Digital Commons Network^™

Data-Driven Methods For Low-Energy Nuclear Theory, Jordan M.R. Fox

CGU Theses & Dissertations

The term data-driven describes computational methods for numerical problem solvingwhich have been developed by the field of data science; these are at the intersection of computer science,mathematics, and statistics. When applied to a domain science like nuclear physics, especially with the goalof deepening scientific insight, data-driven methods form a core pillar of the computational science endeavor.In this dissertation I explore two problems related to theoretical nuclear physics: one in the framework of numerical statistics, and the other in the framework of machine learning. I) Historically our understanding of the structure of the atomic nucleus, the quantum many-body problem, has been …

Non-Perturbative Processes In Standard Model \& New Physics: From Standard Calculations To Machine Learning, Cody Michael Grant

Wayne State University Dissertations

I calculated non-perturbative processes to study the Standard Model and probe areas of new physics. I found that invisible decays of heavy mesons are not dominated by the leading order contribution in the Standard Model. I argue that this affects neutrino mass constraints and avenues for discovering new physics, such as dark photons. In addition to this, I used a novel approach to approximate a semileptonic form factor with an artificial neural network (ANN). Comparing the results from the ANN to common phenomenological parameterizations, and using it to set a lower bound constraint on the CKM matrix element, $V_{cd}$. Finally, …

Methods And Characterization Of Topological And Disordered-Induced Protection Of Coherence In Quantum Systems, Sayandip Dhara

Electronic Theses and Dissertations, 2020-2023

Quantum computers can efficiently simulate natural processes and solve certain types of mathematical problems. Two of the key issues preventing the development of platforms to realize a scalable quantum machine are the decoherence of the qubits due to the interaction with the environment and the existence of a large overhead to correct errors. Although there already exist noisy intermediate-scale quantum machines, we still need to improve much to be able to solve problems faster than the already existing classical computers. In this dissertation, we explore two approaches to tackle both issues. We propose a scheme where, using quasi-Majorana zero modes …

Location And Calibration Of Lightning Pulses From Lofar Radiation Measurements, Nicholas R. Demers

Honors Theses and Capstones

Lightning has the power to shock and awe as an incredible force of nature, yet so many phenomena surrounding lightning are still not well-understood. In fact, the very physics regarding what actually sparks a lightning strike remain poorly defined. In an effort to understand how lightning initiation is achieved, data collected from the Low Frequency Array in the Netherlands were calibrated and interferometry performed to map the flash in 4D space. The calibration process itself is explored, from choosing lightning sources to calibrate, to the various stages of calibration leading to a fully calibrated flash ready for interferometric analysis. Using …

Development Of A Fluxgate Magnetometer Model, Eleonora Olsmats

Honors Theses and Capstones

As a part of the UNH SWFO-L1 mission to monitor space weather and the sun’s behavior, the fluxgate magnetometer is an important component to measure external magnetic fields. The basic principle of a fluxgate magnetometer is to detect changes in the ambient magnetic field by inducing a magnetic field in a ferromagnetic material via a drive winding. Each magnetometer is unique due to the ferromagnetic properties of the core material which can be seen in the hysteresis loop which is a relationship between the magnetic field strength (H) and the induced magnetic field (B). Measuring the hysteresis of a fluxgate …

Classification Of Metal Hydride Superconductors Using Machine Learning, Vichayuth Imchitr

Chulalongkorn University Theses and Dissertations (Chula ETD)

Metal hydrides are currently the main approach in the quest for high-temperature superconductors, as they exhibit a wide range of superconducting critical temperatures (TC). The key ingredient for determining the superconducting critical temperature is the phonon in the material. However, calculating the phonon via the first-principle method requires high computational costs and is time-consuming. To expedite the search for new superconducting hydrides, machine learning has been applied to scan for potential high-TC materials before performing phonon calculations. However, this method has limitations due to the limited number of available training samples, and the selection of input features for the task …

Azimuthal Transverse Single-Spin Asymmetries Of Inclusive Jets And Identified Hadrons Within Jets From Polarized 𝑝⁢𝑝 Collisions At √𝑠 =200  Gev, Star Collaboration

Physics and Astronomy Faculty Publications

The STAR Collaboration reports measurements of the transverse single-spin asymmetries, 𝐴𝑁, for inclusive jets and identified “hadrons within jets” production at midrapidity from transversely polarized 𝑝⁢𝑝 collisions at √𝑠 =200  GeV, based on data recorded in 2012 and 2015. The inclusive jet asymmetry measurements include 𝐴𝑁 for inclusive jets and 𝐴𝑁 for jets containing a charged pion carrying a momentum fraction 𝑧 >0.3 of the jet momentum. The identified hadron within jet asymmetry measurements include the Collins effect for charged pions, kaons, and protons, and the Collins-like effect for charged pions. The measured asymmetries are determined for several distinct kinematic …

Evidence For Nonlinear Gluon Effects In Qcd And Their Mass Number Dependence At Star, Star Collaboration

Physics and Astronomy Faculty Publications

The STAR Collaboration reports measurements of back-to-back azimuthal correlations of di-𝜋0s produced at forward pseudorapidities (2.6 < 𝜂 < 4.0) in 𝑝 +𝑝, 𝑝+Al, and 𝑝+Au collisions at a center-of-mass energy of 200 GeV. We observe a clear suppression of the correlated yields of back-to-back 𝜋0 pairs in 𝑝+Al and 𝑝+Au collisions compared to the 𝑝 +𝑝 data. The observed suppression of back-to-back pairs as a function of transverse momentum suggests nonlinear gluon dynamics arising at high parton densities. The larger suppression found in 𝑝+Au relative to 𝑝+Al collisions exhibits a dependence of the saturation scale 𝑄2/𝑠 on the mass number 𝐴. A linear scaling of the suppression with 𝐴1/3 is observed with a slope of −0.09 ±0.01.

Recent Analytic Development Of The Dynamic Q-Tensor Theory For Nematic Liquid Crystals, Xiang Xu

Mathematics & Statistics Faculty Publications

Liquid crystals are a typical type of soft matter that are intermediate between conventional crystalline solids and isotropic fluids. The nematic phase is the simplest liquid crystal phase, and has been studied the most in the mathematical community. There are various continuum models to describe liquid crystals of nematic type, and Q-tensor theory is one among them. The aim of this paper is to give a brief review of recent PDE results regarding the Q-tensor theory in dynamic configurations.

Nidus Idearum. Scilogs, Viii: Painting By Numbers, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this eighth book of scilogs collected from my nest of ideas, one may find new and old questions and solutions, – in email messages to research colleagues, or replies, and personal notes handwritten on the planes to, and from international conferences, about all kind of topics, centered mostly on Paradoxism and Neutrosophy.

Exchanging ideas with: Robert Neil Boyd, Joseph Brenner, Ahmed Cevik, Victor Christianto, Adrian Curaj, Jean Dezert, Andrei-Lucian Drăgoi, Ervin Goldfain, Young Bae Jun, Yale Landsberg, Radu Munteanu, Paul Piștea, Viorel Roman, Ridvan Sahin, Said Broumi, Selcuk Topal, Eric W. Weisstein, Xiaohing Zhang.

Instanton Counting, Matrix Models, And Characters, Spencer Tamagni

Honors Undergraduate Theses

In this thesis we study symmetries of quantum field theory visible only at the non-perturbative level, which arise from large deformations of the integration contour in the path integral. We exposit the recently-developed theory of qq-characters that organizes such symmetries in the case of N = 2 supersymmetric gauge theories in four dimensions. We sketch the physical origin of such observables from intersecting branes in string theory, and the mathematical origin as certain
equivariant integrals over Nakajima quiver varieties. We explain some of the main applications, including the derivation of Seiberg-Witten geometry for quiver gauge theories and the relations to …

Compact Lens Technologies: Curved Image Sensor And Volumetric Imaging Efficiency, Zhao Ma

Electronic Theses and Dissertations, 2020-2023

Compact image systems bring up people's attention in the field of target recognition, surveillance, situation awareness or even photography. Conventional metrics assess image system based on image quality without considering systems' volume. More comprehensive metrics, such as General Image-Quality Equation and the Targeting Task Performance metric, incorporates all image system components from object, lenses to detector and even imaging processing algorithm. All these key factors prohibit these metrics from being applied to image system in a convenient manner. Here, we propose a simple metric, volumetric imaging efficiency, considering both image quality and volume. Only concentrate on optical lenses enables the …

Review Of Current Reactive Force Field Potentials For Use In Simulating The Atomic Layer Deposition Of Alumina On Aluminum, Devon T. Romine

Graduate Theses/Dissertations

Alumina has recently garnered quite a bit of attention for use as a tunnel barrier in Josephson tunnel junctions. The quality of the metal oxide layer in the Josephson tunnel junction is a key factor in its effectiveness. To optimize the deposition method of alumina, we need a deep understanding of the large-scale surface interactions that cannot be reached using ab initio molecular dynamics. In this study, I have compared two existing reactive force field (ReaxFF) parameters to determine their abilities to model the atomic layer deposition (ALD) of alumina on an aluminum surface. ReaxFF molecular dynamics was chosen because …

Computational And Experimental Studies Of Adsorption And Reactions On Molybdenum Nitride And Silica Covered Ruthenium Surfaces, Muhammad Sajid

Electronic Theses and Dissertations, 2020-2023

Fundamental studies of material surfaces are of continued interest to the development and improvement of many modern technologies, e.g. catalysis, energy efficient electronics, and high-capacity batteries etc. This dissertation targets two distinct sets of molecule-surface interactions relevant to the continued development of structure-property correlations using tools from Density Functional Theory with added verification from ultrahigh vacuum surface-science experiments. These include Haber-Bosch interactions at molybdenum-nitride surfaces and separation-dependent interactions between simple aromatics and Ru(0001) used to model a metal contact of Organic Electronic Devices (OEDs). In the first study, we focus on computational modelling of nitrogen fixation reactions on Mo- and …

A Surrogate Model Of Molecular Dynamics Simulations For Polar Fluids: Supervised Learning Methods For Molecular Polarization And Unsupervised Methods For Phase Classification, Zackerie W. Hjorth

Dissertations, Master's Theses and Master's Reports

Molecular Dynamic (MD) simulation is a standard computational tool in soft matter physics. While very powerful, it is computationally expensive, leading to some simulations taking days or even weeks to complete depending on the size of your computer cluster. Finding computationally cheap surrogate models which can learn the output features of MD simulation is therefore highly motivated. In this report I explore the use of deep neural network ensembles as well as support vector machine regressors as surrogate models for MD simulation. From the output of the surrogate models, we can then employ unsupervised learning methods to get insight into …

Optical And Single Particle Properties Of North Atlantic Free Tropospheric Aerosols And Implications For Aerosol Direct Radiative Forcing, Megan Morgenstern

Dissertations, Master's Theses and Master's Reports

Human-induced climate change has steadily become a reality rather than a possibility. One factor that plays into climate change is radiative forcing due to aerosol-radiation interactions (ARI). As such, it is important to understand how aerosols (atmospheric particles) interact with solar radiation. This work looks at seven samples of well-aged aerosols (aerosols traveling in the atmosphere for at least a few days) collected at Pico Mountain Observatory in the summer of 2015. Pico Mountain Observatory is located in a remote, high elevation site in the Azores, in the Eastern-North Atlantic Ocean. The goals of the study were to analyze the …

The Effects Of "Sticky Stuff" On The Spin Rate And Break Of A Baseball Pitch, Natalie Dale

Scripps Senior Theses

In June 2021, Major League Baseball cracked down on the use of foreign substances by pitchers on the ball (Castrovince, 2021a). It is believed the sticky substances give the pitchers an unfair advantage over batters since they increase spin rate, consequently, through the Magnus Effect, creating more movement or “break” in the pitch, making it harder to hit. There are existing gaps in empirical research on this topic, thus the goal of this project was to determine the effect the banned substances have on the spin rate and related break of the pitches. By using pitch tracking technology, two types …

Characterization Of Undoped Csi At Cryogenic Temperatures, Yongjin Yang

Dissertations and Theses

Doped CSI (Cesium iodide) is wildly used in many detectors. Pure cesium iodide can only perform well at low temperature due to its luminous properties. Its luminous efficiency at low temperature is even better than that of impurity-containing cesium iodide. So we want to measure its properties at low temperatures. In chapter 3, we measure the light yield of the pure CSI, which is the important property as a detector. We also introduce our experimental equipment and methods. In chapter 4, the quenching factor represents the efficiency of energy deposition. This value is a key point for our future detection …

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina

Electrical & Computer Engineering Faculty Publications

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …

Extractable Entanglement From A Euclidean Hourglass, Takanori Anegawa, Norihiro Iizuka, Daniel Kabat

Publications and Research

We previously proposed that entanglement across a planar surface can be obtained from the partition function on a Euclidean hourglass geometry. Here we extend the prescription to spherical entangling surfaces in conformal field theory. We use the prescription to evaluate log terms in the entropy of a conformal field theory in two dimensions, a conformally coupled scalar in four dimensions, and a Maxwell field in four dimensions. For Maxwell we reproduce the extractable entropy obtained by Soni and Trivedi. We take this as evidence that the hourglass prescription provides a Euclidean technique for evaluating extractable entropy in quantum field theory.

Defining Entanglement Without Tensor Factoring: A Euclidean Hourglass Prescription, Takanori Anegawa, Norihiro Iizuka, Daniel Kabat

Publications and Research

We consider entanglement across a planar boundary in flat space. Entanglement entropy is usually thought of as the von Neumann entropy of a reduced density matrix, but it can also be thought of as half the von Neumann entropy of a product of reduced density matrices on the left and right. The latter form allows a natural regulator in which two cones are smoothed into a Euclidean hourglass geometry. Since there is no need to tensor factor the Hilbert space, the regulated entropy is manifestly gauge invariant and has a manifest state-counting interpretation. We explore this prescription for scalar fields, …

Two-Loop Four-Fermion Scattering Amplitude In Qed, R. Bonciani, A. Broggio, S. Di Vita, A. Ferroglia, M. K. Mandal, P. Mastrolia, L. Mattiazzi, A. Primo, J. Ronca, U. Schubert, W. J. Torres Bobadilla, F. Tramontano

Publications and Research

We present the first fully analytic evaluation of the transition amplitude for the scattering of a massless into a massive pair of fermions at the two-loop level in quantum electrodynamics. Our result is an essential ingredient for the determination of the electromagnetic coupling within scattering reactions, beyond the currently known accuracy, which has a crucial impact on the evaluation of the anomalous magnetic moment of the muon. It will allow, in particular, for a precise determination of the leading hadronic contribution to the (g − 2)_μ in the MUonE experiment at CERN, and therefore can be used to …

A Template Method To Measure The $T \Bar T$ Polarisation, J. A. Aguilar-Saavedra, M. C. N. Fiolhais, P. Martín-Ramiro, J. M. Moreno, António Onofre

Publications and Research

We develop a template method for the measurement of the polarisation of $t \bar t$ pairs produced in hadron collisions. The method would allow to extract the individual fractions of $t_L \bar t_L$, $t_R \bar t_R$, $t_L \bar t_R$ and $t_R \bar t_L$ pairs with a fit to data, where L, R refer to the polarisation along any axis. These polarisation fractions have not been independently measured at present. Secondarily, the method also provides the net polarisation of t and $\bar t$, as well as their spin correlation for arbitrary axes.

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan

Electrical and Computer Engineering Faculty Publications

Spiking neural network hardware offers a high performance, power-efficient and robust platform for the processing of complex data. Many of these systems require supervised learning, which poses a challenge when using gradient-based algorithms due to the discontinuous properties of SNNs. Memristor based hardware can offer gains in portability, power reduction, and throughput efficiency when compared to pure CMOS. This paper proposes a memristor-based spiking liquid state machine (LSM). The inherent dynamics of the LSM permit the use of supervised learning without backpropagation for weight updates. To carry out the design space evaluation of the LSM for optimal hardware performance, several …

Bias Impedes Progress In Physical Biology, Consciousness Studies And Quantum Gravity, Maurice Goodman

Articles

If scientists hope to make progress in consciousness studies they needs to accept that biased judgments have a major influence on the sciences, how we divide them up, how they are funded and this, in turn, has a profound impact on progress. The imbalance in funding, resulting from bias, in favour of the life and health sciences needs to be addressed as does why perversely little of this funding is devoted to a physics explanation of self-organisation and life on the mesoscopic scale? While life (the cell) is an outstanding example of self-organisation on the mesoscopic scale we need to …

Theoretical Investigation On Optical Properties Of 2d Materials And Mechanical Properties Of Polymer Composites At Molecular Level, Geeta Sachdeva

Dissertations, Master's Theses and Master's Reports

The field of two-dimensional (2D) layered materials provides a new platform for studying diverse physical phenomena that are scientifically interesting and relevant for technological applications. Theoretical predictions from atomically resolved computational simulations of 2D materials play a pivotal role in designing and advancing these developments. The focus of this thesis is 2D materials especially graphene and BN studied using density functional theory (DFT) and molecular dynamics (MD) simulations. In the first half of the thesis, the electronic structure and optical properties are discussed for graphene, antimonene, and borophene. It is found that the absorbance in (atomically flat) multilayer antimonene (group …

Random Walks On Quasi-1d Infinite Structures, Srawut Sasom

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the present thesis a random walk on quasi-1d lattices as a model for transport processes on quasi-1d materials is analytically investigated. The scope of the present work is to shed light on the asymptotic behavior of basic statistical properties of the random walk on such structures including the first and the second moments of the walker location along the structure axis, the probability of return to the starting site, the probability of ever reach a given site, the conditional mean first-passage time to a given site and the expected number of distinct sites visited. The first part of the …

From Evaluating The Performance Of Approximations In Density Functional Theory To A Machine Learning Design, Pedram Tavazohi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Density-functional theory (DFT) has gained popularity because of its ability to predict the properties of a large group of materials a priori. Even though DFT is exact, there are inaccuracies introduced into the theory due to the approximations in the exchange-correlation (XC) functionals. Over the 50 years of its existence, scientists have tried to improve the design of the XC functionals. The errors introduced by these functionals are not consistent across all types of solid-state materials. In this project, a high throughput framework was utilized to compare the theoretical DFT predictions with the experimental results available in the Inorganic Crystal …

Development Of Computational Methods For Electronic Structural Characterization Of Strongly Correlated Materials: From Different Ab-Initio Perspectives, Uthpala K. Herath

Graduate Theses, Dissertations, and Problem Reports (ETD)

The electronic correlations in materials drive a variety of fascinating phenomena from magnetism to metal-to-insulator transitions (MIT), which are due to the coupling between electron spin, charge, ionic displacements, and orbital ordering. Although Density Functional Theory (DFT) successfully describes the electronic structure of weakly interacting material systems, being a static mean-field approach, it fails to predict the properties of Strongly Correlated Materials (SCM) that include transition and rare earth metals where there is a prominent electron localization as in the case of d and f orbitals due to the nature of their spatial confinement.

Dynamical Mean Field Theory (DMFT) is …