Physics Commons^™

Quantifying The Performance Of The Sparta Toolkit For Use In Planetary Regolith Characterization Missions, Abigail S. Glover

Honors Undergraduate Theses

This research investigates the use of the Soil Properties Assessment, Resistance, and Thermal Analysis (SPARTA) Cone Penetration Tester (CPT) to quantify bulk density in lunar regolith simulant LHS-1E. Twenty-five penetration tests were conducted across five density profiles to derive slope parameters (G), which represent the rate of increase in resistance with depth. Results showed a consistent, nonlinear relationship between G and bulk density, validating the use of G slope as a diagnostic parameter and supporting the primary hypothesis that SPARTA CPT measurements vary meaningfully with density. Compared to prior work by Lucas et al. (2024), G values from SPARTA were …

Entangled Photoelectron Attosecond Spectroscopy, Jonathan Sar-Shalom

Honors Undergraduate Theses

In this thesis we propose an interferometric scheme to retrieve the dynamics of an electron wave packet emitted from two distinct residual photo-ion channels in the ionization of an atom by an ultra-short UV pulse. EPAS (Entangled-Photoelectron Attosecond Spectroscopy) works by having a non-overlapping UV and few-cycle IR pulse, where the IR is tuned near the transition frequency between two electronic bound states of the photo-ion. Using a time-dependent simulation based on a two-channel atomic model, supported by a perturbative approach, we were able to compute the resulting interference in the angular distribution of the photoelectron and retrieve the energy-dependent …

Simulating Positive Ion Distribution In The Protodune Single Phase Detector, Vishnu Pfeiffer

Electronic Theses and Dissertations

This work covers the validation and implementation of a model to solve for argon ion (Ar+) distribution in the ProtoDUNE-SP liquid argon time projection chamber (LArTPC). ProtoDUNE-SP undergoes a constant flux of cosmic ray muons due to surface operation. The performance of the ProtoDUNE-SP provided valuable insights into single-phase technology, membrane cryostat technology, and calibration of cryogenic instrumentation. Still, challenges in achieving precise measurements persist due to the space charge effect—the distortion of the electric field within the detector due to the accumulation of positive argon ions generated from constant cosmic muon flux. The overarching goal of this thesis is …

Investigating The Roles Of Intrinsic Point Defects And Transition Metal Doping In Monolayer And Bulk Tis2, Patrick J. Keeney

UNF Graduate Theses and Dissertations

Within this thesis, the magnetic and electronic properties of various 1T-TiS₂ systems are thoroughly examined using density functional theory (DFT) and scanning tunneling microscopy (STM). Formation energies and electronic implications of intrinsic point defects in bulk TiS₂ and monolayer TiS₂ are analyzed by approximating a computational monolayer of TiS₂ as the surface layer of a bulk sample. This approximation is validated given that intralayer covalent bonding dominates interlayer van der Waals interactions. We conclude that the most energetically favorable intrinsic defects are Ti atoms settling above the outermost S plane and S vacancies. In addition, the …

Frustrated Quantum Magnetism: The Interplay Of Isotropic And Anisotropic Interactions With Application To Α-Rucl3, Evan M. Wilson

UNF Graduate Theses and Dissertations

We investigate how anisotropic spin interactions, including Dzyaloshinskii–Moriya and Kitaev terms, manifest across quantum spin systems ranging from a single S = 1/2 dimer to molecular spin clusters and layered magnetic materials. Beginning with an exact analysis of the spin dimer, we demonstrate how singlet–triplet mixing induced by Dzyaloshinskii–Moriya interaction directly influences both thermodynamic observables and inelastic neutron scattering spectra. These microscopic fingerprints are then extended to trimer, tetramer, and tetrahedron geometries, where field-induced phase transitions and heat capacity anomalies reveal the interplay between isotropic Heisenberg and anisotropic Kitaev exchanges. In the frustrated zigzag honeycomb lattice, we show that a …

Niobium Titanium Nitride Thin Film Deposition, Optimization, And Characterization, Hudson Horne

UNF Graduate Theses and Dissertations

Superconducting thin film devices such as Josephson junctions are a staple of cutting-edge quantum and classical computing architectures. Functional devices require optimized materials with properties suited to the device application; properties like superconducting critical temperature, critical current density, resistivity, and surface roughness are important depending on the intended device application. Niobium titanium nitride (NbTiN), a fcc transition metal nitride, is a promising material for these applications, with a superconducting critical temperature among the highest of the superconductors described by Bardeen, Cooper, and Schreiffer (BCS) theory. NbTiN has excellent mechanical and electrical characteristics and is easily deposited via reactive magnetron sputtering …

The Real-Time Detection Infrastructure Of Ligo, Virgo, And Kagra: Data Products, Current Performance, And Future Developments, Sushant Sharma Chaudhary

Doctoral Dissertations

The discovery of the binary neutron star merger event GW170817 marked the dawn of Multi-Messenger Astronomy (MMA) with Gravitational Waves (GWs). Such multi-messenger events are of immense scientific interest due to the wealth of information they provide through joint observations across different messengers. In this rapidly evolving field, prompt identification and timely distribution of alerts is critical for follow-up observations.

This work offers a comprehensive overview of the LIGO-Virgo-KAGRA (LVK) Collaboration’s low-latency analysis pipeline for GW events, covering key stages from calibration and data analysis to the issuance of public alerts. I examine the latency and accuracy of each stage …

Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern

Doctoral

From aerospace to agriculture, sensors play a fundamental role in many aspects of modern life. Sensors form an integral part of the complex systems and devices required for the continued functioning and development of services and industries across society. The use of sensors is paramount in areas affecting human health, one such area being the monitoring of indoor air quality, in particular the detection of volatile organic compounds (VOCs). Human contact with VOCs has been associated with many health complications, including skin and eye irritation, cardiovascular damage, and cancers. Optical, electrical, gravimetric, and chemical sensors have been developed for VOC …

Structural Optimization And Stability Enhancement Of Uba(2) And Ntl9 Using The Computational Tool: Emcast, Bahar Ghazi Esfahani

Graduate Student Theses, Dissertations, & Professional Papers

This study enhances protein stability prediction by refining EmCAST (Empirical C-Alpha Stability Tool), a computational tool used to identify stabilizing mutations in protein domains. We applied EmCAST to two model proteins: the α-helical ubiquitin-associated domain 2 (UBA(2)) and the α/β N-terminal domain of ribosomal protein L9 (NTL9). Protein stability is critical for proper function, and mutations can lead to misfolding and disease. To validate EmCAST’s predictions, guanidine hydrochloride-induced denaturation was monitored using circular dichroism (CD) spectroscopy for both wild-type and mutant variants. Results guided refinements to EmCAST’s algorithm, incorporating new experimental datasets to improve accuracy. Additionally, we examined the assumption …

Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets

Graduate Student Theses, Dissertations, & Professional Papers

Understanding fuel pattern-fire process relationships is key for predicting fire behavior and effects with follow-on benefits to proactive fire management and model validation. To characterize dynamic fire behavior, this thesis leverages empirical data and numerical simulation through two complementary studies.

In the first study, longwave thermal sensors aboard unmanned aerial systems (UAS) were used to capture fine-scale fire behavior in two experimental grass burns. A novel paired design was used to quantify the effects of fuel arrangement on fire behavior with 3.66 m diameter treatments cut to a height of 0.15 m. The treatments ephemerally reduced fire rate of spread …

Local-Neutrosophic Logic And Local-Neutrosophic Sets: Incorporating Locality With Applications, Florentin Smarandache, Takaaki Fujita

Branch Mathematics and Statistics Faculty and Staff Publications

The study of uncertainty has been a significant area of research, with concepts such as fuzzy sets [87], fuzzy graphs [51], and neutrosophic sets [58] receiving extensive attention. In Neutrosophic Logic, indeterminacy often arises from real-world complexities. This paper explores the concept of locality as a key factor in determining indeterminacy, building upon the framework introduced by F. Smarandache in [73]. Locality refers to processes constrained within a specific region, where an object or system is directly influenced by its immediate surroundings. In contrast, nonlocality involves effects that transcend spatial or temporal boundaries, where changes in one location have direct …

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …

Effect Of Reduction Annealing On The Structural And Electrical Properties Of Α-Moo3 Thin Films, Sandipani Ghosh

Graduate Theses/Dissertations

2D layered molybdenum oxide has attracted significant research interest due to its tuneable bandgap and diverse structural, chemical, electrical, and optical properties influenced by growth parameters and synthesis techniques. In this study, the effects of reduction annealing on the structural and electrical properties of few-layer MoO₃ thin films, deposited on Si/SiO₂ substrates via pulsed laser deposition, were investigated. X-ray diffraction revealed nanocrystalline structures with a preferred (020) orientation, reduction annealing produced highly crystalline orthorhombic α-MoO₃ with reduced unit cell volume. FESEM/EDS provided detailed analyses of microstructures and elemental compositions. Raman spectroscopy confirmed the orthorhombic structure, with characteristic peaks at 667, …

Sustainable Water Purification Using Green-Synthesized Nanoparticles: A Comparison Between Mono- And Bimetallic Nanoparticle Systems, Sai Bhargava Vipparla, Naveen Debbata, Satyavardhan Dharmapuri, Anil Kumar Busi, Pranay Bhasker Kalakonda, Dayanand Aitipamula, Moses Kigozi, Pritam Mandal, Krishna Kumar Balu, Parvathalu Kalakonda

Michigan Tech Publications

This review explores recent advancements in using environmentally benign monometallic nanoparticles (MMNPs) and bimetallic nanoparticles (BMNPs) for photocatalytic water purification, addressing the urgent need for sustainable solutions to global water scarcity. This study systematically analyzes how key photocatalysis variables, including nanocatalyst concentration, dye selection, and pollutant concentration, influence dye degradation outcomes. Standardized experimental conditions utilizing UV irradiation, 10 ppm, methylene blue (MB), and green synthesis routes were employed for comparative assessment. Results indicate that BMNPs, particularly Ag-Cu BMNPs composites, consistently outperform their MMNPs, achieving degradation rates between 90% and 99%, compared to 70%–85% for MMNPs. This superior performance is attributed …

Scaling Laws For Diffusion In Crystallized Plasma From Molecular Dynamics, Dany Yaacoub

Theses and Dissertations

Diffusion coefficients for crystallized Coulomb plasmas are essential microphysics input for modeling white dwarf cores and neutron star crusts. Solving for diffusion coefficients require running large molecular dynamics simulations with thousands of particles over millions of timesteps. The diffusion in a crystallized plasma has been largely ignored and is often taken to be zero in stellar evolution codes. We find that not only is this incorrect, but we find that the diffusion in a crystallized plasma can be modeled completely using a universal scaling law independent of screening. Our simulations also show that the dominant mode of diffusion in a …

Issues And Challenges In Silicon Based Quantum Computing, Rafia Ayub

Electronic Theses & Dissertations (2024 - present)

Silicon-based quantum computing has emerged as a promising platform for scalable and fault-tolerant quantum information processing. This thesis investigates the use of silicon quantum dots as qubits, addressing a key limitation in their implementation—charge noise and decoherence. We explore the physical and electronic properties of silicon quantum dots, focusing on their coherence times, tunability, and compatibility with existing semiconductor fabrication technologies. Through theoretical analysis and numerical simulations, we examine the impact of material imperfections and propose strategies to mitigate decoherence effects, thereby enhancing qubit stability. Additionally, we discuss potential pathways for integrating silicon quantum dots into large-scale quantum architectures. Our …

Backgrounds And Efficiencies For Low-Energy Searches, And Improved Calibration Techniques In The Lux-Zeplin Dark Matter Experiment, Gregory M. Blockinger

Electronic Theses & Dissertations (2024 - present)

The full understanding of dark matter has eluded physicists for many years. While there is abundant astrophysical evidence across many scales, the exact nature of this matter, which comprises about 25% of the Universe’s energy density, remains unknown. Weakly Interacting Massive Particles (WIMPs) are one of the leading theoretical candidates, and numerous ex- periments have searched for their interactions. In recent decades, dual-phase Time Projection Chambers (TPCs) have become the leading technology in this search. The LUX-ZEPLIN (LZ) detector is one such xenon-based experiment, operating nearly a mile underground in the Black Hills of South Dakota at the Sanford Underground …

First-Principles Study Of The Heterostructure, Znsb Bilayer/H-Bn Monolayer For Thermoelectric Applications, Zakariae Darhi, Larbi El Farh, Ravindra Pandey

Michigan Tech Publications

ZnSb is widely recognized as a promising thermoelectric material in its bulk form, and a ZnSb bilayer was recently synthesized from the bulk. In this study, we designed a vertical van der Waals heterostructure consisting of a ZnSb bilayer and an h-BN monolayer to investigate its electronic, elastic, transport, and thermoelectric properties. Based on density functional theory, the results show that the formation of this heterostructure significantly enhances electron mobility and reduces the bandgap compared to the ZnSb bilayer, thereby increasing its power factor. These findings highlight the potential of the h-BN monolayer–supported ZnSb bilayer heterostructure in thermoelectric applications, where …

Impact Of Y-Mixer Geometry And Flow Rate Modulation On Chemical Gradient Generators In Microfluidic Devices, Elizabeth Thurston Hutton

College of Graduate Studies: Theses & Dissertations

Various microfluidic structures are devised to generate tunable, stable spatiotemporal chemical gradients for single-cell studies. This work addresses the role of Y-mixer junctions in generating nonlinear gradients by increasing the width of one arm (bias), which is suspected to cause premature diffusion within the mixer. This study introduced a cinching feature to narrow the wider arm locally and redefine the junctions of these biased Y-mixers using four novel geometries defined by a 5-micrometer drawing rule. Furthermore, three flow rate factors allowed us to explore the impact on the generated gradient landscapes. The results showed that the four novel designs similarly …

Vaim-Cff: A Variational Autoencoder Inverse Mapper Solution To Compton Form Factor Extraction From Deeply Virtual Compton Scattering, Manal Almaeen, Tareq Alghamdi, Brandon Kriesten, Douglas Adams, Yaohang Li, Huey-Wen Lin, Simonetta Liuti

Computer Science Faculty Publications

We develop a new methodology for extracting Compton form factors (CFFs) from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse mapper (VAIM). The VAIM-CFF framework not only allows us access to a fitted solution set possibly containing multiple solutions in the extraction of all 8 CFFs from a single cross section measurement, but also accesses the lost information contained in the forward mapping from CFFs to cross section. We investigate various assumptions and their effects on the predicted CFFs such as cross section organization, number of extracted …

Geometric Gnns For Charged Particle Tracking At Gluex, Ahmed Hossam Mohammed, Kishansingh Rajput, Simon Taylor, Denis Furletov, Sergey Furletov, Malachi Schram

Computer Science Faculty Publications

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this …

Decode The Workload: Training Deep Learning Models For Efficient Compute Cluster Representation, Ahmed Hossam Mohammed, Mark Jones, Diana Mcspadden, Malachi Schram, Bryan Hess, Kishansingh Rajput

Computer Science Faculty Publications

In this study, we address the mounting challenge of monitoring high throughput computing clusters running computationally intensive jobs, which increasingly strains system administrators. We develop autoencoders that analyze traces of Linux kernel CPU metrics to capture salient system features by producing robust compressed embeddings for various downstream tasks. In addition, we employ graph neural networks to incorporate contextual information from surrounding CPUs and assess their performance. We also demonstrate the enhanced job differentiation achieved by increasing the sampling rate of these traces. Our models are evaluated based on their ability to generate meaningful latent representations, detect anomalies, and distinguish between …

Ai For Nuclear Physics: The Exclaim Project, S. Liuti, D. Adams, M. Boër, G. W. Chern, M. Cuic, M. Engelhardt, G. R. Goldstein, B. Kriesten, Y. Li, H. W. Lin, M. Sievert, D. Sivers

Computer Science Faculty Publications

An overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics …

An Overview Of Emri Data Analysis, Zou Xiaobo, Soumya Mohanty, Xie Qunying, Chen Xian, Luo Honggang, Liu Yuxiao, Han Wenbiao, Jiao Jiageng, Zhang Xuehao, Zhao Shaodong

Physics & Astronomy Faculty Publications

The Extreme Mass-Ratio Inspiral (EMRI) refers to binary system with a mass ratio between 104 and 107, where the smaller object loses energy as it inspirals closer to a massive black hole, emitting gravitational waves. It is estimated that there are 105 cycles during the last year before plunge, providing rich information on the evolution of gravitational wave phases. The motion of the smaller object in the strong gravitational field of the massive black hole can reflect the surrounding spacetime structure. The massive black hole is typically located at the center of a galaxy, in which the galaxy environment leaves …

The Gaps Programme At Tng: Lxv. Precise Density Measurement Of Toi-1430 B, A Young Planet With An Evaporating Atmosphere, D. Nardiello, J. M. Akana Murphy, R. Spinelli, M. Baratella, S. Desidera, V. Nascimbeni, L. Malavolta, K. Biazzo, A. Maggio, Ryan J. Oelkers

Physics & Astronomy Faculty Publications

Context. Small-sized (< 4 R_⊕) exoplanets in tight orbits around young stars (10–1000 Myr) give us the opportunity to investigate the mechanisms that led to their formation, the evolution of their physical and orbital properties, and, in particular, their atmospheres. Thanks to the all-sky survey carried out by the TESS spacecraft, many of these exoplanets have been discovered, and have subsequently been characterized with dedicated follow-up observations.

Aims. In the context of a collaboration among the Global Architecture of Planetary Systems (GAPS) team, the TESS-Keck Survey (TKS) team, and the California Planet Search (CPS) team, we measured …

Detecting Anomalous Srf Cavity Behavior With Unsupervised Learning, Hal Ferguson, Jiang Li, Adam Carpenter, Chris Tennant, Dillon Thomas, Dennis Turner

Electrical & Computer Engineering Faculty Publications

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. This unsupervised method eliminates the need for expensive labeling by continuously updating models with recent data. Deployed and operational for 3 months before a …

Data-Driven Gradient Optimization For Field Emission Management In A Superconducting Radio-Frequency Linac, S. Goldenberg, K. Ahammed, A. Carpenter, J. Li, R. Suleiman, C. Tennant

Electrical & Computer Engineering Faculty Publications

Field emission can cause significant problems in superconducting radio-frequency linear accelerators (linacs). When cavity gradients are pushed higher, radiation levels within the linacs may rise exponentially, causing degradation of many nearby systems. This research aims to utilize machine learning with uncertainty quantification to predict radiation levels at multiple locations throughout the linacs and ultimately optimize cavity gradients to reduce field emission-induced radiation while maintaining the total linac energy gain necessary for the experimental physics program. The optimized solutions show over 40% reductions for both neutron and gamma radiation from the standard operational settings.

Quantum Efficiency, Electron Spin Polarization And Lifetime Study For Gaas Based Truncated Nanocone Array Photocathodes, Md. Aziz Ar Rahman, Greg Blume, Md Abdullah Mamun, Shukui Zhang, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

[First slide] Direct band-gap photocathode (Eg = 1.42 eV).

Valence band maximum (VBM) is doubly degenerate, Max. electron spin polarization (ESP) ~35-40%.

Strained-supperlattice (SSL) removed the VBM degeneracy, ESP ~85-90% with QE of ~1% at 780 nm.

Requires UHV: Lifetime ~200 C with ~200 μA beam current.

Ion-back bombardment degrades the lifetime.

Improvement in charge lifetime required for JLAB polarized positron source program: 1mA-10mA beam current for 2 weeks ~ 10³10⁴C.

Polarized Photocathode R&D At Bnl And Spin Consideration For The Eic Preinjector, Jyoti Biswas, Erdong Wang, Omer Rahman, John Skaritka, Adam Masters, Sylvain Marsillac, Tai-De Li

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes are vital for producing polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector at the EIC requires a 7 nC bunch with at least 85% spin polarization from a GaAs-based superlattice cathode. The doping density of the very surface layer of the cathode needs to be optimized to extract a high bunch charge beam from the high-voltage DC gun. The polarization axis of the emitted beam is longitudinal, and it will be rotated to transverse direction using two Wien filters, each rotating the spin by 45 degrees. In this paper, we …

Time-Marching Quantum Algorithm For Simulation Of Nonlinear Lorenz Dynamics, Efstratios Koukoutsis, George Vahala, Min Soe, Kyriakos Hizanidis, Linda Vahala, Abhay K. Ram

Electrical & Computer Engineering Faculty Publications

Simulating nonlinear classical dynamics on a quantum computer is an inherently challenging task due to the linear operator formulation of quantum mechanics. In this work, we provide a systematic approach to alleviate this difficulty by developing an explicit quantum algorithm that implements the time evolution of a second-order time-discretized version of the Lorenz model. The Lorenz model is a celebrated system of nonlinear ordinary differential equations that has been extensively studied in the contexts of climate science, fluid dynamics, and chaos theory. Our algorithm possesses a recursive structure and requires only a linear number of copies of the initial state …