Physics Commons^™

Symbolic Computation Of Squared Amplitudes In High Energy Physics With Machine Learning, Abdulhakim Alnuqaydan

Theses and Dissertations--Physics and Astronomy

The calculation of particle interaction squared amplitudes is a key step in the calculation of cross sections in high-energy physics. These complex calculations are currently performed using domain-specific symbolic algebra tools, where the computational time escalates rapidly with an increase in the number of loops and final state particles. This dissertation introduces an innovative approach: employing a transformer-based sequence-to-sequence model capable of accurately predicting squared amplitudes of Standard Model processes up to one-loop order when trained on symbolic sequence pairs. The primary objective of this work is to significantly reduce the computational time and, more importantly, develop a model that …

Machine Learning-Based Jet And Event Classification At The Electron-Ion Collider With Applications To Hadron Structure And Spin Physics, Kyle Lee, James Mulligan, Mateusz Płoskoń, Felix Ringer, Feng Yuan

Physics Faculty Publications

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in …

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 …

Deeply Learning Deep Inelastic Scattering Kinematics, Markus Diefenthaler, Abdullah Farhat, Andrii Verbytskyi, Yuesheng Xu

Mathematics & Statistics Faculty Publications

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q² and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection …

Making Artificial Cips Data With A Generative Adversarial Neural Network, Austin Hedges

Fall Showcase for Research and Creative Inquiry

Polar mesospheric clouds (PMCs) have been studied for thirteen years by NASA's Aeronomy of Ice in the Mesosphere (AIM) satellite. The Cloud Imaging and Particle Size (CIPS) instrument onboard AIM has taken many images of PMCs over this time. Such a large number of images makes CIPS data ideal for training neural networks which require large datasets. CIPS images were used to train a Generative Adversarial Network (GAN) to train towards being able to generate purely artificial CIPS-like images.

Qwasi: The Quantum Walk Simulator, Warren V. Wilson

Theses and Dissertations

As quantum computing continues to evolve, the ability to design and analyze novel quantum algorithms becomes a necessary focus for research. In many instances, the virtues of quantum algorithms only become evident when compared to their classical counterparts, so a study of the former often begins with a consideration of the latter. This is very much the case with quantum walk algorithms, as the success of random walks and their many, varied applications have inspired much interest in quantum correlates. Unfortunately, finding purely algebraic solutions for quantum walks is an elusive endeavor. At best, and when solvable, they require simple …

9th Annual Postdoctoral Science Symposium, University Of Texas Md Anderson Cancer Center Postdoctoral Association

Annual Postdoctoral Science Symposium Abstracts

The mission of the Annual Postdoctoral Science Symposium (APSS) is to provide a platform for talented postdoctoral fellows throughout the Texas Medical Center to present their work to a wider audience. The MD Anderson Postdoctoral Association convened its inaugural Annual Postdoctoral Science Symposium (APSS) on August 4, 2011.

The APSS provides a professional venue for postdoctoral scientists to develop, clarify, and refine their research as a result of formal reviews and critiques of faculty and other postdoctoral scientists. Additionally, attendees discuss current research on a broad range of subjects while promoting academic interactions and enrichment and developing new collaborations.

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

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

Physics Theses and Dissertations

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

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

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

University of New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …

Hardware Design Theory (Using Raspberry Pi), Anthony Kelly, Thomas Blum Dr.

Undergraduate Research

The concept for this research proposal is focused on achieving three main objectives:

1) To understand the logic and design behind the Raspberry Pi (RbP) mini-computer model, including: all hardware components and their functions, the capabilities [and limits] of the RbP, and the circuit engineering for these components.

2) To be able to, using the Python high-level language, duplicate, manipulate, and create RbP projects ranging from basic user-input and response systems to the theories behind more intricate and complicated observatory sensors.

3) Simultaneously, in order to combine a mutual shared interest of History and to blend in work done within …

Grasping The Void: Immersion Tactics Using Gesture Controlled Physics Interaction Systems In Virtual Reality, Avery Rapson

Senior Independent Study Theses

This thesis uses the HTC Vive in Unity to compare two different types of object interaction systems in order to determine the effectiveness of physics based interaction systems in a virtual environment. The research problem that motivates this project is the fact that there is no standardized method for defining successful object interaction techniques in VR. There are numerous interaction techniques in VR that fall short of simulating realistic object interaction. This project explores a physics based interaction system and examines how effective it is by comparing it to a non-physics based system. A model house with various interactable objects …

Spatio-Temporal Generalization Of The Harris Criterion And Its Application To Diffusive Disorder, Thomas Vojta, Ronald Dickman

Physics Faculty Research & Creative Works

We investigate how a clean continuous phase transition is affected by spatiotemporal disorder, i.e., by an external perturbation that fluctuates in both space and time. We derive a generalization of the Harris criterion for the stability of the clean critical behavior in terms of the space-time correlation function of the external perturbation. As an application, we consider diffusive disorder, i.e., an external perturbation governed by diffusive dynamics, and its effects on a variety of equilibrium and nonequilibrium critical points. We also discuss the relation between diffusive disorder and diffusive dynamical degrees of freedom in the example of model C of …

Strong-Disorder Magnetic Quantum Phase Transitions: Status And New Developments, Thomas Vojta

Physics Faculty Research & Creative Works

This article reviews the unconventional effects of random disorder on magnetic quantum phase transitions, focusing on a number of new experimental and theoretical developments during the last three years. On the theory side, we address smeared quantum phase transitions tuned by changing the chemical composition, for example in alloys of the type A_1-xB_x. We also discuss how the interplay of order parameter conservation and overdamped dynamics leads to enhanced quantum Griffiths singularities in disordered metallic ferromagnets. Finally, we discuss a semiclassical theory of transport properties in quantum Griffiths phases. Experimental examples include the ruthenates Sr_{1-x …}

Rare Regions And Griffiths Singularities At A Clean Critical Point: The Five-Dimensional Disordered Contact Process, Thomas Vojta, John Igo, José A. Hoyos

Physics Faculty Research & Creative Works

We investigate the nonequilibrium phase transition of the disordered contact process in five space dimensions by means of optimal fluctuation theory and Monte Carlo simulations. We find that the critical behavior is of mean-field type, i.e., identical to that of the clean five-dimensional contact process. It is accompanied by off-critical power-law Griffiths singularities whose dynamical exponent z' saturates at a finite value as the transition is approached. These findings resolve the apparent contradiction between the Harris criterion, which implies that weak disorder is renormalization-group irrelevant, and the rare-region classification, which predicts unconventional behavior. We confirm and illustrate our theory by …

Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar

Legacy Theses & Dissertations (2009 - 2024)

The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner.

Nonlinear Dynamics In Combinatorial Games: Renormalizing Chomp, Eric J. Friedman, Adam S. Landsberg

WM Keck Science Faculty Papers

We develop a new approach to combinatorial games that reveals connections between such games and some of the central ideas of nonlinear dynamics: scaling behaviors, complex dynamics and chaos, universality, and aggregation processes. We take as our model system the combinatorial game Chomp, which is one of the simplest in a class of "unsolved" combinatorial games that includes Chess, Checkers, and Go. We discover that the game possesses an underlying geometric structure that "grows" (reminiscent of crystal growth), and show how this growth can be analyzed using a renormalization procedure adapted from physics. In effect, this methodology allows one to …