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On-chip structured light, with potentially infinite complexity, has emerged as a linchpin in the realm of integrated photonics. However, the realization of arbitrarily tailoring a multitude of light field dimensions in complex media remains a challenge1, Through associating physical light fields and mathematical function spaces by introducing a mapping operator, we proposed a data-driven inverse design method to precisely manipulate between any two structured light fields in the on-chip high-dimensional Hilbert space. To illustrate, light field conversion in on-chip topological photonics was achieved. High-performance topological coupling devices with minimal insertion loss and customizable topological routing devices were designed and realized. Our method provides a new paradigm to enable precise manipulation over the on-chip vectorial structured light and paves the way for the realization of complex photonic functions., Comment: 50 pages, 18 figures

Wave localization is a fundamental phenomenon that appears universally in both natural materials and artificial structures and plays a crucial role in understanding the various physical properties of a system. Usually, a localized state has an exponential profile with a localization length independent of the system size. Here, we experimentally demonstrate a new class of localized states called scale-free localized states, which has an unfixed localization length scaling linearly with the system size. Using circuit lattices, we observe that a non-Hermitian defect added to a Hermitian lattice induces an extensive number of states with scale-free localization. Furthermore, we demonstrate that, in a lattice with a parity-time-symmetric non-Hermitian defect, the scale-free localization emerges because of spontaneous parity-time symmetry breaking. Our results uncover a new type of localized states and extend the study of defect physics to the non-Hermitian regime.

Traditional end-to-end (E2E) training of deep networks necessitates storing intermediate activations for back-propagation, resulting in a large memory footprint on GPUs and restricted model parallelization. As an alternative, greedy local learning partitions the network into gradient-isolated modules and trains supervisely based on local preliminary losses, thereby providing asynchronous and parallel training methods that substantially reduce memory cost. However, empirical experiments reveal that as the number of segmentations of the gradient-isolated module increases, the performance of the local learning scheme degrades substantially, severely limiting its expansibility. To avoid this issue, we theoretically analyze the greedy local learning from the standpoint of information theory and propose a ContSup scheme, which incorporates context supply between isolated modules to compensate for information loss. Experiments on benchmark datasets (i.e. CIFAR, SVHN, STL-10) achieve SOTA results and indicate that our proposed method can significantly improve the performance of greedy local learning with minimal memory and computational overhead, allowing for the boost of the number of isolated modules. Our codes are available at https://github.com/Tab-ct/ContSup., Comment: 9 figures, 12 tables

Spiking Neural Networks (SNNs), as one of the algorithmic models in neuromorphic computing, have gained a great deal of research attention owing to temporal information processing capability, low power consumption, and high biological plausibility. The potential to efficiently extract spatio-temporal features makes it suitable for processing the event streams. However, existing synaptic structures in SNNs are almost full-connections or spatial 2D convolution, neither of which can extract temporal dependencies adequately. In this work, we take inspiration from biological synapses and propose a spatio-temporal synaptic connection SNN (STSC-SNN) model, to enhance the spatio-temporal receptive fields of synaptic connections, thereby establishing temporal dependencies across layers. Concretely, we incorporate temporal convolution and attention mechanisms to implement synaptic filtering and gating functions. We show that endowing synaptic models with temporal dependencies can improve the performance of SNNs on classification tasks. In addition, we investigate the impact of performance vias varied spatial-temporal receptive fields and reevaluate the temporal modules in SNNs. Our approach is tested on neuromorphic datasets, including DVS128 Gesture (gesture recognition), N-MNIST, CIFAR10-DVS (image classification), and SHD (speech digit recognition). The results show that the proposed model outperforms the state-of-the-art accuracy on nearly all datasets.

Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, bio-interpretability is partially neglected in those BP-based algorithms. Toward bio-plausible BP-based SNNs, we consider three properties in modeling spike activities: Multiplicity, Adaptability, and Plasticity (MAP). In terms of multiplicity, we propose a Multiple-Spike Pattern (MSP) with multiple spike transmission to strengthen model robustness in discrete time-iteration. To realize adaptability, we adopt Spike Frequency Adaption (SFA) under MSP to decrease spike activities for improved efficiency. For plasticity, we propose a trainable convolutional synapse that models spike response current to enhance the diversity of spiking neurons for temporal feature extraction. The proposed SNN model achieves competitive performances on neuromorphic datasets: N-MNIST and SHD. Furthermore, experimental results demonstrate that the proposed three aspects are significant to iterative robustness, spike efficiency, and temporal feature extraction capability of spike activities. In summary, this work proposes a feasible scheme for bio-inspired spike activities with MAP, offering a new neuromorphic perspective to embed biological characteristics into spiking neural networks.

The tensor network, as a facterization of tensors, aims at performing the operations that are common for normal tensors, such as addition, contraction and stacking. However, due to its non-unique network structure, only the tensor network contraction is so far well defined. In this paper, we propose a mathematically rigorous definition for the tensor network stack approach, that compress a large amount of tensor networks into a single one without changing their structures and configurations. We illustrate the main ideas with the matrix product states based machine learning as an example. Our results are compared with the for loop and the efficient coding method on both CPU and GPU., Comment: 9 pages, 10 figures, close to the online published version, for the code on Github, see this https://github.com/veya2ztn/Stack_of_Tensor_Network

Metasurfaces have received a lot of attentions recently due to their versatile capability in manipulating electromagnetic wave. Advanced designs to satisfy multiple objectives with non-linear constraints have motivated researchers in using machine learning (ML) techniques like deep learning (DL) for accelerated design of metasurfaces. For metasurfaces, it is difficult to make quantitative comparisons between different ML models without having a common and yet complex dataset used in many disciplines like image classification. Many studies were directed to a relatively constrained datasets that are limited to specified patterns or shapes in metasurfaces. In this paper, we present our SUTD polarized reflection of complex metasurfaces (SUTD-PRCM) dataset, which contains approximately 260,000 samples of complex metasurfaces created from electromagnetic simulation, and it has been used to benchmark our DL models. The metasurface patterns are divided into different classes to facilitate different degree of complexity, which involves identifying and exploiting the relationship between the patterns and the electromagnetic responses that can be compared in using different DL models. With the release of this SUTD-PRCM dataset, we hope that it will be useful for benchmarking existing or future DL models developed in the ML community. We also propose a classification problem that is less encountered and apply neural architecture search to have a preliminary understanding of potential modification to the neural architecture that will improve the prediction by DL models. Our finding shows that convolution stacking is not the dominant element of the neural architecture anymore, which implies that low-level features are preferred over the traditional deep hierarchical high-level features thus explains why deep convolutional neural network based models are not performing well in our dataset., Comment: 20 pages, 7 figures, 2 tables

Exploiting topological ideas has been a major theme in modern photonics, which provides unprecedented opportunities to design photonic devices with robustness against defects and flaws. While most previous works in topological photonics have focused on band theory, recent theoretical advances extend the topological concepts to the analysis of scattering matrices and suggest a topological route to complete polarization conversion (CPC), a unique photonic phenomenon without an electronic counterpart. Here, we report on the experimental observation of the topological effect in reflection matrices of a photonic crystal slab, enabling CPC between two linear polarizations over a wide range of frequencies. Using angle-resolved reflection measurements, we observe CPC occurring at vortex singularities of reflection coefficients in momentum space, verifying the topological nature of CPC. In addition, the topological effect also guarantees the spin-preserved reflection of a circularly polarized wave. Remarkably, we experimentally establish a connection between two seemingly unrelated topological phenomena--CPC and bound states in the continuum (BICs): BICs lie on the critical coupling curves that define the condition for CPC. Our work paves the way to exploring the topological properties in scattering matrices for controlling light polarization and spin and creating robust photonic devices., Comment: 11 pages, 4 figures

Photonic topological states, providing light-manipulation approaches in robust manners, have attracted intense attention. Connecting photonic topological states with far-field degrees of freedom(DoFs) has given rise to fruitful phenomena. Recently emerged higher-order topological insulators (HOTIs), hosting boundary states two or more dimensions lower than those of bulk, offer new paradigms to localize/transport light topologically in extended dimensionalities. However, photonic HOTIs have not been related to DoFs of radiation fields yet. Here, we report the observation of polarization-orthogonal second-order topological corner states at different frequencies on a designer-plasmonic Kagome metasurface in the far field.Such phenomenon stands on two mechanisms, i.e., projecting the far-field polarizations to the intrinsic parity DoFs of lattice modes and the parity splitting of the plasmonic corner states in spectra. We theoretically and numerically show that the parity splitting originates from the underlying inter-orbital coupling. Both near-field and far-field experiments verify the polarization-orthogonal nondegeneratesecond-order topological corner states. These results promise applications in robust optical single photon emitters and multiplexed photonic devices., Comment: 18 pages, 4 figures

A permanent magnet array (PMA) is a preferred source of magnetic field for body-part-dedicated low-field (<0.5 T) portable magnetic resonance imaging (MRI) because it has a small footprint, no power consumption, and no need for a cooling system. The current popular PMA is limited by the transversal field below 100 mT, where advanced technologies developed for the long-bore MRI systems (e.g., multi-channel techniques) cannot be applied. In this paper, a sparse high-performance PMA is proposed based on inward-outward ring pairs and using magnet blocks that can be bought off the shelf, targeting on portable head imaging. Through a fast genetic algorithm (GA)-based optimization, the proposed PMA has a longitudinal magnetic field with an average field strength of 111.40 mT and a monotonic field pattern with inhomogeneity of 10.57 mT (an RF bandwidth of <10%) within a Field of View (FoV) of 20 cm in diameter and 4.5 cm in length. The resulting field was validated using analytic calculations and numerical simulations. The encoding capability of the designed PMA was examined by checking the quality of the simulated reconstructed images. The proposed field outperforms a linear pattern for encoding. The PMA is 57.91 cm wide, 38 cm long, has a 5-gauss range of 87x87x104 cm^3, allowing an operation in a small space. It weights 126.08kg, comprising of a stationary main array that supplies a strong homogeneous field, and a light rotatable sub-gradient-array (5.12kg) that supplies a monotonic field for signal encoding. It has a magnetic field generation efficiency of 0.88mT/kg, the highest among sparse PMAs that offer a monotonic field pattern. The force experienced by each magnet was calculated to validate the feasibility of physical implementation. The proposed PMA can be a promising alternative to supply the main and gradient fields combined for dedicated portable MRI.

Metasurfaces based on subwavelength resonators enable novel ways to manipulate the flow of light at optical interfaces. In pursuit of multifunctional or reconfigurable metadevices, efficient tuning of macroscopic performance with little structural/material variation remains a challenge. Here, we put forward the concept of non-Hermitian doping in metasurfaces, showing that an ordinary retroreflector can be switched to asymmetric one by introducing absorptive defects in local regions. The asymmetric absorption performance begins with zero at the Hermitian state, gradually increases under non-Hermitian doping, and reaches the maximum of unity at the exceptional point. This effect is experimentally demonstrated at microwave frequencies via the observation of asymmetric near-field distribution and far-field scattering properties and from a planar metasurface. Furthermore, while importing local gain constituents in conventional retroreflector, it can be tuned to an extremely asymmetric one-side amplifier, extending unidirectional amplification from one-dimensional waveguide to two-dimensional scattering systems. The proposed methodology provides an alternative pathway for engineering electromagnetic metadevices and systems with small perturbations. Introduction, Comment: 20 pages, 4 figures

Photonic topological states have revolutionized our understanding on the propagation and scattering of light. Recent discovery of higher-order photonic topological insulators opens an emergent horizon for zero-dimensional topological corner states. However, the previous realizations of higher-order photonic topological insulators suffer from either a limited operational frequency range due to the lumped components involved or a bulky structure with a large footprint, which are unfavorable for future integrated photonics. To overcome these limitations, we hereby experimentally demonstrate a planar surface-wave photonic crystal realization of two-dimensional higher-order topological insulators. The surface-wave photonic crystals exhibit a very large bulk bandgap (a bandwidth of 28%) due to multiple Bragg scatterings and host one-dimensional gapped edge states described by massive Dirac equations. The topology of those higher-dimensional photonic bands leads to the emergence of zero-dimensional corner states, which provide a route toward robust cavity modes for scalable, integrated photonic chips and an interface for the control of light-matter interaction., Comment: 14 pages, 4 figures

Hyperbolic polaritons in van der Waals materials and metamaterial heterostructures provide unprecedented control over light-matter interaction at the extreme nanoscale. Here, we propose a concept of type-I hyperbolic metasurface supporting highly-squeezed magnetic designer polaritons, which act as magnetic analogues to hyperbolic polaritons in the hexagonal boron nitride (h-BN) in the first Reststrahlen band. Comparing with the natural h-BN, the size and spacing of the metasurface unit cell can be readily scaled up (or down), allowing for manipulating designer polaritons in frequency and in space at will. Experimental measurements display the cone-like hyperbolic dispersion in the momentum space, associating with an effective refractive index up to 60 and a group velocity down to 1/400 of the light speed in vacuum. By tailoring the proposed metasurface, we experimentally demonstrate an ultra-compact (with a footprint shrunken by 3600 times) integrated designer polariton circuit including high-transmission 90{\deg} sharp bending waveguides and waveguide splitters. The designed metasurface with a low profile, lightweight, and ease of access, can serve as an alternatively promising platform for emerging polaritonics, and may find many other potential applications, such as waveguiding, sensing, subdiffraction focusing/imaging, low-threshold Cherenkov radiation, strong magnetic transition enhancement, wireless energy transfer, and so forth., Comment: 15 pages, 5 figures

Superscattering, induced by degenerate resonances, breaks the fundamental single-channel limit of scattering cross section of subwavelength structures; in principle, an arbitrarily large total cross section can be achieved via superscattering. It thus provides a unique way to strengthen the light-matter interaction at the subwavelength scale, and has many potential applications in sensing, energy harvesting, bio-imaging (such as magnetic resonance imaging), communication and optoelectronics. However, the experimental demonstration of superscattering remains an open challenge due to its vulnerability to structural imperfections and intrinsic material losses. Here we report the first experimental evidence for superscattering, by demonstrating the superscattering simultaneously in two different frequency regimes through both the far-field and near-field measurements. The underlying mechanism for the observed superscattering is the degenerate resonances of confined surface waves, by utilizing a subwavelength metasurface-based multilayer structure. Our work paves the way towards practical applications based on superscattering.

The ancient paper craft of kirigami has recently emerged as a potential tool for the design of functional materials. Inspired by the kirigami concept, we propose a class of kirigami-based metamaterials whose electromagnetic functionalities can be switched between nonchiral and chiral states by stretching the predesigned split-ring resonator array. Single-band, dual-band and broadband circular polarizers with reconfigurable performance are experimentally demonstrated with maximum circular dichroisms of 0.88, 0.94 and 0.92, respectively. The underlying mechanism is explained and calculated via detailed analysis of the excited multipoles, including the electric, magnetic, and toroidal dipoles and quadrupole. Our approach enables tailoring the electromagnetic functionalities in kirigami patterns and provides an alternate avenue for reconfigurable optical metadevices with exceptional mechanical properties.

Valley degrees of freedom, providing a novel way to increase capacity and efficiency of information processing, have become an important instrument for photonics. Experimental studies on photonic topological valley kink states at interfaces between regions with opposite valley-Chern numbers have attracted much attention, however, were restricted to zigzag-type interfaces, largely limiting their applications such as geometry-dependent topological channel intersections. Here, we experimentally demonstrate and manipulate valley kink states at generic interfaces in subwavelength substrate-integrated photonic circuitry. We verify the robustness of the kink states by measuring transmissions of the kink states through twisted interfaces and interfaces with disorders. Based on the valley kink states at generic interfaces, we realize several topological channel intersections where photonic transport paths are related to geometries of the intersections. In comparison to those in previous works, the present valley photonic crystals have subwavelength thicknesses and excellent self-consistent electrical shielding, which are perfectly compatible with conventional substrate-integrated photonic circuitry. Our work opens a door to manipulate photonic valley pseudo-spins in substrate-integrated circuitry with robustness, easy access, and lightweight., Comment: 15 pages, 5 figures

The concept of an invisibility cloak is a fixture of science fiction, fantasy, and the collective imagination. However, a real device that could hide an object from sight in visible light from absolutely any viewpoint would be extremely challenging to build. The main obstacle to creating such a cloak is the coupling of the electromagnetic components of light, which would necessitate the use of complex materials with specific permittivity and permeability tensors. Previous cloaking solutions have involved circumventing this obstacle by functioning either in static (or quasi-static) fields where these electromagnetic components are uncoupled or in diffusive light scattering media where complex materials are not required. In this paper, we report concealing a large-scale spherical object from human sight from three orthogonal directions. We achieve this result by developing a three-dimensional (3D) homogeneous polyhedral transformation and a spatially invariant refractive index discretization that considerably reduce the coupling of the electromagnetic components of visible light. This approach allows for a major simplification in the design of 3D invisibility cloaks, which can now be created at a large scale using homogeneous and isotropic materials.

Superscattering, i.e., a phenomenon of the scattering cross section from a subwavelength object exceeding the single-channel limit, has important prospects in enhanced sensing/spectroscopy, solar cells, and biomedical imaging. Superscattering can be typically constructed only at a single frequency regime, and depends critically on the inescapable material losses. Under such realistic conditions, superscattering has not been predicted nor observed to exist simultaneously at multiple frequency regimes. Here we introduce multifrequency superscattering in a subwavelength hyperbolic structure, which can be made from artificial metamaterials or from naturally-existing materials, such as hexagonal boron nitride (BN), and show the advantage of such hyperbolic materials for reducing structural complexity. The underlying mechanism is revealed to be the multimode resonances at multiple frequency regimes as appear in BN due to the peculiar dispersion of phonon-polaritons. Importantly, the multifrequency superscattering has a high tolerance to material losses and some structural variations, bringing the concept of multifrequency superscattering closer to useful and realistic conditions., Comment: 5 figures

In nonlinear plasmonics, the switching threshold of optical bistability is limited by the weak nonlinear responses from the conventional Kerr dielectric media. Considering the giant nonlinear susceptibility of graphene, here we develop a nonlinear scattering model under the mean field approximation and study the bistable scattering in graphene-coated dielectric nanowires based on the semi-analytical solutions. We find that the switching intensities of bistable scattering can be smaller than 1MW/cm2 at the working frequency. To further decrease the switching intensities, we show that the most important factor that restricts the bistable scattering is the relaxation time of graphene, rather than the chemical potential and the permittivity of the dielectric nanowire. Our work not only reveals some general characteristics of graphene-based bistable scattering, but also provides a guidance to further applications of optical bistability in the high speed all-optical signal processing.

The energy-momentum dispersion relation is a fundamental property of plasmonic systems. In this paper, we show that the method of dispersion engineering can be used for the design of ultra-compact graphene-based superscatterers. Based on the Bohr model, the dispersion relation of the equivalent planar waveguide is engineered to enhance the scattering cross section of a dielectric cylinder. Bohr conditions with different orders are fulfilled in multiple dispersion curves at the same resonant frequency. Thus the resonance peaks from the first and second order scattering terms are overlapped in the deepsubwavelength scale by delicately tuning the gap thickness between two graphene layers. Using this ultra-compact graphene-based superscatterer, the scattering cross section of the dielectric cylinder can be enhanced by five orders of magnitude., Comment: This paper has been accepted by IEEE Journal of Selected topics in Quantum Electronics

An invisibility cloak that can hide an arbitrary object external to the cloak itself has not been devised before. In this Letter, we introduce a novel way to design a remote cloaking device that makes any object located at a certain distance invisible. This is accomplished using multi-folded transformation optics to remotely generate a hidden region around the object that no field can penetrate and that does not disturb the far-field scattering electromagnetic field. As a result, any object in the hidden region can stay in position or move freely within that region and remain invisible. Our idea is further extended in order to design a remote illusion optics that can transform any arbitrary object into another one. Unlike other cloaking methods, this method would require no knowledge of the details of the object itself. The proposed multi-folded transformation optics will be crucial in the design of remote devices in a variety of contexts.

We study analytically the plasmonic modes in the graphene-coated dielectric nanowire, based on the explicit form of nonlinear surface conductivity of graphene. The propagation constants of different plasmonic modes can be tuned by the input power at the order of a few tenths of mW. The lower and upper mode bifurcation branches are connected at the limitation value of the input power. Moreover, due to the nonlinearity of graphene, the dispersion curves of plasmonic modes at different input powers form an energy band, which is in sharp contrast with the single dispersion curve in the limit of zero input power.