the transmission matrix has a fundamental role in assessing the learning abilities of the wave. For a given set of training points, a threshold nonlinearity for universal interpolation exists. When considering the nonlinear Schrödinger equation, the use of highly nonlinear regimes implies that solitons, rogue, and shock waves do have a leading role in training and computing. Our results may enable the realization of novel machine learning devices by using diverse physical systems, as nonlinear optics, hydrodynamics, polaritonics, and Bose-Einstein condensates. The application of these concepts to photonics opens the way to a large class of accelerators and new computational paradigms. In complex wave systems, as multimodal fibers, integrated optical circuits, random, topological devices, and metasurfaces, nonlinear waves can be employed to perform computation and solve complex combinatorial optimization.

Anisotropic Optical Shock Waves in Isotropic Media with Giant Nonlocal Nonlinearity.

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 system in the rigged Hilbert spaces. The generalization of this theory to more complex scenarios is still an open question. In this work, we use a thermal third-order medium with an unprecedented giant Kerr coefficient, the m-cresol/nylon mixed solution, to access an extremely nonlinear, highly nonlocal regime and realize anisotropic shock waves with internal gaps. We compare our experimental observations to results obtained under similar conditions but in hemoglobin solutions from human red blood cells, and found that the gap formation strongly depends on the nonlinearity strength. We prove that a superposition of Gamow vectors in an ad hoc rigged Hilbert space, that is, a tensorial product between the reversed and the standard harmonic oscillators spaces, describes the beam propagation beyond the shock point. The anisotropy turns out from the interaction of trapping and antitrapping potentials. Our work furnishes the description of novel intriguing shock phenomena mediated by extreme nonlinearities.

Humanization of Tumor Stroma by Tissue Engineering as a Tool to Improve Squamous Cell Carcinoma Xenograft.

The role of stroma is fundamental in the development and behavior of epithelial tumors. In this regard, limited growth of squamous cell carcinomas (SCC) or cell-lines derived from them has been achieved in immunodeficient mice. Moreover, lack of faithful recapitulation of the original human neoplasia complexity is often observed in xenografted tumors. Here, we used tissue engineering techniques to recreate a humanized tumor stroma for SCCs grafted in host mice, by combining CAF (cancer associated fibroblasts)-like cells with a biocompatible scaffold. The stroma was either co-injected with epithelial cell lines derived from aggressive SCC or implanted 15 days before the injection of the tumoral cells, to allow its vascularization and maturation. None of the mice injected with the cell lines without stroma were able to develop a SCC. In contrast, tumors were able to grow when SCC cells were injected into previously established humanized stroma. Histologically, all of the regenerated tumors were moderately differentiated SCC with a well-developed stroma, resembling that found in the original human neoplasm. Persistence of human stromal cells was also confirmed by immunohistochemistry. In summary, we provide a proof of concept that humanized tumor stroma, generated by tissue engineering, can facilitate the development of epithelial tumors in immunodeficient mice.

Firm characteristics and capabilities that enable superior performance in recessions.

Recessions are recurring events in which most firms suffer severe impacts while others are affected less or may even prosper. Notwithstanding, strategic management scholars have made little progress in understanding the reasons for these differences in performance, particularly in unstable macroeconomic environments such as Latin America. In this study, we link literatures on entrepreneurship and improvisation to create an integrative model that indicates characteristics and capabilities that enable a firm to adapt successfully to the recessionary environment. We use survey data from Brazilian firms on the 2008-2009 global recession, and we find that the firms that have superior performance in recessions are those that had, before the recession, 1) a propensity to recognize opportunities and 2) improvisation capabilities for fast and creative actions. We also find a moderating effect of entrepreneurial orientation.

Out-of-equilibrium electron dynamics of silver driven by ultrafast electromagnetic fields - a novel hydrodynamical approach.

We investigate the ultrafast nonlinear response of silver upon excitation by infrared electromagnetic radiation pulses with a duration of a few femtoseconds. By adopting the Landau weak coupling approach to account for electron-electron and electron-phonon collisions, we solve the Boltzmann equation through the method of moments obtaining a novel set of hydrodynamical equations describing the ultrafast nonlinear dynamics of electrons in silver. While the novel hydrodynamical model that was obtained reduces to the Drude model for small intensities of the driving field, it predicts that absorption saturates for large but experimentally attainable peak intensities of the order of GW cm-2. Our results are important for absorption mitigation in plasmonic devices, with potential impact for low-loss plasmonic waveguides and interconnects.

Control of soliton self-frequency shift dynamics via Airy soliton interaction.

We investigate Airy-soliton interaction in a nonlinear fiber with Raman effect. We find that Airy solitons may fuse upon interaction at a position that can be controlled by a proper engineering of the Airy tail direction. This control allows us to generate Airy solitons with varying deceleration. At variance with the case of two solitons interaction, Raman-induced soliton self-frequency shift (SSFS) is strongly enhanced when the leading soliton is replaced with the accelerating Airy pulse and slightly suppressed for the decelerating one. These notable features are ascribed to the unique properties of asymmetrical Airy pulses with a switchable direction of the oscillatory tails. We show the way these processes are uncovered unambiguously by cross-correlation frequency resolved optical gating. We also investigate the impact of chirp imposed on the input pulse on the SSFS dynamics. Our results not only provide a new way to manipulate the SSFS, but may help to improve the control of soliton fusion events during supercontinuum generation, optical rogue waves and giant dispersive waves formation.

Synchrotron resonant radiation from nonlinear self-accelerating pulses.

Solitons and nonlinear waves emit resonant radiation in the presence of perturbations. This effect is relevant for nonlinear fiber optics, supercontinuum generation, rogue waves, and complex nonlinear dynamics. However, resonant radiation is narrowband, and the challenge is finding novel ways to generate and tailor broadband spectra. We theoretically predict that nonlinear self-accelerated pulses emit a novel form of synchrotron radiation that is extremely broadband and controllable. We develop an analytic theory and confirm the results by numerical analysis. This new form of supercontinuum generation can be highly engineered by shaping the trajectory of the nonlinear self-accelerated pulses. Our results may find applications in novel highly efficient classical and quantum sources for spectroscopy, biophysics, security, and metrology.

Graphene Oxide Induced Osteogenesis Quantification by In-Situ 2D-Fluorescence Spectroscopy.

Graphene and graphene oxide can promote the adhesion, growth and differentiation of mesenchymal stem cells. Further, graphene surface coatings accelerate the differentiation of human mesenchymal stem cells acting as osteogenic inducers. Quantification of the osteogenic induction is conventionally performed with Alizarin Red S (ARS), an anthraquinone derivative used to identify calcium deposits in tissue sections and cell cultures. The ARS staining is quite versatile because the dye forms an Alizarin Red S⁻calcium complex that can be extracted from the stained monolayer of cells and readily assayed by absorbance measurements. Direct visualization of stained deposits is also feasible; however, an in-situ visualization and quantification of deposits is possible only on transparent supports and not on thick opaque materials like ceramics and graphene composites that are well-known inducers of osteogenesis. In this manuscript, the shape of the 2D-fluorescence spectra of the ARS-calcium complex is used to develop a method to detect and monitor the in-situ differentiation process occurring during the osteogenic induction mediated by opaque graphene oxide surfaces.

Anderson localisation and optical-event horizons in rogue-soliton generation.

We unveil the relation between the linear Anderson localisation process and nonlinear modulation instability. Anderson localised modes are formed in certain temporal intervals due to the random background noise. Such localised modes seed the formation of solitary waves that will appear during the modulation instability process at those preferred intervals. Afterwards, optical-event horizon effects between dispersive waves and solitons produce an artificial collective acceleration that favours the collision of solitons, which could eventually lead to a rogue-soliton generation.