Physics Commons^™

Application Of Graphical Models In Protein-Protein Interactions And Dynamics, Amir Vajdi Hoojghan

Graduate Doctoral Dissertations

Every organism contains a few hundred to thousands of proteins. A protein is made of a sequence of molecular building blocks named amino acids. Amino acids will be referred to as residues. Every protein performs one or more functions in the cell. In order for a protein to do its job, it requires to bind properly to other partner proteins. Many genetic diseases such as cancer are caused by mutations (changes) of specific residues which cause disturbances in the functions of those proteins.

The problem of prediction of protein binding site is a crucial topic in computational biology. A protein …

Fast Objective Coupled Planar Illumination Microscopy, Cody Jonathan Greer

Arts & Sciences Electronic Theses and Dissertations

Among optical imaging techniques light sheet fluorescence microscopy stands out as one of the most attractive for capturing high-speed biological dynamics unfolding in three dimensions. The technique is potentially millions of times faster than point-scanning techniques such as two-photon microscopy. This potential is especially poignant for neuroscience applications due to the fact that interactions between neurons transpire over mere milliseconds within tissue volumes spanning hundreds of cubic microns. However current-generation light sheet microscopes are limited by volume scanning rate and/or camera frame rate. We begin by reviewing the optical principles underlying light sheet fluorescence microscopy and the origin of these …

Three-Dimensional Bedrock Channel Evolution With Smoothed Particle Hydrodynamics, Nick Richmond

Electronic Theses and Dissertations

Bedrock channels are responsible for balancing and communicating tectonic and climatic signals across landscapes, but it is difficult and dangerous to observe and measure the flows responsible for removing weakly-attached blocks of bedrock from the channel boundary. Consequently, quantitative descriptions of the dynamics of bedrock removal are scarce. Detailed numerical simulation of violent flows in three dimensions has been historically challenging due to technological limitations, but advances in computational fluid dynamics aided by high-performance computing have made it practical to generate approximate solutions to the governing equations of fluid dynamics. From these numerical solutions we gain detailed knowledge of the …

Computational Modeling Of Radiation Interactions With Molecular Nitrogen, Tyler Reese

Dissertations

The ability to detect radiation through identifying secondary effects it has on its surrounding medium would extend the range at which detections could be made and would be a valuable asset to many industries. The development of such a detection instrument requires an accurate prediction of these secondary effects. This research aims to improve on existing modeling techniques and help provide a method for predicting results for an affected medium in the presence of radioactive materials. A review of radioactivity and the interactions mechanisms for emitted particles as well as a brief history of the Monte Carlo Method and its …

Genetic Algorithm Design Of Photonic Crystals For Energy-Efficient Ultrafast Laser Transmitters, Troy A. Hutchins-Delgado

Shared Knowledge Conference

Photonic crystals allow light to be controlled and manipulated such that novel photonic devices can be created. We are interested in using photonic crystals to increase the energy efficiency of our semiconductor whistle-geometry ring lasers. A photonic crystal will enable us to reduce the ring size, while maintaining confinement, thereby reducing its operating power. Photonic crystals can also exhibit slow light that will increase the interaction with the material. This will increase the gain, and therefore, lower the threshold for lasing to occur. Designing a photonic crystal for a particular application can be a challenge due to its number of …

Sampling Complexity Of Bosonic Random Walkers On A One-Dimensional Lattice, Gopikrishnan Muraleedharan, Akimasa Miyake, Ivan Deutsch

Shared Knowledge Conference

Computers based quantum logic are believed to solve problems faster and more efficiently than computers based on classical boolean logic. However, a large-scale universal quantum computer with error correction may not be realized in near future. But we can ask the question: can we devise a specific problem that a quantum device can solve faster than current state of the art super computers? One such problem is the so called "Boson Sampling" problem introduced by Aaronson and Arkhipov. The problem is to generate random numbers according to same distribution as the output number configurations of photons in linear optics. It …

Parallel Algorithms For Time Dependent Density Functional Theory In Real-Space And Real-Time, James Kestyn

Doctoral Dissertations

Density functional theory (DFT) and time dependent density functional theory (TDDFT) have had great success solving for ground state and excited states properties of molecules, solids and nanostructures. However, these problems are particularly hard to scale. Both the size of the discrete system and the number of needed eigenstates increase with the number of electrons. A complete parallel framework for DFT and TDDFT calculations applied to molecules and nanostructures is presented in this dissertation. This includes the development of custom numerical algorithms for eigenvalue problems and linear systems. New functionality in the FEAST eigenvalue solver presents an additional level of …

Bipartite Quantum Interactions: Entangling And Information Processing Abilities, Siddhartha Das

LSU Doctoral Dissertations

The aim of this thesis is to advance the theory behind quantum information processing tasks, by deriving fundamental limits on bipartite quantum interactions and dynamics. A bipartite quantum interaction corresponds to an underlying Hamiltonian that governs the physical transformation of a two-body open quantum system. Under such an interaction, the physical transformation of a bipartite quantum system is considered in the presence of a bath, which may be inaccessible to an observer. The goal is to determine entangling abilities of such arbitrary bipartite quantum interactions. Doing so provides fundamental limitations on information processing tasks, including entanglement distillation and secret key …

Techniques For Improved Space Object Detection Performance From Ground-Based Telescope Systems Using Long And Short Exposure Images, David J. Becker

Theses and Dissertations

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the space situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator on long exposure data to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This research focuses on improving current space object detection algorithms and developing new algorithms …

Automating Mobile Device File Format Analysis, Richard A. Dill

Theses and Dissertations

Forensic tools assist examiners in extracting evidence from application files from mobile devices. If the file format for the file of interest is known, this process is straightforward, otherwise it requires the examiner to manually reverse engineer the data structures resident in the file. This research presents the Automated Data Structure Slayer (ADSS), which automates the process to reverse engineer unknown file for- mats of Android applications. After statically parsing and preparing an application, ADSS dynamically runs it, injecting hooks at selected methods to uncover the data structures used to store and process data before writing to media. The resultant …

Modeling Recombination In Solar Cells, Paul Chery

Macalester Journal of Physics and Astronomy

Solar cells are a competitive alternative to nonrenewable energy sources such as fossil fuels. However, the efficiency of these devices is limited by photogenerated carrier recombination. We use a finite difference numerical model to study recombination phenomena in the absorber layer of solar cells including alternate recombination models and the effects of spatial distribution of recombination centers. We compare the effect of using the constant lifetime approximation for recombination to the full Shockley-Read-Hall expression in Silicon solar cells and find that the constant lifetime approximation holds for high defect densities but not for high photon flux densities. Finally, we simulate …

Development Of A Slab-Based Monte Carlo Proton Dose Algorithm With A Robust Material-Dependent Nuclear Halo Model, John Wesley Chapman Jr

LSU Doctoral Dissertations

Pencil beam algorithms (PBAs) are often utilized for dose calculation in proton therapy treatment planning because they are fast and accurate under most conditions. However, as discussed in Chapman et al (2017), the accuracy of a PBA can be limited under certain conditions because of two major assumptions: (1) the central-axis semi-infinite slab approximation; and, (2) the lack of material dependence in the nuclear halo model. To address these limitations, we transported individual protons using a class II condensed history Monte Carlo and added a novel energy loss method that scaled the nuclear halo equation in water to arbitrary geometry. …

Efficient Phase Retrieval For Off-Axis Point Spread Functions, Salome Esteban Carrasco

Theses and Dissertations

A novel pairing of phase retrieval tools allows for efficient estimation of pupil phase in optical systems from images of point spread functions (PSFs). The phase retrieval algorithm uses correlation of modeled phase in the focal plane to decouple aberrations that are difficult to identify in complex PSFs. The use of a phase kernel that departs from the Fresnel approximation for off-axis PSFs is a more accurate representation of wavefront phase in finite conjugate imaging. The combination of the approximation and phase correlation algorithm can be more efficient and accurate than generic algorithms.

Augustana Invitational Robotics Challenge 2018, Forrest Stonedahl

Celebration of Learning

We will be hosting the 3rd Annual Augustana Invitational Robotics Challenge. This event will involve student teams from Augustana and potentially several other schools in the region bringing forth the robots that they have designed, built, and programmed, to compete against one another. This year's challenge task involves the careful relocation of soda pop cans.

Cuoricino Thermal Pulse Classification By Machine Learning Algorithms, Joshua Mann

Physics

Many of the various properties of neutrinos are still a mystery. One unknown is whether neutrinos are Majorana fermions or Dirac fermions. Cuoricino and CUORE are experiments that aim to solve this mystery. Noise reduction in these experiments hinges on the ability to discern among alpha, beta and gamma particle detections using the thermal pulses they create. In this paper, we look at Cuoricino data and attempt to classify pulses, not as alpha, beta or gamma particles, but rather as signal, noise or calibration data. We will use this preliminary testing ground to examine various machine learning algorithms' abilities in …

An Analysis Of Frenkel Defects And Backgrounds Modeling For Supercdms Dark Matter Searches, Matthew Stein

Physics Theses and Dissertations

Years of astrophysical observations suggest that dark matter comprises more than ~80 % of all matter in the universe. Particle physics theories favor a weakly-interacting particle that could be directly detected in terrestrial experiments. The Super Cryogenic Dark Matter Search (SuperCDMS) Collaboration operates world-leading experiments to directly detect dark matter interacting with ordinary matter. The SuperCDMS Soudan experiment searched for weakly interacting massive particles (WIMPs) via their elastic-scattering interactions with nuclei in low-temperature germanium detectors.

During the operation of the SuperCDMS Soudan experiment, ²¹⁰Pb sources were installed to study background rejection of the Ge detectors. Data from these sources …

Physical Applications Of The Geometric Minimum Action Method, George L. Poppe Jr.

Dissertations, Theses, and Capstone Projects

This thesis extends the landscape of rare events problems solved on stochastic systems by means of the \textit{geometric minimum action method} (gMAM). These include partial differential equations (PDEs) such as the real Ginzburg-Landau equation (RGLE), the linear Schroedinger equation, along with various forms of the nonlinear Schroedinger equation (NLSE) including an application towards an ultra-short pulse mode-locked laser system (MLL).

Additionally we develop analytical tools that can be used alongside numerics to validate those solutions. This includes the use of instanton methods in deriving state transitions for the linear Schroedinger equation and the cubic diffusive NLSE.

These analytical solutions are …

Identifying Influentials In Directed Networks, Guillermo Gutierrez

Student Symposium

Research into the identification of influential nodes specifically with regards to weighted, directed networks has been lacking throughout the lifetime of Network Theory as a whole. This research project seeks to propel the field forward through by devising an algorithm aimed at identifying influential nodes through the use of probability propagation models of information transfer through various real-world networks. The networks discussed are a developed test-network using the Price Model of citation network growth, the neuronal connectivity network of the flatworm C. elegans, and Congressional co-sponsorship networks of the USA’s 110th House and Senate. Rankings of influence of each node, …

Entropic Bounds On Two-Way Assisted Secret-Key Agreement Capacities Of Quantum Channels, Noah Anthony Davis

LSU Doctoral Dissertations

In order to efficiently put quantum technologies into action, we must know the characteristics of the underlying quantum systems and effects. An interesting example is the use of the secret-key-agreement capacity of a quantum channel as a guide and measure for the implementation of quantum key distribution (QKD) and distributed quantum computation. We define the communication task of establishing a secret key over a quantum channel subject to an energy constraint on the input state and while allowing for unlimited local operations and classical communication (LOCC) between a sender and receiver. We then use the energy-constrained squashed entanglement to bound …

Volume 10, Taylor Hogg, Tiffany Carter, Brandyn Johnson, Haleigh James, Josh Baker, Tyler Cernak, Kirsten Bauer, Allie Snavely, Mary Zell Galen, Eric Powell, Thomas Wise, Katie Kinsey, Beth Barbolla, Maeleigh Ferlet, Rebecca Morra, Michala Day, Alexandra Evangelista, Max Flores, Harley Hodges, Clardene Jones, Harrison Samaniego, Jamesha Watson, Abby Gargiulo, Heather Green, Haley Klepatzki, Juan Guevara, Dani Bondurant, Michael Joseph Link Jr., Pamela Dahl, Maeve Losen, Charlotte Murphey

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Roger A. Byrne

An Analysis of Media Framing in Cases of Violence Against Women by Taylor Hogg

Writing in the Discipline of Nursing by Tiffany Carter

Photography by Brandyn Johnson

The Hidden Life of Beef Cattle: A Study of Cattle Welfare on Traditional Ranches and Industrial Farms by Haleigh James

Bloodworth's by Josh Baker and Tyler Cernak

Prosimians: Little Bodies, Big Significance by Kirsten Bauer

Skinformed by Allie Snavely

Coopertition and Gracious Professionalism: The Effects of First Robotics Folklore and Culture on the Stem Community by Mary Zell Galen

Tilt by Eric Powell And Thomas Wise

The Millennial …

How Do Topological Properties Of Ripple-Carry Adders Affect Time Delay?, Alexander Boukal

All Zyzzogeton Presentations

This poster presents topological properties of N-bit ripple-carry adders and the effects of their topology, specifically their genus, on the speed of current flow. An adder is a very simple computer that takes input numbers (0 and 1) from logic gates and then adds them together. To create a ripple-carry adder, we take N number of adder circuits and arrange them in parallel. We differentiate between two kinds of adder circuits: half adders and full adders. Half adders are non-planar (has loops) circuits with genus = 1 that let us perform elementary addition operations using logic gates. Full adder circuits …

Can Mass Be Negative?, Vladik Kreinovich, Sergei Soloviev

Departmental Technical Reports (CS)

Overcoming the force of gravity is an important part of space travel and a significant obstacle preventing many seemingly reasonable space travel schemes to become practical. Science fiction writers like to imagine materials that may help to make space travel easier. Negative mass -- supposedly causing anti-gravity -- is one of the popular ideas in this regard. But can mass be negative? In this paper, we show that negative masses are not possible -- their existence would enable us to create energy out of nothing, which contradicts to the energy conservation law.

Cluster-Based Network Proximities For Arbitrary Nodal Subsets, Kenneth S. Berenhaut, Peter S. Barr, Alyssa M. Kogel, Ryan L. Melvin

Faculty & Staff Scholarship

The concept of a cluster or community in a network context has been of considerable interest in a variety of settings in recent years. In this paper, employing random walks and geodesic distance, we introduce a unified measure of cluster-based proximity between nodes, relative to a given subset of interest. The inherent simplicity and informativeness of the approach could make it of value to researchers in a variety of scientific fields. Applicability is demonstrated via application to clustering for a number of existent data sets (including multipartite networks). We view community detection (i.e. when the full set of network nodes …

A Study Of Neural Networks For The Quantum Many-Body Problem, Liam B. Schramm

Senior Projects Spring 2018

One of the fundamental problems in analytically approaching the quantum many-body problem is that the amount of information needed to describe a quantum state. As the number of particles in a system grows, the amount of information needed for a full description of the system increases exponentially. A great deal of work then has gone into finding efficient approximate representations of these systems. Among the most popular techniques are Tensor Networks and Quantum Monte Carlo methods. However, one new method with a number of promising theoretical guarantees is the Neural Quantum State. This method is an adaptation of the Restricted …

Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi

Wayne State University Dissertations

Despite the attention that Raman Spectroscopy has gained recently in the area of pathogen identification, the spectra analyses techniques are not well developed. In most scenarios, they rely on expert intervention to detect and assign the peaks of the spectra to specific molecular vibration. Although some investigators have used machine-learning techniques to classify pathogens, these studies are usually limited to a specific application, and the generalization of these techniques is not clear. Also, a wide range of algorithms have been developed for classification problems, however, there is less insight to applying such methods on Raman spectra. Furthermore, analyzing the Raman …