Faculty Publications
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Item Simulation study of multilayer hybrid plasmonic switch using Franz-Keldysh effect(SPIE spie@spie.org, 2020) Sahu, S.K.; Khoja, R.; Kanu, S.; Kumar, A.; Singh, M.ACMOS compatible three-port all-optical silicon switch working in 1.473 to 1.502 ?m (extinction ratio (ER) = 5.5 dB, ?C = 1.488 ?m) and 1.512 to 1.5306 ?m (ER = 3.079 dB, ?C = 1.52 ?m) bands is demonstrated in this work through numerical simulations. However, in spite of the all optical control, having null refractive index contrast between the transmitting and control waveguides of the switch causes the switching merit to deteriorate because of light leaking from the transmitting waveguide. Later, by employing Franz Keldysh effect-induced absorption coefficient tuning of Si1-x Gex (x = 0.85) to replace the silicon control port of the switch, 2.95-dB leakage reduction in the ON state is achieved, which is assessed in detail. Also, our numerical simulations confirmed the bandwidth of 38 GHz, which suggested a multilayer plasmonic waveguide structure. © 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).Item CloudX-net: A robust encoder-decoder architecture for cloud detection from satellite remote sensing images(Elsevier B.V., 2020) Kanu, S.; Khoja, R.; Lal, S.; Raghavendra, B.S.; Cs, A.Cloud Detection is an important pre-processing step for any application involving remote sensing data. This paper presents a deep learning based CloudX-Net architecture, that can detect cloud cover with improved accuracy in comparison to the benchmark from satellite remote sensing images. The proposed CloudX-Net model reduces the number of parameters needed for accurate predictions and thus make deep learning based cloud detection method very efficient. Atrous Spatial Pyramid Pooling (ASPP) and Separable convolution are used to optimize the network. For experimentation, we have used Landsat 8 images and 38-Cloud dataset and trained the architectures using Soft Jaccard loss function. Comparing several quantifying metrics result from various recent deep learning architectures proves the efficiency and effectiveness of the proposed CloudX-Net model for cloud detection from satellite images. The source code and data are available at https://github.com/shyamfec/CloudXNet. © 2020 Elsevier B.V.Item Theoretical Analysis of On-Chip Vertical Hybrid Plasmonic Nanograting(Springer, 2022) Reddy, S.K.; Sahu, S.K.; Khoja, R.; Kanu, S.; Singh, M.A complementary metal oxide semiconductor (CMOS) compatible photonic-plasmonic waveguide with nanoscale dimensions and better optical confinement has been proposed for the infrared (IR)–band applications. The design is based on the multi-layer hybrid plasmonic waveguide (Si–SiO2–Au) structure. The 3D-finite element method (FEM)–based numerical simulations of single slot hybrid plasmonic waveguide (HPWG) confirms 2.5 dB/cm propagation loss and 15 μm−2 confined intensity. Moreover, its application as dual-slot nanograting is studied with higher propagation length and ultra–low–dispersion near the 1550–nm wavelength. The proposed low-dispersion nanoscale grating design is suitable for future lab–on–chip nanophotonic integrated circuits. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.