There is currently extensive demand for optical media like CDROM, DVD and Blue ray disks for data storage with computer technologies. Here we combine mathematical modelling studies and photonic laser diffraction experiments to study the optimization of data storage in different types of optical media. Using calculus-based studies, we estimated the data storage capacities in these systems and calculated the CD, DVD and blue ray disk arc length and data storage linear densities. These are in good agreement with reported values. Using red, blue and green laser sources at our photonics lab, we conducted laser diffraction studies and estimated the line spacing of CDROM, DVD and Blue ray disks. The advancement from CDs to DVDs yields higher data storage densities. In the high capacity blue rays disks, because the physical structures called pits that store data on the disks become smaller, there are other challenges in realizing these smaller devices, which make it more expensive. The CD/DVD players' lasers operate at the diffraction limit resolution of light and provide maximum data capacity for their geometry. Magnetic media like floppy disks, hard disk and magnetic tapes are also used for computer data storage. We have estimated the maximum data storage capacity from magnetic floppy discs. We used curve fitting methods to analytically represent the magnetic read-back pulse as Lorentzian functions for data modeling. Our studies provide an integrated STEM learning of data storage in optical and magnetic media.

One of the Ultracold Atoms Group’s themes is to study the interaction between trapped ultracold atom mixtures. Certain experiments, such as the study of spin-dependent Feshbach resonance, requires us to select one specific nuclear spin state of the atom from the mixture. This process is achieved by the optical Stern-Gerlach technique, where we use the laser to produce the magnetic field gradient. However, this technique requires us to use the imaging path with relatively poor imaging quality due to, for example, vibrations of the optics. When we normalize these atom images, these vibrations introduce misalignment between images and thus unwanted noises. Hence my project is focused on stabilizing the imaging process by a software implementation of imaging alignment scheme. The code I developed can be seen as the analog to the inner product of two vectors, which characterizes the extent of misalignment between two vectors. This scheme has increased the efficiency of the experimental procedure and at least doubled the signal-to-noise ratio. Its easy implementation provides another route to reduce noises in the data of similar experiments. 

In the ATLAS detector at the Large Hadron Collider (LHC), high energy quarks and gluons can be produced during proton-proton collisions. Individual quarks and gluons cannot be directly observed, however, when they enter the detector, interactions with the detector create a number or secondary particles called hadrons, which are made up of groups of quarks and gluons, that can be directly observed. A tagger is used to measure the secondary particles and classify them as coming from a quark or a gluon. The tagger uses several variables which are derived from detector data and machine learning algorithms. We analysed data from the detector and Monte Carlo simulation and compared them using the derived variables, which involves calculating ratios, Monte Carlo closure and scale factor, between distributions of the simulation and detector data for each variable. The Monte Carlo closure and scale factor between extracted detector samples and extracted Monte Carlo samples is expected to be close to 1, indicating the simulation models the data, with an uncertainty less than 10%. The results of this study give an analysis on how well these variables are able to classify the initial particle, and allow better calibration of the tagger parameters. Better classification allows for more precise measurements of physics processes at the LHC.

Recent developments in Machine Learning have led to a number of different applications across a variety of fields. This rapid progress has been fueled by the increased performance of Graphics Processing Units (GPUs). Similar rapid developments can be seen happening in Quantum Computing Hardware. While still years behind logical computing, certain statistical models indicate that quantum computers will be able to outperform classical computers within years. However, due to the lack of high memory systems, all of the distributions have to be represented in low-dimensional space. Our work focuses on using classical computing to automatically find efficient feature maps that allow users to scale down real-world or established problems into low-dimensional space, which can then be loaded into quantum computers. Additionally, by creating a simple, modular design, we want to allow other researchers to have a simple interface to compare classical and quantum versions of algorithms to investigate if there are any benefits to using quantum computing over classical systems. We expect quantum computers to perform similarly, if not better, than similarly sized classical models, but still be outperformed by larger, more complex classical systems.

In 2024 the Large Hadron Collider will undergo upgrades that will dramatically increase the number of collisions occurring. In order to accommodate the increased bandwidth, the innermost detector as well as the readout hardware and data acquisition software will be upgraded. This readout chip, called the RD53, already has a preliminary model called the RD53a for which a software emulator already exists. The final design of the chip, the RD53b has recently been released and the software emulator for the RD53a needs to be updated in order to reflect the new specifications of the RD53b. Our research is seeking to create a software emulator for the RD53b readout chip. In order to create the software emulator, we are updating the existing software emulator for the RD53a and comparing the emulator's output with that of the physical hardware chip. We are currently working to create robust software tests of the old software emulator by running scans from the data acquisition software using the software emulator. Thus far the analog, digital and threshold scans for the RD53a emulator have been implemented. In this talk we will give an overview of the design of the software emulator, deployment progress and the further development plan. We will show how this software emulator can enable the faster development of new data acquisition software in preparation for the upgrades to the Large Hadron Collider.

In this project, we consider two particle scattering with an arbitrary finite-range potential interaction, contained in a volume by a harmonic trap. The properties of this scattering system are then studied through Effective Field Theory. From this analysis, we attain general relationships among effective range parameters in various dimensions. This project is an extension of confinement induced through periodic boundary conditions studied previously. From this work, calculations can then be made to deduce properties of multi-body condensates. Currently, we already have shown the general relationships between effective range paramaters in toroidal compactified spaces. 

Machine learning (ML) is an important tool in analyzing huge data sets. There are various machine learning models in the realm of physics that do everything from identifying subatomic particles to predicting the energy of particle jets. Our project is focused on creating a benchmark that would be used to test different models and compare them with each other. Our goal is to host a service that would evaluate different metrics for a user-provided model and display the results. We have created a Yadage workflow that analyzes different tag taggers (i.e. ML models that identify top quarks). To evaluate the top taggers, we plotted their ROC (Receiver operating characteristic) curves. We then compared the AUC (Area Under the Curve) for each model. Our current goal is to run our workflows on REANA (Reproducible research data analysis platform) servers. We believe this project is not just restricted to the world of physics and can be extended to benchmark models from other disciplines as well such as health sciences, natual language processing, computer vision, etc. Similar Benchmarks could be created for different types of models which can be compared using a common dataset for a better comparison

We are studying the effects of Nuclear Fermi Beta Decay. Beta decay occurs when a proton in the nucleus of an atom decays to a neutron or a neutron decays to a proton. Protons and neutrons are in the class of particles known as “baryons”, as they each consist of three quarks, one of the most fundamental types of particles in our universe. They are both made of two types of quarks, “up” quarks, and “down” quarks. Neutrons consist of two down quarks and one up quark, while protons consist of one down quark and two up quarks. Beta decay specifically takes place when an up quark in a proton decays to a down quark, turning a proton into a neutron, or a down quark in a neutron decays to an up quark, turning a neutron into a proton. Our project studies the radial wave function overlap of these two particles. Particles have wave functions associated with them that describe the probability of measuring them in any given state. The overlap that we study is between the wave functions of the proton and neutron in the nucleus of the atom, as this overlap describes how Beta decay occurs. Particles have an intrinsic quantity known as isospin, which is very often conserved in particle interactions, but is not an exact symmetry. We analytically calculate how isospin symmetry breaking influences beta decay. Studying beta decay is useful for understanding solar radiation and energy, as the sun’s fusion reaction causes protons to decay into a shower of particles which are detectable from Earth. However, we are more interested in beta decay for its applications to testing the validity of assumptions of the standard model of particle physics.

Just as the Schrodinger equation is the pivotal theoretical tool for analyzing atomic systems, the application of light front dynamics to derive light front wave functions provides a powerful point of leverage for analyzing the structure of hadrons. The governing theory for hadronic systems (systems composed of quarks and gluons) is Quantum Chromodynamics (QCD), and the expression of this theory in light front variables presents a mathematically-convenient format. In this project we construct a light front Hamiltonian for a 2-parton hadronic system and solve the resulting differential equation to derive a basis of light front wave functions (LFWFs) representing the corresponding bound states. We subsequently modify the Hamiltonian to include terms characterizing effects such as momentum transfer, and attempt to solve the resulting system non-perturbatively. The ultimate goal is to apply our LFWFs to analyze structures in problems important to nuclear physics, such as deep inelastic scattering.

From a materials design perspective, phosphates offer nearly limitless possibilities for various applications, chelating agents, synthetic replacements for bone and teeth, phosphors, detergents, and fertilisers. As a consequence of its thermal and chemical properties, Barium Hydrogen Phosphate (BaHPO₄) plays an important role in catalytic chemistry, industrial paint manufacturing, and ink-related charge direction. Because hydrogen and hydrogen bonds significantly affect these properties, studying proton mechanisms such as proton diffusive motions and jumps is critical to developing a comprehensive understanding pf the compound, allowing further determination of potential applications. Here, we utilise incoherent Quasi-Elastic Neutron Scattering (QENS). QENS is a useful technique to determine diffusive motions in the 10^-12 to 10^-9 second time range at length scales from 3Å to 60Å, which apply to hydrogen ion diffusion and hydrogenous species. Protons have a substantial neutron cross section, which subsequently enchances the associated QENS signal, and permits studies for low-proton systems such as BaHPO₄. The QENS investigation was conducted using 7 discrete temperatures ranging from 293 to 572 Kelvin, while subsequent fitting and analysis revealed the diffusion coefficient as a function of temperature. Obtained results for BaHPO₄ were compared to Monetite (CaHPO₄). In addition to QENS, Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) provided support by giving insight to the surface topography of the sample. Structural and topographic results were compared with similar studies of other relevant phosphates.

In recent years, gravitational waves have yielded insights across many fields, from the expansion of the universe and black hole populations to the origin of heavy elements and nuclear physics. The Laser Interferometer Gravitational-Wave Observatories (LIGO) are michelson-type interferometers formed by two, 4-kilometer-long arms with suspended test masses (mirrors) at the ends. The test masses reflect high-power lasers to be combined at the intersection of the two arms and create an interference pattern, which is sensitive to gravitational waves passing through the interferometer. For a stable interference pattern, the test masses must be oriented precisely; the low frequency orienting of the test masses is done using optical levers (OpLevs). They consist of optics that launch light from a diode laser which reflects off the test mass and hit a quadrant photodiode, which measures the tip and twist of the test mass as a function of beam spot displacement. However, this measurement has elevated noise at low frequencies, limiting its accuracy. The reduction of this noise by a factor of 10-100, would allow for a more accurate orienting of the test mass. The source of noise is likely to be found in the fiber optics connected to the launching telescope. To isolate this noise I recreated parts of the LIGO OpLev setup with a level of positional noise well below LIGO's current OpLev noise at 0.1 Hz (below a nanometer per square root hertz). To achieve noise at this level I have designed a low noise pre-amplifier, improved the physical stability of the setup, and analyzed data to identify the noise sources. With this reduced noise setup we plan to search for the source of LIGO's OPLEV low frequency noise. Reduced noise would increase the uptime of the observatories thus increasing the number of gravitational wave detections.

 Solar power provides a renewable energy resource that reduces carbon footprints and lowers global warming. Solar panels use photovoltaics which convert light to electricity. Most commercial solar panels use silicon wafers. Electrons in these semiconducting silicon panels are freed by solar energy and are induced to travel through an electrical circuit, powering electrical devices or sending electricity to the grid. We have analyzed the reported crystal structure of silicon, which crystallizes in the same pattern as diamond and has a face centered cubic structure with lattice constant 5.4307 Å. We employed vector calculus-based methods to calculate the nearest-neighbor bond lengths (2.3516 Å) and bond angles (109.471^o) of crystalline silicon. These calculated bond-lengths and angle values are in good agreement with reported data. We visualized the electronic charge-density of silicon. Using vector-calculus based methods, we derived the equation for the plane of the solar panel and estimated the power that a solar panel can produce. Real time data from solar panel grids are currently available from energy databases. We determined the total energy produced by a solar panel array over the course of a day by finding the area under the power-vs-time real-time data reported in energy databases using integral calculus-based methods. To understand seasonal variations, we compared solar energy production on a hot summer day and during an overcast winter day. Our studies provide a microscopic atomic level understanding of solar energy and provides an integrated study of mathematics with solar physics and engineering.

The MAJORANA experiment and its follow-on, the Large Enriched Germanium Experiment for Neutrinoless Double-Beta Decay (LEGEND), search for the creation of matter in the form of neutrinoless double-beta decay, a process that would demonstrate that neutrinos are their own antiparticle and that lepton number conservation may be violated, allowing a deeper understanding of the matter-antimatter imbalance in the universe. MJ60 is a germanium detector used to investigate the low-energy region of the MAJORANA DEMONSTRATOR data, as well as the waveforms produced from incident betas in comparison with gamma events. The latter of these is important for understanding the background of LEGEND: the detectors are submerged in liquid argon, in which beta decays of argon-39 and argon-42 contribute to the background of the extremely sensitive experiment. MJ60 was originally a prototype for the P-type point-contact detectors used in the MAJORANA DEMONSTRATOR. Our group is using this detector to measure mechanisms of energy loss near the detector surfaces by recording events from the nearly monoenergetic beta emissions of metastable krypton-83 (83Kr) at 18 and ~30 keV. Analysis of the waveforms produced from these events, which has been my primary task, will allow us to investigate whether betas incident on our detectors’ passivated surface exhibit markedly different charge collection than gammas, as has been hypothesized. If this expectation is upheld, we will be able to produce a method to identify these events based upon a calculated parameter from the recorded waveforms. Such a parameter will help inform future detector R&D efforts, and will also contribute to background rejection capabilities in MAJORANA and LEGEND.

The COHERENT experiment is endeavoring to detect Coherent Elastic Neutrino-Nucleus Scattering (CEνNS) in several nuclear targets using the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL). We search for very low energy (on the order of keV) coherent interactions between neutrinos and atomic nuclei using an array of particle detectors made of different scintillating materials. Neutrinos are fundamental particles under the Standard Model of particle physics that historically have not conformed to theoretical expectations. Understanding their interactions with other particles helps us potentially find other unexpected qualities of neutrinos and in that, discover new physics. At the UW component of the COHERENT team, I along with several other physics undergrads, have just finished characterizing over one-hundred NaI(Tl) crystals to contribute to a large array of detectors at ORNL where they will be illuminated by a strong, pulsed flux of neutrinos born from pions and muons generated in the SNS beam target. For each crystal, I used two characteristic radioactive sources (133Ba & 137Cs) to gather data on each crystal for characterization of their use at ORNL. Each crystal was run for 1.67 hours to find the optimal operating voltage (gain) and to explore the energy linearity of radiation detections at different points in each 7kg crystal (this allowed us to identify if the crystals had any cracks that would interfere with detections). In this talk, I intend to present the statistics on the measured crystal characteristics, including gains, energy resolution, scintillation uniformity as we prepare to ship the crystals to ORNL for installation in the array of other detectors capable of detecting the CEνNS phenomenon.

DAMIC-M is a next-generation experiment to search for dark matter with charge coupled devices (CCDs) in the Modane Underground Laboratory in France. The final DAMIC-M experiment will feature a tower of fifty of the most massive CCDs ever built. These devices will implement a newly developed "skipper" readout mechanism, where ionization charge collected by each pixel in the CCD is measured many times over. The ultra-low noise achieved by the skipper CCDs will provide an improvement of several orders of magnitude in the exploration of the dark matter particle hypothesis, in particular of candidates pertaining to the so-called "hidden sector". To decrease interference from environmental radiation, the CCDs must be encased in low radioactivity electroformed copper. Electroformed copper is grown cylindrically, then flattened to create stackable trays that hold the CCDs. Because the DAMIC-M CCD tower will be operated at a temperature of 100 K, cooling might cause the flattened copper to warp about the axis of the cylindrical stock material. By taking various height profile measurements using a laser interferometer and a dial indicator, I quantified the deviations from flatness caused by the cooling of the trays. The results showed some warping around the corners of the tray, likely due to the measurement apparatus, but no significant warping about the axis of the cylindrical stock copper.  The warping at the corners was likely due to the substance used to hold the tray in place while the measurement was being taken.  While this complication was not ideal, it could be removed in analysis, allowing us to see that the results still showed what we were looking for, that the trays were not warping about the axis of the cylindrical stock copper.

This project aims to develop the equipment and techniques to study the effects of linear strain on nanoscale materials. Nanoscale layered van-der Waals materials are first isolated by mechanical exfoliation down to the two-dimensional (2D) limit. These 2D materials offer a diversity of interesting properties like magnetism, superconductivity, and topological phases. Furthermore, these interesting phenomena may be tuned by changing conditions such as interlayer spacing, crystal symmetry, and stacking order. Uniaxial strain presents an enticing method for in-situ tuning of these properties. Recent attempts to apply strain to 2D materials have relied on the use of bendable substrates, which has limited the application of strain at cryogenic temperatures. Consequently, the unique physics of highly strained atomically thin materials has gone unexplored. Our project utilizes a piezoelectric strainer which allows for extreme tensile and compressive cryo-strain and is compatible with both optical and electrical probing techniques. We report the development of techniques and hardware to fabricate and measure 2D strain samples, as well as preliminary strain studies of the 2D layered antiferromagnet chromium triiodide (CrI₃). Theoretical predictions promise drastic changes to Cr_I3’s magnetism, crystal structure, and optical response which we intend to explore with uniaxial strain. Our ongoing and future research aims to bring versatile and reliable strain to the nanoscale regime, which could contribute to the discovery of novel physics in the plethora of 2D materials studied at the University of Washington and around the world.

The generation of light at harmonic frequencies due to the non-linear interaction between a material and an electric field plays a critical role in several new technologies including ultra-short laser pulse shaping, spectroscopy, and quantum information networks. Gallium-Phosphide ring resonators can effectively convert incident light from visible to telecommunications band wavelengths, but nanoscale fabrication differences in the dimensions of ring resonators can significantly change the devices’ optimal resonant wavelengths. Unless these devices can perform optimally at uniform wavelengths, they cannot be implemented as part of any large-scale system. Post-fabrication etching methods could be used to change the width of the resonators and fine-tune their resonant frequencies. Diffusion-limited wet etching has been shown to remove angstroms-thick layers from III-V semiconductors similar to Gallium Phosphide. Hydrogen peroxide and acid solutions are alternately applied to form and remove oxide layers, reducing the width of the resonators by tens of angstroms each etching cycle. The shift in resonances near nominal wavelengths of 775 and 1550 nm after each etching cycle are measured and compared to simulated results.

Debris Disk Stars are stars that are surrounded by dust and diffuse gas. Certain elements in the gas and dust absorb the light from the star and show up as an absorption-line spectrum. Our goal was to find trends in the elemental abundance patterns of similar debris disk stars. We took 30 debris disk stars that are similar in mass and surface temperature and measured their elemental abundances. Using Spectroscopy through IRAF’s s-plot tool we found accurate abundances of certain elements. We found abundances of metals including Iron, Nickel, Sodium, Carbon, and Oxygen. Comparing their Metallicities ([x/Fe]) we can find certain trends between the abundance of the elements and their condensation temperatures. From the 30 stars in the data-set, we chose 3 of the most interesting objects. The first star we chose, HD162826, is the closest in terms of motion and chemical abundances to the Sun. The second star, HD187691, has a small debris disk. The third star, HD122652, has a large debris disk. For HD162826, we found the metallicity of the refractory elements (high condensation temperature, >1200 K) to be spread around the 0 metallicity marker ([x/Fe]=0), for HD187691 we found most of the refractory elements above [x/Fe]=0 with the rest being very close to zero, and for HD122652 we found that the metallicities of most of the refractory elements were negative. The trends we found are small and could be explained by observational uncertainty, therefore further analysis of our data set would be required to make stronger conclusions. By accurately measuring more absorption lines from our dataset, possibly more connections can be made about the properties of Debris Disk Stars.

This research explores two different projects. Firstly, systematic measurements of the resistivity, susceptibility, and quantum oscillations are presented for single-crystal samples of the chemically substituted RAgSb₂ (R=Gd,La). Doping the parent compound LaAgSb₂ with Gd explores the effect of magnetic doping and applying chemical pressure to the crystal. La_1−xGd_xAgSb₂ exhibits charge density ordering around that is suppressed with increase Gd percentages, while Gd_1−xY_xAgSb₂ exhibits anti-ferromagnetic ordering that is suppressed with increasing Y percentages. Resistivity and susceptibility data are used to identify phase transition temperatures and create a temperature vs doping phase diagram for each chemical substitution family. Magnetic quantum oscillation data is presented suggesting changes in the Fermi surface and effective mass with chemical doping. Secondly, the chiral magnetic effect is the generation of electric current induced by an external magnetic field, resulting in a chiral imbalance. This imbalance creates a strong current by pushing oppositely charged particles in opposite directions within the material. The first observation of the chiral magnetic effect was reported through the measurement of magneto-transport in ZrTe₅, specifically a large negative magnetoresistance when magnetic field and current are parallel. In materials with a large field-induced anisotropic resistivity tensor, such as ZrTe₅, an effect called “current jetting” can lead to a strong apparent negative longitudinal magnetoresistance. Finite element analysis models, contrusted with COMSOL Multiphysics software, of the potential distribution inside ZrTe₅ have been created to investigate possible underlying effects of current jetting.

Nitrogen-vacancy centers (NVs) are defects in diamond whose spin and optical properties enable their use as qubits, the basic building blocks of quantum information processing (QIP). Our group is interested in forming NV centers with good optical properties near the surface of a diamond substrate to create a scalable QIP platform. To form these near-surface NV centers, we implant nitrogen ions into a diamond and subsequently anneal. Recent published literature suggests NV centers formed by implantation and annealing protocols have poor optical properties, including optical linewidth and spectral diffusion, while NV centers formed from naturally-grown-in nitrogen have good optical properties. In this project, we examine this discrepancy by studying the optical properties of NVs formed from implanted nitrogen (¹⁵N isotope) versus grown-in nitrogen (¹⁴N isotope). We implant diamonds with ¹⁵N ions, anneal to form NV centers, then identify each NV center’s nitrogen isotope using optically-detected magnetic resonance (ODMR) to establish the NV’s origin (from implanted or naturally occurring nitrogen.) We then measure the optical properties of the NV centers using photoluminescence excitation (PLE). Preliminary results show a statistical correlation between good optical properties and ¹⁴N NV centers. In this project, I aim to analyze PLE data to measure NV optical properties, use ODMR to identify NV isotopes, and correlate these two measurements for the same NV centers. This work will identify the source and study the spectral properties of implanted NV centers in diamond, ultimately assisting in the development of a scalable QIP platform.

SrHPO₄ is of interest as a candidate material for use in proton-exchange membranes, as a startup material for ceramic fuel-cells, and as a catalyst, but until now its proton mobility had not been studied by quasi-elastic neutron scattering (QENS). QENS analysis of a material provides an understanding of its usefulness for these applications. It displays the behavior of proton diffusion processes in a sample, and the stability of such processes at a wide range of temperatures is crucial to the success of a candidate material. A QENS experiment was performed at the National Institute of Standards and Technology (NIST) on SrHPO₄ powder from 20K to 523K using a Disk Chopper Spectrometer (DCS). Data analysis was then conducted to gain insight into the properties of the sample at each of these temperatures. The data was modeled with background, delta, and Lorentzian functions, as parameters of these models constrain the physical behavior of protons in SrHPO₄. These results were compared with a QENS analysis of Monetite (CaHPO₄) to provide further context to our findings.

We probe the crystal structure and the proton conductivity of magnesium hydrogen phosphate trihydrate MgHPO₄·3H₂O, also known as newberyite. Newberyite is used as an ingredient in pigments, plastics, and anticorrosive paints, and as an alkaline phosphate it has potential for use in proton conduction. The structural transition and the proton diffusive motion as a function of temperature from 20K to 383K have been studied using X-ray crystallography, quasi-elastic neutron scattering (QENS) spectroscopy and atomic force microscopy (AFM), collected from the National Institute of Standards and Technology (NIST) and the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory (ORNL). We confirm that newberyite undergoes a crystalline-to-amorphous dehydration phase transition at low temperatures, which is unusual in other phosphate materials. We compare our analysis with previous crystallographic surveys.

As the world's climate situation becomes more dire, the need for a clean, renewable energy source becomes more pronounced. Proton conductor fuel cells (PCFCs) use the chemical energy of hydrogen fuel efficiently and cleanly to produce electricity with zero-emission. A proton conductor electrolyte is the heart of the fuel cell operation. Alkaline phosphates such as SrHPO₄ are an attractive class of compounds for potential electrolyte materials in proton conducting fuel cells; understanding the crystal structure as function of temperature, the way crystal defects affect structure, the proton conductivity, and resultant properties is of great importance to the advancement of both science and industry. To this end, we are interested in making progress in the science of phosphates as potential proton conductors by studying the structure of SrHPO₄ and other aliovalent (Ca, Ba) phosphate materials by neutron powder diffraction (NPD). Studying the phosphate family allows us to characterize the correlation between the aliovalent alkaline-earth oxide local structures and the measured dynamics properties. An advanced comprehension study of the change in structure of SrHPO₄ as a function of temperature will provide clues to the relationship between structure and the dynamics of proton conduction. In an effort to better understand the structural properties of SrHPO₄ as a function of temperature, NPD data was collected in temperatures ranging from 6K to 300K. X-ray Diffraction(XRD) was performed at 150K and 300K. Surface topography was studied via Scanning Electron Microscopy(SEM) and Atomic Force Microscopy (AFM), collected at Oak Ridge National Laboratory (ORNL). The NPD data was analyzed using the Rietveld Method in conjunction with the FullProf software tool, and we will compare the results with those of CaHPO₄ and BaHPO₄ in order to better understand the relationship between the crystal structure and the proton conduction dynamics of these materials.

Euler integration is the simplest, most versatile, and underappreciated method of integrating partial differential equations (PDEs) that only involves repeated addition. Evaluating the evolution of connected dynamical systems is critical to fundamental research as well as to students’ understanding of the physical world and their classwork. The purpose of this research is to design and implement an educational tool that empowers students and faculty to understand the beautiful simplicity of the most applicable method of evaluating PDEs on a computer. Physical law is always written in the form of a PDE. Traditional physics education does not emphasize this technique. This is largely due to the lack of computers over the last six hundred years. But now, we have super computational ability at our fingertips, and it is time that everyone in the field of physics has access to this versatile and simple tool. The first educational tool is complete and has already helped students learn about this technique. Over the next few months this tool and ones like it will be sewn into existing curricula in the physics department. This technique applies to an enormous range of disciplines from fungal growth to fluid dynamics and will be a skill at every student’s disposal.

The number of theoretical models for particle collisions has been steadily increasing, but creating and running a new program for each analysis is time-consuming. Often the individual steps in these analyses are applicable to a wide range of models. We created Recast-workflow, a project that preserves the steps in the analyses for truth-level reinterpretations (theoretically ideal models), as a solution to this issue. Developed as a Python3 package with a command line interface, this program generates runnable yadage workflows, defined by a yaml schema with instructions for running each step of the analysis. There are three main steps in a Recast workflow - generation, selection, and statistics. The generation step or “subworkflow” we implemented used MadGraph with Pythia, which takes a particle collision and uses a given model to generate the parton shower. We used Rivet, a software for validating data produced by Monte Carlo event generators, for the selection step and Contur or pyhf are the final steps we made to be used to find statistical confidence levels. Recast-workflow runs each stage using the yadage workflow engine in a docker encapsulated environment, and the output from each stage is passed to the subsequent one. This project will help researchers gauge the potential of interesting physics results from a region of phase space by running these generated workflows quickly without the computational complexity of a full reinterpretation. In the future, this can be made more accessible through a web interface and powerful through an expanded catalogue of steps.

The magnitude at which a minimal change in initial conditions can affect data results was first observed by Edward Lorenz in 1963. Through his examination of chaos emerged the discovery that many natural systems are governed by chaotic behavior. The main complication of chaos theory is that nonperiodic unstable systems are unpredictable, and therefore many natural systems have yet to be understood because of its complexity. Our research considers the unstable nature of the Lorenz attractor and its influence on a center of gravity. By examining intervals of data and comparing their centers of gravity, we found that as the amount of data points tends to infinity, a center of gravity never converges to a single point. We also examine what appears to be a stark regularity and group of symmetries under an extension M(n+k)=f(Mn) of Lorenz’ original M(n+1)=f(Mn) study of Poincare sections Z.

In 2007, David Vokoun et al. derived a formula for the force of interaction between magnets. The formula is called the Gilbert's Model. According to the Gilbert’s Model, the force between two ferromagnets is given by a constant factor proportional to the saturation magnetization of each magnet multiplied by a function of the separation distance and geometry of the magnets. We show that the assumed constant is better described as a function of hyperbolic tangent of the separation distance due to the effects of magnetic field interactions on the magnetizations of each magnet, and we demonstrate that the inclusion of a simple toy 1D Ising model acting as a perturbation on the background magnetizations better predicts magnetic coupling of cylindrical magnets over small distances.

The search for renewable energy, electricity-generating wind turbines were first introduced by Charles F. Brush in 1888. Wind turbines use the principles of turning the mechanical energy of the wind into useful electrical energy that is able to produce work while also having no direct emissions towards the atmosphere. Using Betz’s law derived from the principles of conservation of mass and momentum of the air stream flowing, we construct and test a model wind turbine maximizing the power generated due to the varying angular velocities, from which testing data are used to iteratively design blade aerodynamics and assignation angle. For the particular model used thus far, the data indicate that with angular velocity lower than or equal to 4.124 rad/s and 13.359 rad/s a maximum efficiency of 22-23% is achieved. The blade designs are flat and angled blades, which are 3D printed and tested its efficiency on the model with pitches of 15°,30° and 45° to accommodate the motor to generate the optimal use of power input, therefore maximum power output. The result shows that 30° pitch is the most optimal angle for both blades design, with the flat blade generating 29000% more power than the angled blade. Blade pitch of 15° is the least efficient, resulting in no power generated with angled blade design, and significantly lower power in flat blade design compared to the other pitch. This discovery is essential to the future development of renewable energy especially in revolutionizing the wind turbine to be more efficient.