Sandeep Inampudi

Diffractive interface theory: nonlocal susceptibility approach to the optics of metasurfaces

We present a formalism for understanding the electromagnetism of metasurfaces, optically thin composite films with engineered diffraction. The technique, diffractive interface theory (DIT), takes explicit advantage of the small optical thickness of a metasurface, eliminating the need for solving for light propagation inside the film and providing a direct link between the spatial profile of a metasurface and its diffractive properties. Predictions of DIT are compared with full-wave numerical solutions of Maxwells equations, demonstrating DITs validity and computational advantages for optically thin structures. Applications of the DIT range from understanding of fundamentals of light-matter interaction in metasurfaces to efficient analysis of generalized refraction to metasurface optimization.

Optimization-based Dielectric Metasurfaces for Angle-Selective Multifunctional Beam Deflection

Synthesization of multiple functionalities over a flat metasurface platform offers a promising approach to achieving integrated photonic devices with minimized footprint. Metasurfaces capable of diverse wavefront shaping according to wavelengths and polarizations have been demonstrated. Here we propose a class of angle-selective metasurfaces, over which beams are reflected following different and independent phase gradients in the light of the beam direction. Such powerful feature is achieved by leveraging the local phase modulation and the non-local lattice diffraction via inverse scattered field and geometry optimization in a monolayer dielectric grating, whereas most of the previous designs utilize the local phase modulation only and operate optimally for a specific angle. Beam combiner/splitter and independent multibeam deflections with up to 4 incident angles are numerically demonstrated respectively at the wavelength of 700 nm. The deflection efficiency is around 45% due to the material loss and the compromise of multi-angle responses. Flexibility of the approach is further validated by additional designs of angle-switchable metagratings as splitter/reflector and transparent/opaque mirror. The proposed designs hold great potential for increasing information density of compact optical components from the degree of freedom of angle.

Manipulation of surface plasmon polariton propagation on isotropic and anisotropic two-dimensional materials coupled to boron nitride heterostructures

We present a comprehensive analysis of surface plasmonpolaritondispersioncharacteristics associated with isotropic and anisotropic two-dimensional atomically thin layered materials (2D sheets) coupled to h-BN heterostructures. A scattering matrix based approach is presented to compute the electromagnetic fields and related dispersioncharacteristics of stacked layered systems composed of anisotropic 2D sheets and uniaxial bulk materials. We analyze specifically the surface plasmonpolariton (SPP) dispersioncharacteristics in case of isolated and coupled two-dimensional layers with isotropic and anisotropic conductivities. An analysis based on residue theorem is utilized to identify optimum optical parameters (surface conductivity) and geometrical parameters (separation between layers) to maximize the SPP field at a given position. The effect of type and degree of anisotropy on the shapes of iso-frequency curves and propagation characteristics is discussed in detail. The analysis presented in this paper gives an insight to identify optimum setup to enhance the SPP field at a given position and in a given direction on the surface of two-dimensional materials.

Terahertz transmission ellipsometry of vertically aligned multi-walled carbon nanotubes

We demonstrate time-resolved terahertz transmission ellipsometry of vertically aligned multi-walled carbon nanotubes. The angle-resolved transmission measurements reveal anisotropic characteristics of the terahertz electrodynamics in multi-walled carbon nanotubes. The anisotropy is, however, unexpectedly weak: the ratio of the tube-axis conductivity to the transverse conductivity, σz/σxy≅2.3, is nearly constant over the broad spectral range of 0.4–1.6 THz. The relatively weak anisotropy and the strong transverse electrical conduction indicate that THz fields readily induce electron transport between adjacent shells within multi-walled carbon nanotubes.

Unidirectional thermal radiation from a SiC metasurface

Emission of thermal radiation from periodically patterned surfaces that support surface phonon polaritons has always been into two symmetric emission angles. This is because of the nature of randomness in the thermal spectrum of a hot body that symmetrically distributes the heat into counterpropagating surface waves. Here we demonstrate the design method of metasurfaces with unconventional unit cell dimension and internal structure to direct the thermal radiation into a single specific emission angle. We utilize a combination of diffraction order engineering and numerical optimization techniques for the design process of an ultra-thin metasurface to couple counterpropagating surface waves into a single emission direction. In addition, we compute the near-field incoherent thermal emission intensity from the metasurface by combining the concepts of fluctuation dissipation theorem with solutions of Maxwell’s equations based on rigorous coupled-wave analysis and demonstrate unidirectional phaseless thermal radiation emission. The developed approach serves as a tool to design metasurfaces for manipulation of light sources with more complex nature than a plane wave.

Diffractive imaging route to sub-wavelength pixels

We propose optical imaging technique that relies on diffractive rather than refractive elements. Our approach takes advantage of metagratings, structures with engineered diffraction properties, and natural materials with sufficiently high refractive indices to achieve significant reduction in pixel size. In contrast to conventional refraction-based imaging, the developed approach essentially produces a digital hologram, a low-dimensional projection of the volumetric optical field. The perspectives of numerical recovery of the optical field and the stability of such recovery are discussed.

Fresnel Refraction and Diffraction of Surface Plasmon Polaritons in Two-Dimensional Conducting Sheets

The propagation of surface plasmon polaritons (SPPs) along two-dimensional (2D) materials, such as graphene, is a complex phenomenon linking the microscale electronic properties to macroscale optical properties. Complex geometries increase the complexity of understanding the nature and performance of optoelectronic devices based on surface wave propagation. Here, we demonstrate that under a proper design of macroscopic conductivity profile, the propagation characteristics of SPPs in 2D materials can be made analogous to the propagation of plane waves in homogeneous layers with minimal out-of-plane scattering. Such a direct resemblance enables prediction, design, and calculation of SPP propagation through advanced geometries using fundamental laws of optics. We demonstrate that the propagation of surface waves can be manipulated in-plane using reflection, refraction, diffraction, and also generalized refraction laws analogous to plane waves. We present simple mathematical models to calculate the scattered electromagnetic fields of SPP waves based on Fresnel equations. The presented formulation could facilitate the transfer of many existing plane wave based optical phenomenon to a surface wave based integrated optoelectronic devices.

Interscale mixing microscopy: numerically stable imaging of wavelength- scale objects with sub-wavelength resolution and far field measurements

We present an imaging technique that allows the recovery of the profile of wavelength-scale objects with deep subwavelength resolution based on far-field intensity measurements. The approach, interscale mixing microscopy (IMM), relies on diffractive elements positioned in the near-field proximity of an object in order to scatter information carried by evanescent waves into propagating part of the spectrum. A combination of numerical solutions of Maxwell equations and nonlinear fitting is then used to recover the information about the object based on far-field intensity measurements. It is demonstrated that IMM has the potential to recover wavelength/20 features of wavelength-scale objects in the presence of 10% noise.

Adaptive Genetic Algorithm for Optical Metasurfaces Design

As optical metasurfaces become progressively ubiquitous, the expectations from them are becoming increasingly complex. The limited number of structural parameters in the conventional metasurface building blocks, and existing phase engineering rules do not completely support the growth rate of metasurface applications. In this paper, we present digitized-binary elements, as alternative high-dimensional building blocks, to accommodate the needs of complex-tailorable-multifunctional applications. To design these complicated platforms, we demonstrate adaptive genetic algorithm (AGA), as a powerful evolutionary optimizer, capable of handling such demanding design expectations. We solve four complex problems of high current interest to the optics community, namely, a binary-pattern plasmonic reflectarray with high tolerance to fabrication imperfections and high reflection efficiency for beam-steering purposes, a dual-beam aperiodic leaky-wave antenna, which diffracts TE and TM excitation waveguides modes to arbitrarily chosen directions, a compact birefringent all-dielectric metasurface with finer pixel resolution compared to canonical nano-antennas, and a visible-transparent infrared emitting/absorbing metasurface that shows high promise for solar-cell cooling applications, to showcase the advantages of the combination of binary-pattern metasurfaces and the AGA technique. Each of these novel applications encounters computational and fabrication challenges under conventional design methods, and is chosen carefully to highlight one of the unique advantages of the AGA technique. Finally, we show that large surplus datasets produced as by-products of the evolutionary optimizers can be employed as ingredients of the new-age computational algorithms, such as, machine learning and deep leaning. In doing so, we open a new gateway of predicting the solution to a problem in the fastest possible way based on statistical analysis of the datasets rather than researching the whole solution space.

Neural network based design of metagratings

Metagratings are flat and thin surfaces that rely on unique, periodically repeating (non-gradient), arbitrary shaped light scattering units for wave manipulation. However, the absence of an empirical relationship between the structural and diffraction properties of the units enforces utilization of brute force numerical optimization techniques to determine the unit shape for a desired application. Here, we present an artificial neural network based methodology to develop a fast-paced numerical relationship between the two. We demonstrate the training and the performance of a numerical function, utilizing simulated diffraction efficiencies of a large set of units, that can instantaneously mimic the optical response of any other arbitrary shaped unit of the same class. We validate the performance of the trained neural network on a previously unseen set of test samples and discuss the statistical significance. We then utilize the virtually instantaneous network operations to inverse design the metagrating unit shapes for a desired diffraction efficiency distribution. The proposed inter-disciplinary combination of advanced information processing techniques with Maxwells equation solvers opens a pathway for the fast-paced prediction of metagrating designs rather than full wave computation.