arXiv subjects

Anand Kumar

Publications and source records attributed to Anand Kumar.

26 records · Page 2Linked to original sources

arXiv2023

The ideal wavelength for daylight free-space quantum key distribution

Quantum key distribution (QKD) has matured in recent years from laboratory proof-of-principle demonstrations to commercially available systems. One of the major bottlenecks is the limited communication distance in fiber networks due to the exponential signal damping. To bridge intercontinental distances, low Earth orbit satellites transmitting the quantum signals over the atmosphere can be used. These free-space links, however, can only operate during the night, as the sunlight otherwise saturates the detectors used to measure the quantum states. For applying QKD in a global quantum internet with continuous availability and high data rates, operation during daylight is required. In this work, we model a satellite-to-ground quantum channel for different quantum light sources to identify the optimal wavelength for free-space QKD in ambient conditions. Daylight quantum communication is possible within the Fraunhofer lines or in the near-infrared spectrum, where the intrinsic background from the sun is comparably low. The highest annual secret key length considering the finite key effect is achievable at the H\textalpha\ Fraunhofer line. More importantly, we provide the full model that can be adapted in general to any other specific link scenario. We also propose a true single-photon source based on a color center in hexagonal boron nitride coupled to a microresonator that can implement such a scheme. Our results can also be applied in roof-to-roof scenarios and are therefore relevant for near-future quantum networks.

quant-ph↗

arXiv2023

Localized creation of yellow single photon emitting carbon complexes in hexagonal boron nitride

Single photon emitters in solid-state crystals have received a lot of attention as building blocks for numerous quantum technology applications. Fluorescent defects in hexagonal boron nitride (hBN) stand out due to their high luminosity and robust operation at room temperature. The identical emitter fabrication at pre-defined sites is still challenging, which hampers the integration of these defects in optical systems and electro-optical devices. Here, we demonstrate the localized fabrication of hBN emitter arrays by electron beam irradiation using a standard scanning electron microscope with deep sub-micron lateral precision. The emitters are created with a high yield and a reproducible spectrum peaking at 575 nm. Our measurements of optically detected magnetic resonance have not revealed any addressable spin states. Using density functional theory, we attribute the experimentally observed emission lines to carbon-related defects, which are activated by the electron beam. Our scalable approach provides a promising pathway for fabricating room temperature single photon emitters in integrated quantum devices.

quant-ph↗

arXiv2022

A Compact Quasi-Yagi Antenna for FMCW Radar-on-Chip based Through-Wall Imaging

A compact quasi-Yagi antenna with a modified ground plane is designed for a through-wall radar (TWR) on-chip. A slot-based ground plane modification in the proposed antenna results in significant miniaturization with an increase in the impedance bandwidth by 44.62%. The antenna has a high directivity of 9.02 dBi and a front-to-back ratio of 25.76 dB at 2.4 GHz. Based on experiments in real-world deployment scenarios, the performance of the proposed quasi-Yagi antenna is found to be comparable to that of a Vivaldi antenna and a commercial-off-the-shelf (COTS) horn antenna. Spectrogram-based signatures of a moving person behind a wooden partition and a 40 cm thick masonry wall are successfully obtained using the designed antenna, demonstrating the suitability of the quasi-Yagi antenna for portable applications using a radar-on-chip.

eess.SY↗

arXiv2022

Single-shot multispectral quantitative phase imaging using deep neural network

Multi-spectral quantitative phase imaging (MS-QPI) is a cutting-edge label-free technique to determine the morphological changes, refractive index variations and spectroscopic information of the specimens. The bottleneck to implement this technique to extract quantitative information, is the need of more than two measurements for generating MS-QPI images. We propose a single-shot MS-QPI technique using highly spatially sensitive digital holographic microscope assisted with deep neural network (DNN). Our method first acquires the interferometric datasets corresponding to multiple wavelengths (λ=532, 633 and 808 nm used here). The acquired datasets are used to train generative adversarial network (GAN) to generate multi-spectral quantitative phase maps from a single input interferogram. The network is trained and validated on two different samples, the optical waveguide and a MG63 osteosarcoma cells. Further, validation of the framework is performed by comparing the predicted phase maps with experimentally acquired and processed multi-spectral phase maps. The current MS-QPI+DNN framework can further empower spectroscopic QPI to improve the chemical specificity without complex instrumentation and color-cross talk.

physics.optics↗

arXiv2021

High-resolution single-shot phase-shifting interference microscopy using deep neural network for quantitative phase imaging of biological samples

White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts are essentially required in WL-PSIM for measuring the accurate phase of the object. Here, we present single-shot phase-shifting interferometric techniques for accurate phase measurement using filtered white light phase-shifting interference microscopy (F-WL-PSIM) and deep neural network (DNN). The methods are incorporated by training the DNN to generate 1) four phase-shifted frames and 2) direct phase from a single interferogram. The training of network is performed on two different samples i.e., optical waveguide and MG63 osteosarcoma cells. Further, performance of F-WL-PSIM+DNN framework is validated by comparing the phase map extracted from network generated and experimentally recorded interferograms. The current approach can further strengthen QPI techniques for high-resolution phase recovery using a single frame for different biomedical applications.

eess.IV↗

arXiv2020

High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network

Quantitative phase microscopy (QPM) is a label-free technique that enables to monitor morphological changes at subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth QPM using partially spatially coherent optical coherence microscopy (PSC-OCM) assisted with deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from PSC-OCM system. The training of the network is performed on two different types of samples i.e. mostly homogenous human red blood cells (RBC) and on highly heterogenous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with low NA lens and compared with the actual HR phase images. An improvement of 9 times in space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-OCM+GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source.

physics.bio-ph↗

arXiv2018

Characterization of color cross-talk of CCD detectors and its influence in multispectral quantitative phase imaging

Multi-spectral quantitative phase imaging (QPI) is an emerging imaging modality for wavelength dependent studies of several biological and industrial specimens. Simultaneous multi-spectral QPI is generally performed with color CCD cameras. However, color CCD cameras are suffered from the color crosstalk issue, which needed to be explored. Here, we present a new approach for accurately measuring the color crosstalk of 2D area detectors, without needing prior information about camera specifications. Color crosstalk of two different cameras commonly used in QPI, single chip CCD (1-CCD) and three chip CCD (3-CCD), is systematically studied and compared using compact interference microscopy. The influence of color crosstalk on the fringe width and the visibility of the monochromatic constituents corresponding to three color channels of white light interferogram are studied both through simulations and experiments. It is observed that presence of color crosstalk changes the fringe width and visibility over the imaging field of view. This leads to an unwanted non-uniform background error in the multi-spectral phase imaging of the specimens. It is demonstrated that the color crosstalk of the detector is the key limiting factor for phase measurement accuracy of simultaneous multi-spectral QPI systems.

physics.ins-det↗

arXiv2010

Scope of cloud computing for SMEs in India

Cloud computing is a set of services that provide infrastructure resources using internet media and data storage on a third party server. SMEs are said to be the lifeblood of any vibrant economy. They are known to be the silent drivers of a nation's economy. SMEs of India are one of the most aggressive adopters of ERP Packages. Most of the Indian SMEs have adopted the traditional ERP Systems and have incurred a heavy cost while implementing these systems. This paper presents the cost savings and reduction in the level of difficulty in adopting a cloud computing Service (CCS) enabled ERP system. For the study, IT people from 30 North Indian SMEs were interviewed. In the cloud computing environment the SMEs will not have to own the infrastructure so they can abstain from any capital expenditure and instead they can utilize the resources as a service and pay as per their usage. We consider the results of the paper to be supportive to our proposed research concept.

cs.CY↗