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Sarma, Raktim

Publications and source records attributed to Sarma, Raktim.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Terahertz Detection Using Enhanced Two‐Step Absorption in Photoconductive Metasurfaces Gated at λ = 1.55 µm

Abstract Superior ultrafast photoconductive properties make low temperature grown (LT) GaAs one of the best materials for photoconductive terahertz (THz) detection. However, the large bandgap of LT‐GaAs limits its operation to gating at wavelengths shorter than 870 nm. Here, it is demonstrated for the first time that nanostructuring the LT‐GaAs into a highly absorbing metasurface enables THz photoconductive detection with a pulsed laser at λ = 1.55 µm. The very weak sub‐bandgap absorption mediated by midgap states in LT‐GaAs is strongly enhanced using the concept of perfect absorption via degenerate critical coupling. Integrated with a THz antenna, the LT‐GaAs metasurface enables high sensitivity THz detection with a high dynamic range of 60 dB and large bandwidth up to 4.5 THz. The LT‐GaAs metasurface has the potential to serve as a universal ultrafast switching element for THz applications, enabling low‐cost, turn‐key THz systems for a variety of real‐world applications.

Jung, Hyunseung↗
DOE OSTI2022

Control of second-harmonic generation in all-dielectric intersubband metasurfaces by controlling the polarity of χ (2)

All-dielectric metasurfaces have recently led to a paradigm shift in nonlinear optics as they allow for circumventing the phase matching constraints of bulk crystals and offer high nonlinear conversion efficiencies when normalized by the light-matter interaction volume. Unlike bulk crystals, in all-dielectric metasurfaces nonlinear conversion efficiencies primarily rely on the material nonlinearity, field enhancements, and the modal overlaps, therefore most efforts to date have only focused on utilizing these degrees of freedom. In this work, we demonstrate that for second-harmonic generation in all-dielectric metasurfaces, an additional degree of freedom is the control of the polarity of the nonlinear susceptibility. We demonstrate that semiconductor heterostructures that support resonant nonlinearities based on quantum-engineered intersubband transitions provide this new degree of freedom. We can flip and control the polarity of the nonlinear susceptibility of the dielectric medium along the growth direction and couple it to the Mie-type photonic modes. Here we demonstrate that engineering the χ (2) polarity in the meta-atom enables the control of the second-harmonic radiation pattern and conversion efficiency. Our results therefore open a new direction for engineering and optimizing second-harmonic generation using all-dielectric intersubband nonlinear metasurfaces.

42 ENGINEERING↗
DOE OSTI2022

Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Efficient ultrathin all-dielectric nonlinear optical device

An apparatus and method are provided for generating harmonic light from a pump beam that is impinged on a metasurface comprising a plurality of all-dielectric resonator bodies. A multiple quantum well structure formed in each resonator body includes asymmetric coupled quantum wells having intersubband transition frequencies that couple to Mie resonances of the resonator bodies.

Sarma, Raktim↗
DOE OSTI2021

All Optical Neural Networks for Low Power Edge Computing

We developed a simplistic physics-based model of an all-optical neural network that mimics the encoder part of an autoencoder neural network for image compression. Our approach relies on the generation of a MATLAB-based model for both data compression and decompression and utilizes MATLAB's built-in autoencoder networks in combination with simple propagation of optical fields between layers constituting phase elements via Fourier transform. We optimize the phase elements using the particle swarm optimization technique and using our model, we demonstrate a compression ratio of 25% for 2828-pixel input images containing numeric digits from 0 to 9.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Strong Coupling in All-Dielectric Intersubband Polaritonic Metasurfaces

Mie-resonant dielectric metasurfaces are excellent candidates for both fundamental studies related to light–matter interactions and for numerous applications ranging from holography to sensing to nonlinear optics. To date, however, most applications using Mie metasurfaces utilize only weak light-matter interaction. Furthermore, we go beyond the weak coupling regime and demonstrate for the first time strong polaritonic coupling between Mie photonic modes and intersubband (ISB) transitions in semiconductor heterostructures. Furthermore, along with demonstrating ISB polaritons with Rabi splitting as large as 10%, we also demonstrate the ability to tailor the strength of strong coupling by engineering either the semiconductor heterostructure or the photonic mode of the resonators. Unlike previous plasmonic-based works, our new all-dielectric metasurface approach to generate ISB polaritons is free from ohmic losses and has high optical damage thresholds, thereby making it ideal for creating novel and compact mid-infrared light sources based on nonlinear optics.

42 ENGINEERING↗
DOE OSTI2020

Optimization and Prediction of Spectral Response of Metasurfaces Using Artificial Intelligence

Hot-electron generation has been a topic of intense research for decades for numerous applications ranging from photodetection and photochemistry to biosensing. Recently, the technique of hot-electron generation using non-radiative decay of surface plasmons excited by metallic nanoantennas, or meta-atoms, in a metasurface has attracted attention. These metasurfaces can be designed with thicknesses on the order of the hot-electron diffusion length. The plasmonic resonances of these ultrathin metasurfaces can be tailored by changing the shape and size of the meta-atoms. One of the fundamental mechanisms leading to generation of hot-electrons in such systems is optical absorption, therefore, optimization of absorption is a key step in enhancing the performance of any metasurface based hot-electron device. Here we utilized an artificial intelligence-based approach, the genetic algorithm, to optimize absorption spectra of plasmonic metasurfaces. Using genetic algorithm optimization strategies, we designed a polarization insensitive plasmonic metasurface with 90% absorption at 1550 nm that does not require an optically thick ground plane. We fabricated and optically characterized the metasurface and our experimental results agree with simulations. Finally, we present a convolutional neural network that can predict the absorption spectra of metasurfaces never seen by the network, thereby eliminating the need for computationally expensive simulations. Our results suggest a new direction for optimizing hot-electron based photodetectors and sensors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗