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Articles 1 - 7 of 7
Full-Text Articles in Physics
Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel
Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel
Mathematics Theses and Dissertations
Solitons are self-reinforcing localized wave packets that have remarkable stability features that arise from the balanced competition of nonlinear and dispersive effects in the medium. Traditionally, the dominant order of dispersion has been the lowest (second), however in recent years, experimental and theoretical research has shown that high, even order dispersion may lead to novel applications. Here, the focus is on investigating the interplay of dominant quartic (fourth-order) dispersion and the self-phase modulation due to the nonlinear Kerr effect in laser systems. One big factor to consider for experimentalists working in laser systems is the effect of noise on the …
Investigation Of Gas Dynamics In Water And Oil-Based Muds Using Das, Dts, And Dss Measurements, Temitayo S. Adeyemi
Investigation Of Gas Dynamics In Water And Oil-Based Muds Using Das, Dts, And Dss Measurements, Temitayo S. Adeyemi
LSU Master's Theses
Reliable prediction of gas migration velocity, void fraction, and length of gas-affected region in water and oil-based muds is essential for effective planning, control, and optimization of drilling operations. However, there is a gap in our understanding of gas behavior and dynamics in water and oil-based muds. This is a consequence of the use of experimental systems that are not representative of field-scale conditions. This study seeks to bridge the gap via the well-scale deployment of distributed fiber-optic sensors for real-time monitoring of gas behavior and dynamics in water and oil-based mud. The aforementioned parameters were estimated in real-time using …
Spectroscopic End Point Detection With An Electron Beam Evaporator, Ryan Mcgraw
Spectroscopic End Point Detection With An Electron Beam Evaporator, Ryan Mcgraw
University Honors Theses
Spectroscopic end point detection is a common tool used for measuring slope changes in wavelength intensity. Using algorithms able to apply this concept, coatings will be able to be dynamically measured in real time and stopped at the appropriate level to ensure process uniformity. It is currently applied to reductive processes such as etching, where the surface will start to be eaten away, creating a plasma. When the entire amount of a material on a substrate has been eaten away, the plasma will change color as it is beginning to etch a different material. Using a spectrometer, this point where …
Exciton Dynamics, Interaction, And Transport In Monolayers Of Transition Metal Dichalcogenides, Saroj Chand
Exciton Dynamics, Interaction, And Transport In Monolayers Of Transition Metal Dichalcogenides, Saroj Chand
Dissertations, Theses, and Capstone Projects
Monolayers Transition metal dichalcogenides (TMDs) have attracted much attention in recent years due to their promising optical and electronic properties for applications in optoelectronic devices. The rich multivalley band structure and sizable spin-orbit coupling in monolayer TMDs result in several optically bright and dark excitonic states with different spin and valley configurations. In the proposed works, we have developed experimental techniques and theoretical models to study the dynamics, interactions, and transport of both dark and bright excitons.
In W-based monolayers of TMDs, the momentum dark exciton cannot typically recombine optically, but they represent the lowest excitonic state of the system …
Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner
Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner
Dissertations, Master's Theses and Master's Reports
The unifying theme of this thesis is the characterization of “perfect randomness,” i.e., independent and identically distributed (IID) stochastic processes as these are applied in physical science. Two specific and mathematically distinct applications are chosen: (i) Radar and optical polarimetry; (ii) Analysis of time series in meteorology. In (i), IID process of a special kind, namely, with a distribution defined by symmetry, is used to link its multivariate Gaussian density to uniformity on the Poincaré sphere. This “statistical ellipsometry” approach is then used to relate polarimetric mismatches or imbalances to ellipsometric variables and suitably chosen cross-correlation measures. In (ii), recently …
Scattering Of Electromagnetic Radiation By Bianisotropic Spheres, Maxwell A. Wallace
Scattering Of Electromagnetic Radiation By Bianisotropic Spheres, Maxwell A. Wallace
Electronic Theses and Dissertations
Modern developments in materials science have led to the increased demand for the ability to control electromagnetic radiation at scales smaller than ever. One of the most important areas of research for controlling the manipulation of electromagnetic radiation, has been the studying of novel optical metamaterials, including the most general and complex form, bianisotropic metamaterials (BAMs). With modern developments in nano- engineering, paired with the advancement of more robust theoretical studies of BAMs, the demand for more novel BAM technologies has increased. With the advent of research of unbounded BAM media, as well as the recent extensions of Mie theory …
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Theses and Dissertations--Electrical and Computer Engineering
Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …