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Empirical investigation of the quintillion-scale, functionally diverse antibody repertoires that can be generated synthetically or naturally is critical for identifying potential biotherapeutic leads, yet remains burdensome. We present high-throughput nanophotonics- and bioprinter-enabled screening (HT-NaBS), a multiplexed assay for large-scale, sample-efficient, and rapid characterization of antibody libraries. Our platform is built upon independently addressable pixelated nanoantennas exhibiting wavelength-scale mode volumes, high-quality factors (high-Q) exceeding 5000, and pattern densities exceeding one million sensors per square centimeter. Our custom-built acoustic bioprinter enables individual sensor functionalization via the deposition of picoliter droplets from a library of capture antigens at rates up to 25,000 droplets per second. We detect subtle differentiation in the target binding signature through spatially-resolved spectral imaging of hundreds of resonators simultaneously, elucidating antigen-antibody binding kinetic rates, affinity constant, and specificity. We demonstrate HT-NaBS on a panel of antibodies targeting SARS-CoV-2, Influenza A, and Influenza B antigens, with a sub-picomolar limit of detection within 30 minutes. Furthermore, through epitope binning analysis, we demonstrate the competence and diversity of a library of native antibodies targeting functional epitopes on a priority pathogen (H5N1 bird flu) and on glycosylated therapeutic Cetuximab antibodies against epidermal growth factor receptor. With a roadmap to image tens of thousands of sensors simultaneously, this high-throughput, resource-efficient, and label-free platform can rapidly screen for high-affinity and broad epitope coverage, accelerating biotherapeutic discovery and de novo protein design.

Achieving deterministic control over the properties of low-dimensional materials with nanoscale precision is a long-sought goal. Mastering this capability has a transformative impact on the design of multifunctional electrical and optical devices. Here, we present an ion-assisted synthetic technique that enables precise control over the material composition and energy landscape of two-dimensional (2D) atomic crystals. Our method transforms binary transition metal dichalcogenides (TMDs), like MoSe$_2$, into ternary MoS$_{2\alpha}$Se$_{2(1-{\alpha}})$ alloys with systematically adjustable compositions, ${\alpha}$. By piecewise assembly of the lateral, compositionally modulated MoS$_{2\alpha}$Se$_{2(1-{\alpha})}$ segments within 2D atomic layers, we present a synthetic pathway towards the realization of multi-compositional designer materials. Our technique enables the fabrication of complex structures with arbitrary boundaries, dimensions as small as 30 nm, and fully customizable energy landscapes. Our optical characterizations further showcase the potential for implementing tailored optoelectronics in these engineered 2D crystals., Comment: 22 pages, 5 Figures

Metasurfaces provide a versatile and compact approach to free-space optical manipulation and wavefront shaping. Comprised of arrays of judiciously-arranged dipolar resonators, metasurfaces precisely control the amplitude, polarization, and phase of light, with applications spanning imaging, sensing, modulation, and computing. Three crucial performance metrics of metasurfaces and their constituent resonators are the quality factor ($Q$-factor), mode-volume ($V_m$), and the ability to control far-field radiation. Often, resonators face a trade-off between these parameters: a reduction in $V_m$ leads to an equivalent reduction in $Q$, albeit with more control over radiation. Here, we demonstrate that this perceived compromise is not inevitable $-$ high-$Q$, subwavelength $V_m$, and controlled dipole-like radiation can be achieved, simultaneously. We design high-$Q$, very-large-scale integrated silicon nanoantenna pixels $-$ VINPix $-$ that combine guided mode resonance waveguides with photonic crystal cavities. With optimized nanoantennas, we achieve $Q$-factors exceeding 1500 with $V_m$ less than 0.1 $(\lambda/n_{\text{air}})^3$. Each nanoantenna is individually addressable by free-space light, and exhibits dipole-like scattering to the far-field. Resonator densities exceeding a million nanoantennas per $\text{cm}^2$ can be achieved, as demonstrated by our fabrication of an 8 mm x 8 mm VINPix array. As a proof-of-concept application, we demonstrate spectrometer-free, spatially localized, refractive-index sensing utilizing a VINPix array. Our platform provides a foundation for compact, densely multiplexed devices such as spatial light modulators, computational spectrometers, and in-situ environmental sensors.

Structural colors generated due to light scattering from static all-dielectric metasurfaces have successfully enabled high-resolution, high-saturation, and wide-gamut color printing applications. Despite recent advances, most demonstrations of these structure-dependent colors lack post-fabrication tunability. This hinders their applicability for front-end dynamic display technologies. Phase-change materials (PCMs), with significant contrast of their optical properties between their amorphous and crystalline states, have demonstrated promising potentials in reconfigurable nanophotonics. Herein, we leverage tunable all-dielectric reflective metasurfaces made of newly emerged classes of low-loss optical PCMs, i.e., antimony trisulphide (Sb$_2$S$_3$) and antimony triselenide (Sb$_2$Se$_3$), with superb characteristics to realize switchable, high-saturation, high-efficiency and high-resolution dynamic meta-pixels. Exploiting polarization-sensitive building blocks, the presented meta-pixel can generate two different colors when illuminated by either one of two orthogonally polarized incident beams. Such degrees of freedom (i.e., material phase and polarization state) enable a single reconfigurable metasurface with fixed geometrical parameters to generate four distinct wide-gamut colors. We experimentally demonstrate, for the first time, an electrically-driven micro-scale display through the integration of phase-change metasurfaces with an on-chip heater formed by transparent conductive oxide. Our experimental findings enable a versatile platform suitable for a wide range of applications, including tunable full-color printing, enhanced dynamic displays, information encryption, and anti-counterfeiting., Comment: arXiv admin note: substantial text overlap with arXiv:2105.01313

Structural colors generated due to light scattering from static all-dielectric metasurfaces have successfully enabled high-resolution, high-saturation and wide-gamut color printing applications. Despite recent advances, most demonstrations of these structure-dependent colors lack post-fabrication tunability that hinders their applicability for front-end dynamic display technologies. Phase-change materials (PCMs), with significant contrast of their optical properties between their amorphous and crystalline states, have demonstrated promising potentials in reconfigurable nanophotonics. Herein, we leverage a tunable all-dielectric reflective metasurface made of a newly emerged class of low-loss optical PCMs with superb characteristics, i.e., antimony trisulphide (Sb$_2$S$_3$), antimony triselenide (Sb$_2$Se$_3$), and binary germanium-doped selenide (GeSe$_3$), to realize switchable, high-saturation, high-efficiency and high-resolution structural colors. Having polarization sensitive building blocks, the presented metasurface can generate two different colors when illuminated by two orthogonally polarized incident beams. Such degrees of freedom (i.e., structural state and polarization) enable a single reconfigurable metasurface with fixed geometrical parameters to generate four distinct wide-gamut colors suitable for a wide range of applications, including tunable full-color printing and displays, information encryption, and anti-counterfeiting.

Despite recent advances in active metaoptics, wide dynamic range combined with high-speed reconfigurable solutions is still elusive. Phase-change materials (PCMs) offer a compelling platform for metasurface optical elements, owing to the large index contrast and fast yet stable phase transition properties. Here, we experimentally demonstrate an in situ electrically-driven reprogrammable metasurface by harnessing the unique properties of a phase-change chalcogenide alloy, Ge$_{2}$Sb$_{2}$Te$_{5}$ (GST), in order to realize fast, non-volatile, reversible, multilevel, and pronounced optical modulation in the near-infrared spectral range. Co-optimized through a multiphysics analysis, we integrate an efficient heterostructure resistive microheater that indirectly heats and transforms the embedded GST film without compromising the optical performance of the metasurface even after several reversible phase transitions. A hybrid plasmonic-PCM meta-switch with a record electrical modulation of the reflectance over eleven-fold (an absolute reflectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and switching speed that can potentially reach a few kHz is presented. Our work represents a significant step towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications.

Efficient hybrid plasmonic-photonic metasurfaces that simultaneously take advantage of the potential of both pure metallic and all-dielectric nanoantennas are identified as an emerging technology in flat optics. Nevertheless, post-fabrication tunable hybrid metasurfaces are still elusive. Here, we present a reconfigurable hybrid metasurface platform by incorporating the phase-change material Ge$_{2}$Sb$_{2}$Te$_{5}$ (GST) into metal-dielectric meta-atoms for active and non-volatile tuning of properties of light. We systematically design a reduced-dimension meta-atom, which selectively controls the fundamental hybrid plasmonic-photonic resonances of the metasurface via the dynamic change of optical constants of GST without compromising the scattering efficiency. As a proof-of-concept, we experimentally demonstrate miniaturized tunable metasurfaces that control the amplitude and phase of incident light necessary for high-contrast optical switching and anomalous to specular beam deflection, respectively. Finally, we leverage a deep learning-based approach to present an intuitive low-dimensional visualization of the enhanced range of response reconfiguration enabled by the addition of GST. Our findings further substantiate dynamically tunable hybrid metasurfaces as promising candidates for the development of small-footprint energy harvesting, imaging, and optical signal processing devices.

Rapidly growing demands for high-performance computing, powerful data processing systems, and big data necessitate the advent of novel optical devices to perform demanding computing processes effectively. Due to its unprecedented growth in the past two decades, the field of meta-optics offers a viable solution for spatially, spectrally, and/or even temporally sculpting amplitude, phase, polarization, and/or dispersion of optical wavefronts. In this Review, we discuss state-of-the-art developments as well as emerging trends in computational meta-structures as disruptive platforms for spatial optical analog computation. Two fundamental approaches based on general concepts of spatial Fourier transformation and Green's function are discussed in detail. Moreover, numerical investigations and experimental demonstrations of computational optical surfaces and meta-structures for solving a diverse set of mathematical problems (e.g., integro-differentiation and convolution equations) necessary for on-demand applications (e.g., edge detection) are reviewed. Finally, we explore the current challenges and the potential resolutions in computational meta-optics followed by our perspective on future research directions and possible developments in this promising area.

Inducing a large refractive-index change is the holy grail of reconfigurable photonic structures, a goal that has long been the driving force behind the discovery of new optical material platforms. Recently, the unprecedentedly large refractive-index contrast between the amorphous and crystalline states of Ge-Sb-Te (GST)-based phase-change materials (PCMs) has attracted tremendous attention for reconfigurable integrated nanophotonics. Here, we introduce a microheater platform that employs optically transparent and electrically conductive indium-tin-oxide (ITO) bridges for the fast and reversible electrical switching of the GST phase between crystalline and amorphous states. By the proper assignment of electrical pulses applied to the ITO microheater, we show that our platform allows for the registration of virtually any intermediate crystalline state into the GST film integrated on the top of the designed microheaters. More importantly, we demonstrate the full reversibility of the GST phase between amorphous and crystalline states. To show the feasibility of using this hybrid GST/ITO platform for miniaturized integrated nanophotonic structures, we integrate our designed microheaters into the arms of a Mach-Zehnder interferometer to realize electrically reconfigurable optical phase shifters with orders of magnitude smaller footprints compared to existing integrated photonic architectures. We show that the phase of optical signals can be gradually shifted in multiple intermediate states using a structure that can potentially be smaller than a single wavelength. We believe that our study showcases the possibility of forming a whole new class of miniaturized reconfigurable integrated nanophotonics using beyond-binary reconfiguration of optical functionalities in hybrid PCM-photonic devices.

Nanophotonics has garnered intensive attention due to its unique capabilities in molding the flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated circuits (PICs) enable the realization of mass-producible, cost-effective, and highly efficient flat optical components for imaging, sensing, and communications. In order to enable nanophotonics with multi-purpose functionalities, chalcogenide phase-change materials (PCMs) have been introduced as a promising platform for tunable and reconfigurable nanophotonic frameworks. Integration of non-volatile chalcogenide PCMs with unique properties such as drastic optical contrasts, fast switching speeds, and long-term stability grants substantial reconfiguration to the more conventional static nanophotonic platforms. In this review, we discuss state-of-the-art developments as well as emerging trends in tunable MSs and PICs using chalcogenide PCMs. We outline the unique material properties, structural transformation, electro-optic, and thermo-optic effects of well-established classes of chalcogenide PCMs. The emerging deep learning-based approaches for the optimization of reconfigurable MSs and the analysis of light-matter interactions are also discussed. The review is concluded by discussing existing challenges in the realization of adjustable nanophotonics and a perspective on the possible developments in this promising area.

We present here a new approach for using the intelligence aspects of artificial intelligence for knowledge discovery rather than device optimization in electromagnetic (EM) nanostructures. This approach uses training data obtained through full-wave EM simulations of a series of nanostructures to train geometric deep learning algorithms to assess the range of feasible responses as well as the feasibility of a desired response from a class of EM nanostructures. To facilitate the knowledge discovery and reduce the computation complexity, our approach combines the dimensionality reduction technique (using an autoencoder) with convex-hull and one-class support-vector-machine (SVM) algorithms to find the range of the feasible responses in the latent (or the reduced) response space of the EM nanostructure. We show that by using a small set of training instances (compared to all possible structures), our approach can provide better than 95% accuracy in assessing the feasibility of a given response. More importantly, the one-class SVM algorithm can be trained to provide the degree of feasibility (or unfeasibility) of a response from a given nanostructure. This important information can be used to modify the initial structure to an alternative one that can enable an initially unfeasible response. To show the applicability of our approach, we apply it to two important classes of binary metasurfaces (MSs), formed by array of plasmonic nanostructures, and periodic MSs formed by an array of dielectric nanopillars. In addition to theoretical results, we show the experimental results obtained by fabricating several MSs of the second class. Our theoretical and experimental results confirm the unique features of this approach for knowledge discovery in EM nanostructures., Comment: Adv. Intell. Syst. (2020)

In contrast to lossy plasmonic metasurfaces (MSs), wideband dielectric MSs comprising of subwavelength nanostructures supporting Mie resonances are of great interest in the visible wavelength range. Here, for the first time to our knowledge, we experimentally demonstrate a reflective MS consisting of a square-lattice array of Hafnia (HfO$_2$) nanopillars to generate a wide color gamut. To design and optimize these MSs, we use a deep-learning algorithm based on a dimensionality reduction technique. Good agreement is observed between simulation and experimental results in yielding vivid and high-quality colors. We envision that these structures not only empower the high-resolution digital displays and sensitive colorimetric biosensors but also can be applied to on-demand applications of beaming in a wide wavelength range down to deep ultraviolet.

In this paper, we present a deep learning-based (DL-based) algorithm, as a purely mathematical platform, for providing intuitive understanding of the properties of electromagnetic (EM) wave-matter interaction in nanostructures. This approach is based on using the dimensionality reduction (DR) technique to significantly reduce the dimensionality of a generic EM wave-matter interaction problem without imposing significant error. Such an approach implicitly provides useful information about the role of different features (or design parameters such as geometry) of the nanostructure in its response functionality. To demonstrate the practical capabilities of this DL-based technique, we apply it to a reconfigurable optical metadevice enabling dual-band and triple-band optical absorption in the telecommunication window. Combination of the proposed approach with existing commercialized full-wave simulation tools offers a powerful toolkit to extract basic mechanisms of wave-matter interaction in complex EM devices and facilitate the design and optimization of nanostructures for a large range of applications including imaging, spectroscopy, and signal processing. It is worth to mention that the demonstrated approach is general and can be used in a large range of problems as long as enough training data can be provided.

In this paper, we demonstrate a computationally efficient new approach based on deep learning (DL) techniques for analysis, design, and optimization of electromagnetic (EM) nanostructures. We use the strong correlation among features of a generic EM problem to considerably reduce the dimensionality of the problem and thus, the computational complexity, without imposing considerable errors. By employing the dimensionality reduction concept using the more recently demonstrated autoencoder technique, we redefine the conventional many-to-one design problem in EM nanostructures into a one-to-one problem plus a much simpler many-to-one problem, which can be simply solved using an analytic formulation. This approach reduces the computational complexity in solving both the forward problem (i.e., analysis) and the inverse problem (i.e., design) by orders of magnitude compared to conventional approaches. In addition, it provides analytic formulations that, despite their complexity, can be used to obtain intuitive understanding of the physics and dynamics of EM wave interaction with nanostructures with minimal computation requirements. As a proof-of-concept, we applied such an efficacious method to design a new class of on-demand reconfigurable optical metasurfaces based on phase-change materials (PCM). We envision that the integration of such a DL-based technique with full-wave commercial software packages offers a powerful toolkit to facilitate the analysis, design, and optimization of the EM nanostructures as well as explaining, understanding, and predicting the observed responses in such structures.

We present a hybrid device platform for creating an electrically reconfigurable metasurface formed by the integration of plasmonic nanostructures with phase-change material germanium antimony telluride (GST). By changing the phase of GST from amorphous to crystalline through Joule heating, a large range of responses from the metasurface can be achieved. Furthermore, by using the intermediate phases of GST, the metasurface can interact with the incident light in both over-coupling and under-coupling regimes, leading to an inherently broadband response. Through a detailed investigation of the nature of the fundamental modes, we demonstrate that changing the crystalline phase of the GST at the pixel-level enables an effective control over the key properties (i.e., amplitude, phase, and polarization) of incident light. This leads to the realization of a broadband electrically tunable multi-functional metadevice enabling beam switching, focusing, steering, and polarization conversion. Such a hybrid structure offers a high-speed, broadband, and non-volatile reconfigurable paradigm for electrically programmable optical devices such as switches, holograms, and polarimeters.

Optical signal propagation through underwater channels is affected by three main degrading phenomena, namely absorption, scattering, and fading. In this paper, we experimentally study the statistical distribution of intensity fluctuations in underwater wireless optical channels with random temperature and salinity variations as well as the presence of air bubbles. In particular, we define different scenarios to produce random fluctuations on the water refractive index across the propagation path, and then examine the accuracy of various statistical distributions in terms of their goodness of fit to the experimental data. We also obtain the channel coherence time to address the average period of fading temporal variations. The scenarios under consideration cover a wide range of scintillation index from weak to strong turbulence. Moreover, the effects of beam-collimator at the transmitter side and aperture averaging lens at the receiver side are experimentally investigated. We show that the use of a transmitter beam-collimator and/or a receiver aperture averaging lens suits single-lobe distributions such that the generalized Gamma and exponential Weibull distributions can excellently match the histograms of the acquired data. Our experimental results further reveal that the channel coherence time is on the order of $10^{-3}$ seconds and larger which implies to the slow fading turbulent channels.

Inspired by the ever-increasing demand for higher data transmission rates and the tremendous attention toward all-optical signal processing based on miniaturized nanophotonics, in this paper, for the first time, we investigate the integrable design of coherent ultrashort light pulse code-division multiple-access (CDMA) technique, also known as femtosecond CDMA, using all-dielectric metasurfaces (MSs). In this technique, the data bits are firstly modulated using ultrashort femtosecond optical pulses generated by mode-locked lasers, and then by employing a unique phase metamask for each data stream, in order to provide the multiple access capability, the optical signals are spectrally encoded. This procedure spreads the optical signal in the temporal domain and generates low-intensity pseudo-noise bursts through random phase coding leading to minimized multiple access interference. This paper comprehensively presents the principles and design approach to realize fundamental components of a typical femtosecond CDMA encoder, including the grating, lens, and phase mask, by employing high-contrast CMOS-compatible MSs. By controlling the interference between the provided Mie and Fabry-Perot resonance modes, we tailor the spectral and spatial responses of the impinging light locally and independently. Accordingly, we design a MS-based grating with the highest possible refracted angle and, in the meantime, the maximized efficiency which results in a reasonable diameter for the subsequent lens. Moreover, to design our MS-based lens commensurate with the spot size and distance requirements of the pursuant phase mask, we leverage a new optimization method which splits the lens structure into central and peripheral parts, and then design the peripheral part using a collection of gratings converging the impinging at the subsequent phase mask.

Anomalous group velocity dispersion is a key parameter for generating bright solitons, and thus wideband Kerr frequency combs. Extension of frequency combs to visible wavelength in conventional photonic materials and structures has been a major challenge due to strong normal material dispersion at the relevant frequencies. Extension of frequency combs toward the normal dispersion region is possible via dispersive waves through soliton-induced Cherenkov radiation. However, this potentially powerful technique has not been used for extending frequency combs to the visible spectrum. In this paper, we demonstrate a new microresonator structure formed by an over-etched silicon nitride waveguide that enables the use of soliton-induced Cherenkov radiation to extend the bandwidth of the Kerr-combs. Furthermore, we show that by careful dispersion engineering in a coupled microring resonator structure we can optimize the properties (e.g., wavelength, and amplitude) of the generated dispersive wave to further extend the Kerr frequency combs to the visible spectrum while increasing the total Kerr-comb bandwidth as well.

In this paper, we realize the concept of analog computing using an array of engineered gradient dielectric meta-reflect-array. The proposed configuration consists of individual subwavelength silicon nanobricks in combination with fused silica spacer and silver ground plane realizing a reflection beam with full phase coverage $2\pi$ degrees as well as amplitude range $0$ to $1$. Spectrally overlapping electric and magnetic dipole resonances, such high-index dielectric metasurfaces can locally and independently manipulate the amplitude and phase of the incident electromagnetic wave. This practically feasible structure overcomes substantial limitations imposed by plasmonic metasurfaces such as absorption losses and low polarization conversion efficiency in the visible range. Using such CMOS-compatible and easily integrable platforms promises highly efficient ultrathin planar wave-based computing systems which circumvent the drawbacks of conventional bulky lens-based signal processors. Based on these key properties and general concept of spatial Fourier transformation, we design and realize broadband mathematical operators such as differentiator and integrator in the telecommunication wavelengths.

In this paper, a plasmonic absorber consisting of a metal-dielectric-metal stack with a top layer of Sierpinski nanocarpet is theoretically investigated. Such compact absorber depicts broadband angle-independent behavior over a wide optical wavelength range ($400-700$ nm) and a broad range of angles of light incidence ($0-80^{\circ}$). Including several feature sizes, such fractal-like structure shows widely strong extinction ($85-99$%) response for either transverse electric or magnetic polarization states under normal incidence. Underlying mechanisms of absorbance due to excited surface plasmon modes as well as electric/magnetic dipole resonances are well revealed by investigating electric field, magnetic field and current distributions. The proposed absorber opens a path to realize high-performance ultrathin light trapping devices.

Optical computing has emerged as a promising candidate for real-time and parallel continuous data processing. Motivated by recent progresses in metamaterial-based analog computing [Science 343, 160 (2014)], we theoretically investigate realization of two-dimensional complex mathematical operations using rotated configurations, recently reported in [Opt. Lett. 39, 1278 (2014)]. Breaking the reflection symmetry, such configurations could realize both even and odd Green's functions associated with spatial operators. Based on such appealing theory and by using Brewster effect, we demonstrate realization of a first-order differentiator. Such efficient wave-based computation method not only circumvents the major potential drawbacks of metamaterials, but also offers the most compact possible device compared to the conventional bulky lens-based optical signal and data processors., Comment: 4 pages, 7 figures, journal

In this paper, we present an optical computing method for string data alignment applicable to genome information analysis. By applying moire technique to spatial encoding patterns of deoxyribonucleic acid (DNA) sequences, association information of the genome and the expressed phenotypes could more effectively be extracted. Such moire fringes reveal occurrence of matching, deletion and insertion between DNA sequences providing useful visualized information for prediction of gene function and classification of species. Furthermore, by applying a cylindrical lens, a new technique is proposed to map two-dimensional (2D) association information to a one-dimensional (1D) column of pixels, where each pixel in the column is representative of superposition of all bright and dark pixels in the corresponding row. By such a time-consuming preprocessing, local similarities between two intended patterns can readily be found by just using a 1D array of photodetectors and postprocessing could be performed on specified parts in the initial 2D pattern. We also evaluate our proposed circular encoding adapted for poor data alignment condition. Our simulation results together with experimental implementation verify the effectiveness of our dynamic proposed methods which significantly improve system parameters such as processing gain and signal to noise ratio (SNR).

In this paper, we experimentally investigate the statistical distribution of intensity fluctuations for underwater wireless optical channels under different channel conditions, namely fresh and salty underwater channels with and without air bubbles. To do so, we first measure the received optical signal with a large number of samples. Based on the normalized acquired data the channel coherence time and the fluctuations probability density function (PDF) are obtained for different channel scenarios. Our experimental results show that salt attenuates the received signal while air bubbles mainly introduce severe intensity fluctuations. Moreover, we observe that log-normal distribution precisely fits the acquired data PDF for scintillation index ($\sigma^2_I$) values less than $0.1$, while Gamma-Gamma and K distributions aptly predict the intensity fluctuations for $\sigma^2_I>1$. Since neither of these distributions are capable of predicting the received irradiance for $0.1<\sigma^2_I<1$, we propose a combination of an exponential and a log-normal distributions to perfectly describe the acquired data PDF for such regimes of scintillation index.

We introduce the new concept of "metalines" for manipulating the amplitude and phase profile of an incident wave locally and independently. Thanks to the highly confined graphene plasmons, a transmit-array of graphene-based metalines is used to realize analog computing on an ultra-compact, integrable and planar platform. By employing the general concepts of spatial Fourier transformation, a well-designed structure of such meta-transmit-array combined with graded index lenses can perform two mathematical operations; i.e. differentiation and integration, with high efficiency. The presented configuration is about 60 times shorter than the recent structure proposed by Silva et al.(Science, 2014, 343, 160-163); moreover, our simulated output responses are in more agreement with the desired analytic results. These findings may lead to remarkable achievements in light-based plasmonic signal processors at nanoscale instead of their bulky conventional dielectric lens-based counterparts.