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2022

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Full-Text Articles in Physics

Atom-Specific Probing Of Electron Dynamics In An Atomic Adsorbate By Time-Resolved X-Ray Spectroscopy, Simon Schreck, Elias Diesen, Martina Dell'angela, Chang Liu, Matthew Weston, Flavio Capotondi, Hirohito Ogasawara, Jerry Larue, Roberto Costantini, Martin Beye, Piter S. Miedema, Joakim Halldin Stenlid, Jörgen Gladh, Boyang Liu, Hsin-Yi Wang, Fivos Perakis, Filippo Cavalca, Sergey Koroidov, Peter Amann, Emanuele Pedersoli, Denys Naumenko, Ivaylo Nikolov, Lorenzo Raimondi, Frank Abild-Pedersen, Tony F. Heinz, Johannes Voss, Alan C. Luntz, Anders Nilsson Dec 2022

Atom-Specific Probing Of Electron Dynamics In An Atomic Adsorbate By Time-Resolved X-Ray Spectroscopy, Simon Schreck, Elias Diesen, Martina Dell'angela, Chang Liu, Matthew Weston, Flavio Capotondi, Hirohito Ogasawara, Jerry Larue, Roberto Costantini, Martin Beye, Piter S. Miedema, Joakim Halldin Stenlid, Jörgen Gladh, Boyang Liu, Hsin-Yi Wang, Fivos Perakis, Filippo Cavalca, Sergey Koroidov, Peter Amann, Emanuele Pedersoli, Denys Naumenko, Ivaylo Nikolov, Lorenzo Raimondi, Frank Abild-Pedersen, Tony F. Heinz, Johannes Voss, Alan C. Luntz, Anders Nilsson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The electronic excitation occurring on adsorbates at ultrafast timescales from optical lasers that initiate surface chemical reactions is still an open question. Here, we report the ultrafast temporal evolution of x-ray absorption spectroscopy (XAS) and x-ray emission spectroscopy (XES) of a simple well-known adsorbate prototype system, namely carbon (C) atoms adsorbed on a nickel [Ni(100)] surface, following intense laser optical pumping at 400 nm. We observe ultrafast (∼100  fs) changes in both XAS and XES showing clear signatures of the formation of a hot electron-hole pair distribution on the adsorbate. This is followed by slower changes on a few picoseconds …


Pyseg: A Python Package For 2d Material Flake Localization, Segmentation, And Thickness Prediction, Diana B. Horangic Dec 2022

Pyseg: A Python Package For 2d Material Flake Localization, Segmentation, And Thickness Prediction, Diana B. Horangic

Student Research Projects

Thin materials are of interest for their extraordinary physical, mechanical, thermal, electrical, and optical properties. Monolayers and bilayers of 2D materials can be manufactured through a variety of exfoliation methods. To determine layer thickness, Raman spectroscopy or other methods like Rayleigh scattering are used. These methods are, however, slow, and they require equipment beyond an optical microscope. A Python package that automates flake identification processes was built, with access solely to RGB data from an optical microscope assumed. My package, pyseg, localizes flakes on a substrate and then makes a rough estimate of their thickness from first principles. It can …


Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew Dec 2022

Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …


Supercontinuum Light Generation Via Non-Linear Effects In Hollow-Core Fiber, Skyler Gulati Dec 2022

Supercontinuum Light Generation Via Non-Linear Effects In Hollow-Core Fiber, Skyler Gulati

Physics Student Works

The field of non-linear optics has gained traction in the last couple decades due to the variable generation of wavelengths which are less deterministic than within traditional optics. Using non-linear mediums, including hollow-core fibers (HCF), generation of wavelengths spanning into the vacuum ultraviolet (VUV) wavelength range is possible. These short wavelengths can be utilized within electron spectroscopy-based methods of material science like angle-resolved photoemission spectroscopy (ARPES). This technique most often uses specific photoemission lines of atoms in discharge lamps, however, with the frequency dispersion capabilities of HCF, broad band creation can allow for variable wavelength selection through filtering specific wavelengths …


A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie Nov 2022

A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …


Optimizing Switching Of Non-Linear Properties With Hyperbolic Metamaterials, James A. Ethridge, John G. Jones, Manuel R. Ferdinandus, Michael J. Havrilla, Michael A. Marciniak Nov 2022

Optimizing Switching Of Non-Linear Properties With Hyperbolic Metamaterials, James A. Ethridge, John G. Jones, Manuel R. Ferdinandus, Michael J. Havrilla, Michael A. Marciniak

Faculty Publications

Hyperbolic metamaterials have been demonstrated to have special potential in their linear response, but the extent of their non-linear response has not been extensively modeled or measured. In this work, novel non-linear behavior of an ITO/SiO2 layered hyperbolic metamaterial is modeled and experimentally confirmed, specifically a change in the sign of the non-linear absorption with intensity. This behavior is tunable and can be achieved with a simple one-dimensional layered design. Fabrication was performed with physical vapor deposition, and measurements were conducted using the Z-scan technique. Potential applications include tunable optical switches, optical limiters, and tunable components of laser sources.


Electro-Optical Sensors For Atmospheric Turbulence Strength Characterization With Embedded Edge Ai Processing Of Scintillation Patterns, Ernst Polnau, Don L. N. Hettiarachchi, Mikhail A. Vorontsov Oct 2022

Electro-Optical Sensors For Atmospheric Turbulence Strength Characterization With Embedded Edge Ai Processing Of Scintillation Patterns, Ernst Polnau, Don L. N. Hettiarachchi, Mikhail A. Vorontsov

Electro-Optics and Photonics Faculty Publications

This study introduces electro-optical (EO) sensors (TurbNet sensors) that utilize a remote laser beacon (either coherent or incoherent) and an optical receiver with CCD camera and embedded edge AI computer (Jetson Xavier Nx) for in situ evaluation of the path-averaged atmospheric turbulence refractive index structure parameter C-n(2) at a high temporal rate. Evaluation of C-n(2) values was performed using deep neural network (DNN)-based real-time processing of short-exposure laser-beacon light intensity scintillation patterns (images) captured by a TurbNet sensor optical receiver. Several pre-trained DNN models were loaded onto the AI computer and used for TurbNet sensor performance evaluation in a set …


Oxygen Vacancies In Lib3O5 Crystals And Their Role In Nonlinear Absorption, Brian C. Holloway, Christopher A. Lenyk, Timothy D. Gustafson, Nancy C. Giles Oct 2022

Oxygen Vacancies In Lib3O5 Crystals And Their Role In Nonlinear Absorption, Brian C. Holloway, Christopher A. Lenyk, Timothy D. Gustafson, Nancy C. Giles

Faculty Publications

LiB3O5 (LBO) crystals are used to generate the second, third, and fourth harmonics of near-infrared solid-state lasers. At high power levels, the material’s performance is adversely affected by nonlinear absorption. We show that as-grown crystals contain oxygen and lithium vacancies. Transient absorption bands are formed when these intrinsic defects serve as traps for “free” electrons and holes created by x rays or by three- and four-photon absorption processes. Trapped electrons introduce a band near 300 nm and trapped holes produce bands in the 500-600 nm region. Electron paramagnetic resonance (EPR) is used to identify and characterize the …


Deep-Turbulence Phase Compensation Using Tiled Arrays, Mark F. Spencer, Terry J. Brennan Sep 2022

Deep-Turbulence Phase Compensation Using Tiled Arrays, Mark F. Spencer, Terry J. Brennan

Faculty Publications

Tiled arrays use modulo-2π phase compensation and coherent beam combination to correct for the effects of deep turbulence. As such, this paper uses wave-optics simulations to compare the closed-loop performance of tiled arrays to a branch-point-tolerant phase reconstructor known as LSPV+7 [Appl. Opt. 53, 3821 (2014) [CrossRef] ]. The wave-optics simulations make use of a point-source beacon and are setup with weak-to-strong scintillation conditions. This setup enables a trade-space exploration in support of a power-in-the-bucket comparison with LSPV+7. In turn, the results show that tiled arrays outperform LSPV+7 when transitioning from weak-to-strong scintillation conditions. These results are both …


Resonant Plasmonic–Biomolecular Chiral Interactions In The Far-Ultraviolet: Enantiomeric Discrimination Of Sub-10 Nm Amino Acid Films, Tiago Ramos Leite, Lin Zschiedrich, Orhan Kizilkaya, Kevin M. Mcpeak Sep 2022

Resonant Plasmonic–Biomolecular Chiral Interactions In The Far-Ultraviolet: Enantiomeric Discrimination Of Sub-10 Nm Amino Acid Films, Tiago Ramos Leite, Lin Zschiedrich, Orhan Kizilkaya, Kevin M. Mcpeak

Faculty Publications

Resonant plasmonic–molecular chiral interactions are a promising route to enhanced biosensing. However, biomolecular optical activity primarily exists in the far-ultraviolet regime, posing significant challenges for spectral overlap with current nano-optical platforms. We demonstrate experimentally and computationally the enhanced chiral sensing of a resonant plasmonic–biomolecular system operating in the far-UV. We develop a full-wave model of biomolecular films on Al gammadion arrays using experimentally derived chirality parameters. Our calculations show that detectable enhancements in the chiroptical signals from small amounts of biomolecules are possible only when tight spectral overlap exists between the plasmonic and biomolecular chiral responses. We support this conclusion …


Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri Aug 2022

Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri

Publications and Research

Integrated planar lenses are critical components for analog optical information processing that enable a wide range of applications including beam steering. Conventional planar lenses require gradient index control which makes their on-chip realization challenging. Here, we introduce a new approach for beam steering by designing an array of coupled waveguides with segmented tails that allow for simultaneously achieving planar lensing and off-chip radiation. The proposed arrayed waveguide lens is built on engineering the evanescent coupling between adjacent channels to realize a photonic lattice with an equi-distant ladder of propagation constants that emulates the continuous parabolic index profile. Through coupled-mode analysis …


Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras Aug 2022

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …


Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu Aug 2022

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …


Modelling Spherical Aberration Detection In An Analog Holographic Wavefront Sensor, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy Jul 2022

Modelling Spherical Aberration Detection In An Analog Holographic Wavefront Sensor, Emma Branigan, Suzanne Martin, Matthew Sheehan, Kevin Murphy

Conference Papers

The analog holographic wavefront sensor (AHWFS) is a simple and robust solution to wavefront sensing in turbulent environments. Here, the ability of a photopolymer based AHWFS to detect refractively generated spherical aberration is modelled and verified.


Noncontact Liquid Crystalline Broadband Optoacoustic Sensors, Hengky Chandrahalim, Michael T. Dela Cruz Jun 2022

Noncontact Liquid Crystalline Broadband Optoacoustic Sensors, Hengky Chandrahalim, Michael T. Dela Cruz

AFIT Patents

An optoacoustic sensor includes a liquid crystal (LC) cell formed between top and bottom plates of transparent material. A transverse grating formed across the LC cell that forms an optical transmission bandgap. A CL is aligned to form a spring-like, tunable Bragg grating that is naturally responsive to external agitations providing a spectral transition regime, or edge, in the optical transmission bandgap of the transverse grating that respond to broadband acoustic waves. The optoacoustic sensor includes a narrowband light source that is oriented to transmit light through the top plate, the LC cell, and the bottom plate. The optoacoustic sensor …


Improving On Atmospheric Turbulence Profiles Derived From Dual Beacon Hartmann Turbulence Sensor Measurements, Alexander S. Boeckenstedt, Jack E. Mccrae, Santasri Bose-Pillai, Benjamin Wilson Jun 2022

Improving On Atmospheric Turbulence Profiles Derived From Dual Beacon Hartmann Turbulence Sensor Measurements, Alexander S. Boeckenstedt, Jack E. Mccrae, Santasri Bose-Pillai, Benjamin Wilson

Faculty Publications

Atmospheric turbulence is an inevitable source of wavefront distortion in all fields of long range laser propagation and sensing. However, the distorting effects of turbulence can be corrected using wavefront sensors contained in adaptive optics systems. Such systems also provide deeper insight into surface layer turbulence, which is not well understood. A unique method of profile generation by a dual source Hartmann Turbulence Sensor (HTS) technique is introduced here. Measurements of optical turbulence along a horizontal path were taken to create C2n profiles. Two helium-neon laser beams were directed over an inhomogeneous horizontal path and captured by the HTS. The …


Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay Jun 2022

Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …


Monolithically Integrated Microscale Pressure Sensor On An Optical Fiber Tip, Jeremiah C. Williams, Hengky Chandrahalim May 2022

Monolithically Integrated Microscale Pressure Sensor On An Optical Fiber Tip, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) pressure sensor includes an optical fiber and a three-dimensional microscopic optical enclosure. The three-dimensional microscopic optical enclosure includes tubular side walls having lateral pleated corrugations and attached to a cleaved tip of the optical fiber to receive a light signal. An optically reflecting end wall is distally engaged to the tubular side walls to enclose a trapped quantity of gas that longitudinally positions the optically reflecting end wall in relation to ambient air pressure, changing a distance traveled by a light signal reflected back through the optical fiber.


Hinged Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim May 2022

Hinged Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) sensor includes a three-dimensional microscopic optical structure formed on a cleaved tip of the optical fighter using a two-photon polymerization process on a photosensitive polymer by a three-dimensional micromachining device. The three-dimensional microscopic optical structure having a hinged optical layer pivotally connected to a distal portion of a suspended structure. A reflective layer is deposited on a mirror surface of the hinged optical layer while in an open position. The hinged optical layer is subsequently positioned in the closed position to align the mirror surface to at least partially reflect a light signal back …


3d Flow Field Measurements Outside Nanopores, Jeffrey Mc Hugh, Alice L. Thorneywork, Kurt Andresen, Ulrich F. Keyser Apr 2022

3d Flow Field Measurements Outside Nanopores, Jeffrey Mc Hugh, Alice L. Thorneywork, Kurt Andresen, Ulrich F. Keyser

Physics and Astronomy Faculty Publications

We demonstrate a non-stereoscopic, video-based particle tracking system with optical tweezers to study fluid flow in 3D in the vicinity of glass nanopores. In particular, we used the quadrant interpolation algorithm to extend our video-based particle tracking to displacements out of the trapping plane of the tweezers. This permitted the study of flow from nanopores oriented at an angle to the trapping plane, enabling the mounting of nanopores on a micromanipulator with which it was then possible to automate the mapping procedure. Mapping of the voltage driven flow in 3D volumes outside nanopores revealed polarity dependent flow fields. This is …


Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha Apr 2022

Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …


Limits Of Detection Of Mycotoxins By Laminar Flow Strips: A Review, Xinyi Zhao, Hugh Byrne, Christine M. O’Connor, James Curtin, Furong Tian Apr 2022

Limits Of Detection Of Mycotoxins By Laminar Flow Strips: A Review, Xinyi Zhao, Hugh Byrne, Christine M. O’Connor, James Curtin, Furong Tian

Articles

Mycotoxins are secondary metabolic products of fungi. They are poisonous, carcinogenic, and mutagenic in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even death. Rapid, simple and low-cost methods of detection of mycotoxins are of immense importance and in great demand in the food and beverage industry, as well as in agriculture and environmental monitoring, and, for this purpose, lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety and environmental monitoring. The literature to date describing the development of ICSTs for the detection of different types of mycotoxins using …


Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu Apr 2022

Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …


Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim Mar 2022

Method Of Making Hinged Self-Referencing Fabry–Pérot Cavity Sensors, Jeremiah C. Williams, Hengky Chandrahalim

AFIT Patents

A method is provided for fabricating a passive optical sensor on a tip of an optical fiber. The method includes perpendicularly cleaving a tip of an optical fiber and mounting the tip of the optical fiber in a specimen holder of a photosensitive polymer three-dimensional micromachining machine. The method includes forming a three-dimensional microscopic optical structure within the photosensitive polymer that comprises a two cavity Fabry-Perot Interferometer (FPI) having a hinged optical layer that is pivotally coupled to a suspended structure. The method includes removing an uncured portion of the photosensitive polymer using a solvent. The method includes depositing a …


Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison Mar 2022

Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison

Engineering Faculty Articles and Research

Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …


Utilization And Efficient Computation Of Polarization Factor Q For Fast, Accurate Brdf Modeling, Samuel D. Butler, Michael A. Marciniak Feb 2022

Utilization And Efficient Computation Of Polarization Factor Q For Fast, Accurate Brdf Modeling, Samuel D. Butler, Michael A. Marciniak

Faculty Publications

The Bidirectional Reflectance Distribution Function (BRDF) is of substantial use in remote sensing, scene generation, and computer graphics, to describe optical scatter off realistic surfaces. This paper begins by summarizing our prior work in relating wave optics and geometric optics models, culminating with the Modified Cook-Torrance (MCT) model. The MCT model is evaluated here against aluminum, Infragold, and silver paint at various wavelengths in the IR. In each case, the MCT model is shown to outperform a standard microfacet model. Then, this paper shows a non-trivial method of computing the primary new term, the polarization factor Q. This optimization …


Resolving The Three-Dimensional Rotational And Translational Dynamics Of Single Molecules Using Radially And Azimuthally Polarized Fluorescence, Oumeng Zhang, Weiyan Zhou, Jin Lu, Tingting Wu, Matthew D. Lew Jan 2022

Resolving The Three-Dimensional Rotational And Translational Dynamics Of Single Molecules Using Radially And Azimuthally Polarized Fluorescence, Oumeng Zhang, Weiyan Zhou, Jin Lu, Tingting Wu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We report a radially and azimuthally polarized (raPol) microscope for high detection and estimation performance in single-molecule orientation-localization microscopy (SMOLM). With 5000 photons detected from Nile red (NR) transiently bound within supported lipid bilayers (SLBs), raPol SMOLM achieves 2.9 nm localization precision, 1.5° orientation precision, and 0.17 sr precision in estimating rotational wobble. Within DPPC SLBs, SMOLM imaging reveals the existence of randomly oriented binding pockets that prevent NR from freely exploring all orientations. Treating the SLBs with cholesterol-loaded methyl-β-cyclodextrin (MβCD-chol) causes NR’s orientational diffusion to be dramatically reduced, but curiously NR’s median lateral displacements drastically increase from 20.8 to …


Electromagnetic Multi–Gaussian Speckle, Milo W. Hyde Iv, Olga Korotkova Jan 2022

Electromagnetic Multi–Gaussian Speckle, Milo W. Hyde Iv, Olga Korotkova

Faculty Publications

Generalizing our prior work on scalar multi-Gaussian (MG) distributed optical fields, we introduce the two-dimensional instantaneous electric-field vector whose components are jointly MG distributed. We then derive the single-point Stokes parameter probability density functions (PDFs) of MG-distributed light having an arbitrary degree and state of polarization. We show, in particular, that the intensity contrast of such a field can be tuned to values smaller or larger than unity. We validate our analysis by generating an example partially polarized MG field with a specified single-point polarization matrix using two different Monte Carlo simulation methods. We then compute the joint PDFs of …


A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran Jan 2022

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …


Enhanced Study Of Complex Systems By Unveiling Hidden Symmetries With Dynamical Visibility, Nhat Vu Minh Nguyen Jan 2022

Enhanced Study Of Complex Systems By Unveiling Hidden Symmetries With Dynamical Visibility, Nhat Vu Minh Nguyen

2022 Symposium

One of the great challenges in complex and chaotic dynamics is to reveal its deterministic structures. These temporal dynamical structures are sometimes a consequence of hidden symmetries. Detecting and understanding them can allow the study of complex systems even without knowing the full underlying mathematical description of the system. Here we introduce a new technique, called Dynamical Visibility, that quantifies temporal correlations of the dynamics based upon some symmetry conditions. This visibility measures the departure of the dynamics from internal symmetries. We apply this technique to well-known chaotic systems, such as the logistic map and the circle map, as well …