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Quantum dots (QDs) have garnered a significant amount of attention as promising memristive materials owing to their size-dependent tunable bandgap, structural stability, and high level of applicability for neuromorphic computing. Despite these advantageous properties, the development of QD-based memristors has been hindered by challenges in understanding and adjusting the resistive switching (RS) behavior of QDs. Herein, we propose three types of InP/ZnSe/ZnS QD-based memristors to elucidate the RS mechanism, employing a thin poly(methyl methacrylate) layer. This approach not only allows us to identify which carriers (electron or hole) are trapped within the QD layer but also successfully demonstrates QD-based synaptic devices. Furthermore, to utilize the QD memristor as a synapse, long-term potentiation/depression (LTP/LTD) characteristics are measured, resulting in a low nonlinearity of LTP/LTD at 0.1/1. On the basis of the LTP/LTD characteristics, single-layer perceptron simulations were performed using the Extended Modified National Institute of Standards and Technology, verifying a maximum recognition rate of 91.46%.
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Programmable photonic circuits (PPCs) have garnered substantial interest for their potential in facilitating deep learning accelerations and universal quantum computations. Although photonic computation using PPCs offers ultrafast operation, energy-efficient matrix calculations, and room-temperature quantum states, its poor scalability hinders integration. This challenge arises from the temporally one-shot operation of propagating light in conventional PPCs, resulting in a light-speed increase in device footprints. Here we propose the concept of programmable photonic time circuits, utilizing time-cycle-based computations analogous to gate cycling in the von Neumann architecture and quantum computation. Our building block is a reconfigurable SU(2) time gate, consisting of two resonators with tunable resonances, and coupled via time-coded dual-channel gauge fields. We demonstrate universal U(N) operations with high fidelity using an assembly of the SU(2) time gates, substantially improving scalability from O(N^{2}) to O(N) in terms of both the footprint and the number of gates. This result paves the way for PPC implementation in very large-scale integration.
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Reducing geometrical complexity while preserving desired wave properties is critical for proof-of-concept studies in wave physics, as evidenced by recent efforts to realize photonic synthetic dimensions, isospectrality, and hyperbolic lattices. Laughlin's topological pump, which elucidates quantum Hall states in cylindrical geometry with a radial magnetic field and a time-varying axial magnetic flux, is a prime example of these efforts. Here we propose a two-dimensional dynamical photonic system for the topological pumping of pseudospin modes by exploiting synthetic frequency dimensions. The system provides the independent control of pseudomagnetic fields and electromotive forces achieved by the interplay between mode-dependent and mode-independent gauge fields. To address the axial open boundaries and azimuthal periodicity of the system, we define the adjusted local Chern marker with rotating azimuthal coordinates, proving the nontrivial topology of the system. We demonstrate the adiabatic pumping for crosstalk-free frequency conversion with wave front molding. Our approach allows for reproducing Laughlin's thought experiment at room temperature with a scalable setup.
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The effect of deep subwavelength disorder in one-dimensional dichromic multilayer films on the optical transmission, localization length, and Goos-Hänchen shift around the critical angle is analyzed using sets of disordered multilayer films with different degrees of order metric τ. For each Gaussian-perturbed multilayer film designed by a Metropolis algorithm targeting the predetermined order metric τ, the numerically obtained localization length and transmission show excellent agreement with the recent theoretical analysis developed for disordered multilayer films, further revealing τ-dependence of the Goos-Hänchen shift across the critical angle. Emphasizing the role of deep subwavelength structures in disorder-induced transmission enhancement, our result thus paves the way toward the inverse design of a deep subwavelength disordered structural landscape for the targeted order metric τ or abnormal optical responses - including the Goos-Hänchen shift.
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Non-Euclidean geometry, discovered by negating Euclid's parallel postulate, has been of considerable interest in mathematics and related fields for the description of geographical coordinates, Internet infrastructures, and the general theory of relativity. Notably, an infinite number of regular tessellations in hyperbolic geometry-hyperbolic lattices-are expected to extend Euclidean Bravais lattices and the consequent wave phenomena to non-Euclidean geometry. However, topological states of matter in hyperbolic lattices have yet to be reported. Here we investigate topological phenomena in hyperbolic geometry, exploring how the quantized curvature and edge dominance of the geometry affect topological phases. We report a recipe for the construction of a Euclidean photonic platform that inherits the topological band properties of a hyperbolic lattice under a uniform, pseudospin-dependent magnetic field, realizing a non-Euclidean analog of the quantum spin Hall effect. For hyperbolic lattices with different quantized curvatures, we examine the topological protection of helical edge states and generalize Hofstadter's butterfly, by employing two empirical parameters that measure the edge confinement and defect immunity. We demonstrate that the proposed platforms exhibit the unique spectral-magnetic sensitivity of topological immunity in highly curved hyperbolic planes. Our approach is applicable to general non-Euclidean geometry and enables the exploitation of infinite lattice degrees of freedom for band theory.
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We propose an approach of steering the second harmonic (SH) emission from a single plasmonic structure, through local excitations of plasmon. The proposed idea is confirmed experimentally, by adjusting the incident beam position at the fundamental frequency, on a single plasmonic antenna. A significant directivity change ( ± 52°) for the SH emission is observed with submicrometer adjustment ( ± 250 nm) of the excitation beam position, over broadband SH frequencies. Providing a simple method of controlling the directivity of frequency-converted light, our approach paves the way to new design strategy for nonlinear optical devices with various nonlinear wavefronts.
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Access to the transverse spin of light has unlocked new regimes in topological photonics. To achieve the transverse spin from nonzero longitudinal fields, various platforms that derive transversely confined waves based on focusing, interference, or evanescent waves have been suggested. Nonetheless, because of the transverse confinement inherently accompanying sign reversal of the field derivative, the resulting transverse spin handedness of each field experiences spatial inversion, which leads to a mismatch between the intensities of the field and its spin component and hinders the global observation of the transverse spin. Here, we reveal a globally pure transverse spin of the electric field in which the field intensity signifies the spin distribution. Starting from the target spin mode for the inverse design of required spatial profiles of anisotropic permittivities, we show that the elliptic-hyperbolic transition around the epsilon-near-zero permittivity allows for the global conservation of transverse spin handedness of the electric field across the topological interface between anisotropic metamaterials. Extending to the non-Hermitian regime, we develop annihilated transverse spin modes to cover the entire Poincaré sphere of the meridional plane. This result realizes the complete optical analogy of three-dimensional quantum spin states.
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The de Broglie-Bohm theory is one of the nonstandard interpretations of quantum phenomena that focuses on reintroducing definite positions of particles, in contrast to the indeterminism of the Copenhagen interpretation. In spite of intense debate on its measurement and nonlocality, the de Broglie-Bohm theory based on the reformulation of the Schrödinger equation allows for the description of quantum phenomena as deterministic trajectories embodied in the modified Hamilton-Jacobi mechanics. Here, we apply the Bohmian reformulation to Maxwell's equations to achieve the independent manipulation of optical phase evolution and energy confinement. After establishing the deterministic design method based on the Bohmian approach, we investigate the condition of optical materials enabling scattering-free light with bounded or random phase evolutions. We also demonstrate a unique form of optical confinement and annihilation that preserves the phase information of incident light. Our separate tailoring of wave information extends the notion and range of artificial materials.
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The concept of parity-time (PT) symmetry has been used to identify a route toward unidirectional dynamics in optical k-space: imposing asymmetry on the flow of light. Although PT-symmetric potentials have been implemented under the requirement of V(x) = V*(-x), this precondition has only been interpreted within the mathematical framework for the symmetry of Hamiltonians and has not been directly linked to unidirectionality induced by PT symmetry. In this paper, within the context of light-matter interactions, we develop an alternative route toward unidirectionality in k-space by employing the concept of causality. We demonstrate that potentials with real and causal momentum spectra produce unidirectional transitions of optical modes inside the k-continuum, which corresponds to an exceptional point on the degree of PT symmetry. Our analysis reveals a critical link between non-Hermitian problems and spectral theory and also enables multi-dimensional designer manipulation of optical modes, in contrast to the one-dimensional approach that used a Schrödinger-like equation in previous PT-symmetric optics.
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The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave systems. In photonics, because electromagnetic interactions between optical elements generally decay rapidly with spatial distance, most wave phenomena are modeled with neighboring interactions, which account for only a small part of conceptually possible networks. Here, we explore the impact of substantial long-range interactions in topological photonics. We demonstrate that a crystalline structure, characterized by long-range interactions in the absence of neighboring ones, can be interpreted as an overlapped lattice. This overlap model facilitates the realization of higher values of topological invariants while maintaining bandgap width in photonic topological insulators. This breaking of topology-bandgap tradeoff enables topologically protected multichannel signal processing with broad bandwidths. Under practically accessible system parameters, the result paves the way to the extension of topological physics to network science.
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Network science provides a powerful tool for unraveling the complexities of social, technological and biological systems. Constructing networks using wave phenomena is also of great interest in devising advanced hardware for machine learning, as shown in optical neural networks. Although most wave-based networks have employed static network models, the impact of evolving models in network science provides strong motivation to apply dynamical network modeling to wave physics. Here the concept of evolving scattering networks for scattering phenomena is developed. The network is defined by links, node degrees and their evolution processes modeling multi-particle interferences, which directly determine scattering from disordered materials. I demonstrate the concept by examining network-based material classification, microstructure screening and preferential attachment in evolutions, which are applied to stealthy hyperuniformity. The results enable independent control of scattering from different length scales, revealing superdense material phases in short-range order. The proposed concept provides a bridge between wave physics and network science to resolve multiscale material complexities and open-system material design.
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Redes Neurales de la Computación , FísicaRESUMEN
Developing hardware for high-dimensional unitary operators plays a vital role in implementing quantum computations and deep learning accelerations. Programmable photonic circuits are singularly promising candidates for universal unitaries owing to intrinsic unitarity, ultrafast tunability and energy efficiency of photonic platforms. Nonetheless, when the scale of a photonic circuit increases, the effects of noise on the fidelity of quantum operators and deep learning weight matrices become more severe. Here we demonstrate a nontrivial stochastic nature of large-scale programmable photonic circuits-heavy-tailed distributions of rotation operators-that enables the development of high-fidelity universal unitaries through designed pruning of superfluous rotations. The power law and the Pareto principle for the conventional architecture of programmable photonic circuits are revealed with the presence of hub phase shifters, allowing for the application of network pruning to the design of photonic hardware. For the Clements design of programmable photonic circuits, we extract a universal architecture for pruning random unitary matrices and prove that "the bad is sometimes better to be removed" to achieve high fidelity and energy efficiency. This result lowers the hurdle for high fidelity in large-scale quantum computing and photonic deep learning accelerators.
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In this paper, we derive a governing equation for spectral asymmetry in electromagnetically induced transparency (EIT). From the key parameters of asymmetry factor - namely dark mode quality factor Q(d), and frequency separation between bright and dark mode Δω(bd) = (ω(b) - ω(d)) -, a logical pathway for the maximization of EIT asymmetry is identified. By taking the plasmonic metal-insulator-metal (MIM) waveguide as a platform, a plasmon-induced transparency (PIT) structure of tunable frequency separation Δω(bd) and dark mode quality factor Q(d) is suggested and analyzed. Compared to previous works on MIM-based plasmon modulators, an order of increase in the performance Fig. (12dB contrast at ~60% throughput) was achieved from the highly asymmetric, narrowband PIT spectra.
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Luz , Modelos Teóricos , Dispersión de Radiación , Resonancia por Plasmón de Superficie/instrumentación , Resonancia por Plasmón de Superficie/métodos , Simulación por Computador , Diseño Asistido por Computadora , Diseño de Equipo , Análisis de Falla de EquipoRESUMEN
We use coupled mode theory (CMT) to analyze a metal-insulator-metal (MIM) plasmonic stub structure, to reveal the existence of asymmetry in its transmittance spectra. Including the effect of the near field contribution for the stub structure, the observed asymmetry is interpreted as Fano-type interference between the quasi-continuum T-junction-resonator local-modes and discrete stub eigenmodes. Based on the asymmetry factor derived from the CMT analysis, methods to control transmittance asymmetry are also demonstrated.
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Junction structures provide the foundation of digital electronics and spintronics today. An equivalent, a photonic junction to achieve systematic and drastic control of photon flow is currently missing, but is mandatory for serious all-optical signal processing. Here we propose a photonic junction built upon mode-orthogonal hetero-structures, as a fundamental structural unit for photonic integrated circuits. Controlling the optical potential of mode-orthogonal junctions, the flow of photons can be dynamically manipulated, to complete the correspondence to the electronic junction structures. Of the possible applications, we provide examples of a photonic junction diode and a multi-junction half-adder, with exceptional performance metrics. Highly directional (41dB), nearly unity throughput, ultra-low threshold-power, high quality signal regeneration at 200Gb/s, and all-optic logic operations are successfully derived with the self-induced, bi-level dynamic mode-conversion process across the junction.
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Diseño Asistido por Computadora , Modelos Teóricos , Dispositivos Ópticos , Fotometría/instrumentación , Semiconductores , Simulación por Computador , Diseño de Equipo , Análisis de Falla de Equipo , Luz , Fotones , Dispersión de RadiaciónRESUMEN
We propose a rigorous design method of structured gratings for out of plane mode conversion, line focusing and manipulation of Surface Plasmon Polariton (SPP) waves. Employing a blazed grating to incorporate the directionality of SPP launch, and at the same time controlling grating depth and chirp to account for the radiation loss and diffraction angle, it was possible to achieve high efficiency and flexible SPP to freespace mode conversion. Devices with advanced functionalities, such as balanced SPP power splitter, and SPP wavelength demultiplexer are demonstrated with over 75% of power efficiencies at reasonable working distances of less than several wavelengths.
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The vast amount of design freedom in disordered systems expands the parameter space for signal processing. However, this large degree of freedom has hindered the deterministic design of disordered systems for target functionalities. Here, we employ a machine learning approach for predicting and designing wave-matter interactions in disordered structures, thereby identifying scale-free properties for waves. To abstract and map the features of wave behaviors and disordered structures, we develop disorder-to-localization and localization-to-disorder convolutional neural networks, each of which enables the instantaneous prediction of wave localization in disordered structures and the instantaneous generation of disordered structures from given localizations. We demonstrate that the structural properties of the network architectures lead to the identification of scale-free disordered structures having heavy-tailed distributions, thus achieving multiple orders of magnitude improvement in robustness to accidental defects. Our results verify the critical role of neural network structures in determining machine-learning-generated real-space structures and their defect immunity.
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We propose a novel metal slit array Fresnel lens for wavelength-scale optical coupling into a nanophotonic waveguide. Using the plasmonic waveguide structure in Fresnel lens form, a much wider beam acceptance angle and wavelength-scale working distance of the lens was realized compared to a conventional dielectric Fresnel lens. By applying the plasmon waveguide dispersion relation to a phased antenna array model, we also develop and analyze design rules and parameters for the suggested metal slit Fresnel lens. Numerical assessment of the suggested structure shows excellent coupling efficiency (up to 59%) of the 10 mum free-space Gaussian beam to the 0.36 mum Si waveguide within a working distance of a few mum.
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As an elementary processor of neural networks, a neuron performs exotic dynamic functions, such as bifurcation, repetitive firing, and oscillation quenching. To achieve ultrafast neuromorphic signal processing, the realization of photonic equivalents to neuronal dynamic functions has attracted considerable attention. However, despite the nonconservative nature of neurons due to energy exchange between intra- and extra-cellular regions through ion channels, the critical role of non-Hermitian physics in the photonic analogy of a neuron has been neglected. Here, a neuromorphic non-Hermitian photonic system ruled by parity-time symmetry is presented. For a photonic platform that induces the competition between saturable gain and loss channels, dynamical phases are classified with respect to parity-time symmetry and stability. In each phase, unique oscillation quenching functions and nonreciprocal oscillations of light fields are revealed as photonic equivalents of neuronal dynamic functions. The proposed photonic system for neuronal functionalities will become a fundamental building block for light-based neural signal processing.
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A photonic analog-to-digital converter (PADC) utilizing a slow-light photonic crystal Mach-Zehnder interferometer (MZI) is proposed, to enable the optically coded output of a PADC with reduced device size and power consumption. Assuming an index modulation for the MZI on the Taylor's PADC structure, limiting factors in device size, speed, and effective number of bits are derived considering the signal transition time of the light and the slow light dispersion effects. Details of the device design and results of a time domain assessment of the device performance is described with discussions on the feasibility of sub-mm size, 20GS/s operation of the device having the ENOB (effective number of bits) > 5.