Physics Commons^™

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Faster, Cheaper, And Better Cfd: A Case For Machine Learning To Augment Reynolds-Averaged Navier-Stokes, John Peter Romano Ii

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, the field of machine learning (ML) has made significant advances, particularly through applying deep learning (DL) algorithms and artificial intelligence (AI). The literature shows several ways that ML may enhance the power of computational fluid dynamics (CFD) to improve its solution accuracy, reduce the needed computational resources and reduce overall simulation cost. ML techniques have also expanded the understanding of underlying flow physics and improved data capture from experimental fluid dynamics.

This dissertation presents an in-depth literature review and discusses ways the field of fluid dynamics has leveraged ML modeling to date. The author selects and describes …

Deep Virtual Pion Pair Production, Dilini Lakshani Bulumulla

Physics Theses & Dissertations

This experiment investigates the deep virtual production of both σ− and ρ− mesons, with a particular focus on the microscopic structure of the σ mesons. While the ρ meson is an ordinary qq¯ pair, the σ meson is composed of not only the typical qq¯ pair, making it a topic of controversy for nearly six decades. Although the existence of the σ− meson is now well established, its microscopic structure remains poorly understood. The primary objective of this thesis is to contribute to the understanding of the σ meson by analyzing its deep virtual production. The main focus of this …

Study Of Microphonic Effects On The C100 Cryomodule For High Energy Electron Beam Accelerators, Caleb James Hull

Mechanical & Aerospace Engineering Theses & Dissertations

The Continuous Electron Beam Accelerator Facility (CEBAF) at Thomas Jefferson National Laboratory (JLab) is a particle accelerator which can accelerate an electron beam to relativistic speeds and apply the beam onto target samples. The C100 superconducting radio frequency (SRF) cavity is the primary accelerating structure of the C100 cryomodule, one of the many cryomodules which compose the CEBAF linear accelerator. SRF cavities are particularly sensitive to internal and external vibrations that can result in a phenomenon called microphonics which degrade the operational stability of a cryomodule.

The purpose of this thesis is to investigate the significance of mechanical disturbances on …

Inverse Mappers For Qcd Global Analysis, Manal Almaeen

Computer Science Theses & Dissertations

Inverse problems – using measured observations to determine unknown parameters – are well motivated but challenging in many scientific problems. Mapping parameters to observables is a well-posed problem with unique solutions, and therefore can be solved with differential equations or linear algebra solvers. However, the inverse problem requires backward mapping from observable to parameter space, which is often nonunique. Consequently, solving inverse problems is ill-posed and a far more challenging computational problem.

Our motivated application in this dissertation is the inverse problems in nuclear physics that characterize the internal structure of the hadrons. We first present a machine learning framework …

Experimental And Computational Aerodynamic Studies Of Axially-Oriented Low-Fineness-Ratio Cylinders, Forrest Miller

Mechanical & Aerospace Engineering Theses & Dissertations

For the successful completion of atmospheric entry, descent, and landing (EDL) missions, a body geometry must be selected which provides favorable dynamic aerodynamic properties. The types of experimental facilities capable of collecting information on these properties are limited; however, their numbers are growing thanks to the continued work by the aerodynamics community. NASA Langley Research Center (LaRC) is conducting dynamic aerodynamic testing using a subsonic magnetic suspension and balance system (MSBS), with the end goal of implementing a supersonic MSBS facility at NASA Glenn Research Center. MSBSs are also currently used at the Institute of Fluid Science (IFS) at Tohoku …

A Statistical Framework For Automating Resonance Detection: Modelling Pion Proton Collision Activity, Shahnaz Abdul Hameed

2023 REYES Proceedings

In this paper, we analyze π− − p elastic collision data from the Particle Data Group (PDG), by creating a general framework to study resonance activity: automating peak detection, extrapolating, parametrizing thresholds, filtering resonances and further comparing and extracting characteristics, to identify Delta (Δ) baryons. We then analyse experimental Energy vs Phase-Shift (δ) data for the collision π+ +π− → π− +π+, model the T matrix from a curve fitted polynomial representation of the K⁻¹ matrix, simulate its Riemann sheets and analyse it to identify the characteristics of ρ⁰(770) meson, as well as estimate their uncertainties. …

Nb3Sn Coating Of Twin Axis Cavity And Other Complex Srf Cavity Structures, Jayendrika Kumari Tiskumara

Physics Theses & Dissertations

In the field of Accelerator Science, for the low cost and increased quality factor, thin films coated niobium cavities are used in the modern SRF research. Within the potential substances, Nb₃Sn has shown higher critical temperature than niobium. Here the tin vapor diffusion method is used as the preferred technique to coat niobium cavities. So far, only elliptical cavities have been coated with Nb₃Sn and this technique has not yet been applied to cavities with complex geometries, which are also helpful in the accelerator science field. The Half-wave resonator could provide us data across frequencies of …

Measurements Of Magnetic Field Penetration Of Materials For Superconducting Radiofrequency Cavities, Iresha Harshani Senevirathne

Physics Theses & Dissertations

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized …

Spectra Of Atmospheric And Astronomical Molecules, W. D. Cameron

Physics Theses & Dissertations

Spectroscopy techniques are focused on spectra of molecules of interest to the Earth’s atmosphere and/or astronomy and astrophysics. Laboratory spectroscopy as well as remote satellite sensing are applied. Using the Fourier transform spectrometer aboard the Atmospheric Chemistry Experiment (ACE) satellite to measure the absorption spectra of the Earth’s atmosphere through solar occultation limb observation demonstrates that volcanic eruption plumes can be located and tracked through their SO₂ content. The presence of those plumes is corroborated by overlaying infrared atmospheric aerosol extinction observed by the 1 μm imager on the same satellite. Tracking atmospheric aerosol movement with the ACE …

Design And Construction Of A Longitudinally Polarized Solid Nuclear Target For Clas12, Victoria Lagerquist

Physics Theses & Dissertations

A new polarized nuclear target has been developed, constructed, and deployed at Jefferson Laboratory in Newport News, VA for use with the upgraded 12 GeV CEBAF (Continuous Electron Beam Accelerator Facility) accelerator and the Hall B CLAS12 (12 GeV CEBAF Large Acceptance Spectrometer) detector array. This ‘APOLLO’ (Ammonia POLarized LOngitudinally) target is a longitudinally polarized, solid ammonia, nuclear target which employs DNP (Dynamic Nuclear Polarization) to induce a net polarization in samples of protons (NH3) and deuterons (ND3) cooled to 1K via helium evaporation, held in a 5T polarizing field supplied by the CLAS12 spectrometer, and irradiated with 140 GHz …

Exploring The Dependence Of Bulges In Spiral Galaxies On Their Environment, William Jackson Clark

Physics Theses & Dissertations

Recent research has shown a relationship between spiral galaxy satellite populations and the size of spiral bulges. The modern cosmological model of our universe (ΛCDM), does not predict this. Instead, ΛCMD predicts that only the total dynamical mass of a host galaxy should be correlated with satellite populations. We investigate this relationship in regimes other than satellites. In this study we compare the bulge to total mass ratios of spiral galaxies to the number of nearby galaxies within “n” Mpc. We use four papers from literature that calculate bulge to total mass ratios of 189 spiral galaxies using …

R-Process Nucleosynthesis: Identifying The Significant Nuclear Properties, Sabina Gaia Tomasicchio

2023 REYES Proceedings

We provide a theoretical overview of r-process nucleosynthesis. We then identify the nuclear properties that have the greatest astrophysical impact according to recent sensitivity studies as: nuclear masses, β decays and neutron capture rates. Finally, we briefly discuss how the NuCRL model can enhance the performance of the relevant simulations.

Architecture Of Heptagonal Metallo-Macrocycles Via Embedding Metal Nodes Into Its Rigid Backbone, A.M.Shashika D. Wijerathna, He Zhao, Qiangqiang Dong, Qixia Bai, Zhiyuan Jiang, Jie Yuan, Jun Wang, Mingzhao Chen, Markus Zirnheld, Rockwell T. Li, Yuan Zhang, Yiming Li, Pingshan Wang

College of Sciences Posters

Metal-organic macrocycles have received increasing attention not only due to their versatile applications such as molecular recognition, compounds encapsulation, anti-bacteria and others, but also for their important role in the study of structure-property relationship at nano scale. However, most of the constructions utilize benzene ring as the backbone, which restricts the ligand arm angle in the range of 60, 120 and 180 degrees. Thus, the topologies of most metallo-macrocycles are limited as triangles and hexagons, and explorations of using other backbones with large angles and the construction of metallo-macrocycles with more than six edges are very rare.

In this study, …

Evaluation Of Scalable Quantum And Classical Machine Learning For Particle Tracking Classification In Nuclear Physics, Polykarpos Thomadakis, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Future particle accelerators will exceed by far the current data size (10¹⁵) per experiment, and high- luminosity program(s) will produce more than 300 times as much data. Classical Machine Learning (ML) likely will benefit from new tools based on quantum computing. Particle track reconstruction is the most computationally intensive process in nuclear physics experiments. A combinatorial approach exhaustively tests track measurements (“hits”), represented as images, to identify those that form an actual particle trajectory, which is then used to reconstruct track parameters necessary for the physics experiment. Quantum Machine Learning (QML) could improve this process in multiple ways, …

Quantum Computing For Nuclear Physics, Aikaterini Nikou

2023 REYES Proceedings

Nuclear physics can greatly advance by taking advantage of quantum computing. Quantum computing can play a pivotal role in advancing nuclear physics and can allow for the description of physical situations and problems that are prohibitive to solve using classical computing due to their complexity. Some of the problems whose complexity requires using quantum computing to describe are: interacting quantum many-body and Quantum Field Theory problems such as simulating strongly interacting fields such as Quantum Chromodynamics with physical time evolution, the determination of the shape/phase of a nucleus using the time evolution of an appropriated observable as well as identifying …

Spontaneous Symmetry Breaking And Goldstone Theorem, Emilia Szymańska

2023 REYES Proceedings

We discuss the concept of spontaneous symmetry breaking and illustrate it with a general example. We consider Wigner-Weyl and Nambu-Goldstone realisations of symmetry in the quantum theory. Next, we state Goldstone’s theorem and sketch its proof. We discuss why quantum chromodynamics is not realised in the Wigner-Weyl mode. We also consider different order parameters of spontaneous chiral symmetry breaking.

Ml-Based Surrogates And Emulators, Tareq Alghamdi, Yaohang Li, Nobuo Sato

College of Sciences Posters

No abstract provided.

Quantum Computing And Its Applications In Healthcare, Vu Giang

OUR Journal: ODU Undergraduate Research Journal

This paper serves as a review of the state of quantum computing and its application in healthcare. The various avenues for how quantum computing can be applied to healthcare is discussed here along with the conversation about the limitations of the technology. With more and more efforts put into the development of these computers, its future is promising with the endeavors of furthering healthcare and various other industries.

Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

This paper expands the authors’ prior work[1], which focuses on developing a convolutional neural network (CNN) model capable of mapping time-averaged, unsteady Reynold’s-averaged Navier-Stokes (URANS) simulations to higher resolution results informed by time-averaged detached eddy simulations (DES). The authors present improvements over the prior CNN autoencoder model that result from hyperparameter optimization, increased data set augmentation through the adoption of a patch-wise training approach, and the predictions of primitive variables rather than vorticity magnitude. The training of the CNN model developed in this study uses the same URANS and DES simulations of a transonic flow around several NACA 4-digit airfoils …

Toward A Generative Modeling Analysis Of Clas Exclusive 2𝜋 Photoproduction, T. Alghamdi, Y. Alanazi, M. Battaglieri, Ł. Bibrzycki, A. V. Golda, A. N. Hiller Blin, E. L. Isupov, Y. Li, L. Marsicano, W. Melnitchouk, V. I. Mokeev, G. Montaña, A. Pilloni, N. Sato, A. P. Szczepaniak, T. Vittorini

Computer Science Faculty Publications

AI-supported algorithms, particularly generative models, have been successfully used in a variety of different contexts. This work employs a generative modeling approach to unfold detector effects specifically tailored for exclusive reactions that involve multiparticle final states. Our study demonstrates the preservation of correlations between kinematic variables in a multidimensional phase space. We perform a full closure test on two-pion photoproduction pseudodata generated with a realistic model in the kinematics of the Jefferson Lab CLAS g11 experiment. The overlap of different reaction mechanisms leading to the same final state associated with the CLAS detector’s nontrivial effects represents an ideal test case …

Charged Track Reconstruction With Artificial Intelligence For Clas12, Gagik Gavalian, Polykarpos Thomadakis, Angelos Angelopoulos, Nikos Chrisochoides

Computer Science Faculty Publications

In this paper, we present the results of charged particle track reconstruction in CLAS12 using artificial intelligence. In our approach, we use neural networks working together to identify tracks based on the raw signals in the Drift Chambers. A Convolutional Auto-Encoder is used to de-noise raw data by removing the hits that do not satisfy the patterns for tracks, and second Multi-Layer Perceptron is used to identify tracks from combinations of clusters in the drift chambers. Our method increases the tracking efficiency by 50% for multi-particle final states already conducted experiments. The de-noising results indicate that future experiments can run …

Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …

Non-Singlet Quark Helicity Pdfs Of The Nucleon From Pseudo-Distributions, Robert Edwards, Colin Egerer, Joseph Karpie, Nikhil Karthik, Christopher Monahan, Wayne Morris, Kostas Orginos, Anatoly Radyushkin, David Richards, Eloy Romero, Raza Sabbir Sufian, Savvas Zafeiropoulos, On Behalf Of The Hadstruc Collaboration

Physics Faculty Publications

The non-singlet helicity quark parton distribution functions (PDFs) of the nucleon are determined from lattice QCD, by jointly leveraging pseudo-distributions and the distillation spatial smearing paradigm. A Lorentz decomposition of appropriately isolated space-like matrix elements reveals pseudo-distributions that contain information on the leading-twist helicity PDFs, as well as an invariant amplitude that induces an additional z² contamination of the leading-twist signal. An analysis of the short-distance behavior of the space-like matrix elements using matching coefficients computed to next-to-leading order (NLO) exposes the desired PDF up to this additional z² contamination. Due to the non-conservation of the axial current, …

Status And Future Plans For C³ R&D, Emilio A. Nanni, Martin Breidenbach, Zenghai Li, Caterina Vernieri, Faya Wang, Glen White, Mei Bai, Sergey Belomestnykh, Pushpalatha Bhat, Tim Barklow, William J. Berg, Valery Borzenets, John Byrd, Ankur Dhar, Ram C. Dhuley, Chris Doss, Joseph Duris, Auralee Edelen, Claudio Emma, Joseph Frisch, Annika Gabriel, Spenser Gessner, Carsten Hast, Chunguang Jing, Arkadiy Klebaner, Dongsung Kim, Anatoly Krasnykh, John Lewellen, Matthias Liepe, Michael Litos, Xueying Lu, Jared Maxon, David Montanari, Pietro Musumeci, Sergei Nagaitsev, Alireza Nassiri, Cho-Kuen Ng, David A. K. Othman, Marco Oriunno, Dennis Palmer, J. Ritchie Patterson, Michael E. Peskin, Thomas J. Peterson, John Power, Ji Qiang, James Rosenzweig, Vladimir Shiltsev, Muhammad Shumail, Evgenya Simakov, Emma Snively, Bruno Spataro, Sami Tantawi, Harry Van Der Graaf, Brandon Weatherford, Juhao Wu, Kent P. Wootton

Physics Faculty Publications

C³ is an opportunity to realize an e⁺e^- collider for the study of the Higgs boson at √s = 250 GeV, with a well defined upgrade path to 550 GeV while staying on the same short facility footprint [2,3]. C³ is based on a fundamentally new approach to normal conducting linear accelerators that achieves both high gradient and high efficiency at relatively low cost. Given the advanced state of linear collider designs, the key system that requires technical maturation for C³ is the main linac. This paper presents the staged approach towards a …

On The Chronological Understanding Of The Homogeneous Dielectric Barrier Discharge, Xinpei Lu, Zhi Fang, Dong Dai, Tao Shao, Feng Liu, Cheng Zhang, Dawei Liu, Lanlan Nie, Chunqi Jiang

Bioelectrics Publications

Dielectric barrier discharges (DBD) are widely utilised non-equilibrium atmospheric pressure plasmas with a diverse range of applications, such as material processing, surface treatment, light sources, pollution control, and medicine. Over the course of several decades, extensive research has been dedicated to the generation of homogeneous DBD (H-DBD), focussing on understanding the transition from H-DBD to filamentary DBD and exploring strategies to create and sustain H-DBD. This paper first discusses the influence of various parameters on DBD, including gas flow, dielectric material, surface conductivity, and mesh electrode. Secondly, a chronological literature review is presented, highlighting the development of H-DBD and the …

More On The Demons Of Thermodynamics, Daniel P. Sheehan, Garret Moddel, James W. Lee

Chemistry & Biochemistry Faculty Publications

No abstract provided.

Nudyclr: Nuclear Dynamic Co-Learned Representations, Víctor Samuel Pérez-Díaz

2023 REYES Proceedings

NuCLR (Nuclear Co-Learned Representations) is a cutting-edge multi-task deep learning framework designed to predict essential nuclear observables, including binding energies, decay energies, and nuclear charge radii. As part of the REYES Mentorship Program, we investigated the application of dynamic loss weighting to further refine NuCLR’s predictive performance. Our findings indicate that while weighting strategies can enhance accuracy in specific tasks, such as binding energy prediction, they may underperform in others. Equal Weighting (EW), the original method employed by NuCLR, demonstrated consistent performance across multiple tasks, affirming its robustness. This report succinctly presents the developments and results of the mentorship program …

Resonance Signatures In 𝜋+𝜋− Scattering: Theoretical Analysis And Interpretation, Mayul Verma

2023 REYES Proceedings

Hadron colour confinement, a phenomenon central to Quantum Chromodynamics (QCD), presents a formidable challenge in theoretical physics. The non-perturbative nature of confinement necessitates innovative approaches to the production of and reaction mechanisms between these subatomic particles. In the pursuit of comprehending the fundamental constituents of matter, particle resonances assume a pivotal role. Through the utilization of advanced methodologies like 𝑆-Matrix formulations, more profound insights into resonance phenomena and their effects on the dynamics of particle interactions can be attained. This research paper embarks on a mathematical journey that holds the potential to shed light on the intricate structure of particle …

Algebraic Tunnelling, Gaurab Sedhain

2023 REYES Proceedings

We study the quantum phenomenon of tunnelling in the framework of algebraic quantum theory, motivated by the tunnelling aspects of false vacuum decay. We see that resolvent C*-algebra, proposed relatively recently by Buchholz and Grundling rather than Weyl algebra provides an appropriate framework for treating the dynamics of non-free quantum mechanical system as an algebraic automorphism. At the end, we propose to investigate false vacuum decay in algebraic quantum field theoretic setting in terms of the two-point correlation function which gives us the tunneling probability, with the corresponding C*-algebraic construction.