Physics
Browse by
Recent Submissions
-
Topological Quantum Computing with Majorana Zero Mode Qubits: Theory and State of the Art
(2020)Topological Quantum Computing (TQC) has been proposed as a strong candidate for universal quantum computation, due to its inherent capability for fault-tolerance in the form of error detection and correction, and robustness ... -
Towards a measurement of the nuclear magnetic octupole moment of barium-137
(2011)A description of a 2051 nm laser system designed and built for use in a number of proposed experiments is presented. Results of spectroscopic measurements of the 6S1/2 to 5D3/2 transition in 138Ba+ are discussed. The ... -
Novel Ion Traps for Enhanced Fluorescence Collections and Single Photon Sources Based on Barium Ions
(2010)Efficient ion-photon interface is critical for ion-photon and ion-ion entanglement generation, which are the fundamental building blocks for loophole-free Bell inequality violation tests based on ion qubits, and for the ... -
Experiments with remote entanglement using single barium ions
(2010)Barium ions are trapped and Doppler cooled in a linear Paul trap with the goal of demonstrating state initialization, single-qubit operations and detection. Rabi rotations are demonstrated on the 6S1/2 ↔ 6P3/2 transition ... -
Barium Ions for Quantum Computation
(2009)Barium ion is investigated as a hyperfine qubit. 137Ba+ is trapped in a linear Paul trap and laser cooled. Isotope selective photoionization is employed to improve trapping from an isotopically inpure source. Optical ... -
Deep Learning Applications for Particle Physics in Tracking and Calorimetry
This thesis presents an in-depth exploration of advanced deep learning applications in particle physics, particularly in the context of tracking, calorimetry, and energy reconstruction within High Energy Physics (HEP) ... -
Sparse deep neural networks for modeling physical and biological systems
Characterizing the relationship between network performance and its parameters is an active area of investigation within the fields of deep learning and complex network science. In this thesis, sparse deep neural networks ... -
Utilizing modern machine learning approaches for image cytometry
Until recently, the scientific community has lacked image segmentation tools that are precise, reliable, and general-purpose. Such tools are especially needed in applications to bacterial image cytometry, wherein single-pixel ... -
Exploring Neural Correlates of Flexible Cognition During a Complex Decision Making Task
Efficiently solving complex decision making tasks typically arises from the use of schemas, abstract structures that organize experience and guide integration of novel information. There is a wealth of knowledge related ... -
Novel Observations in Mixed Reality (NOMR): Designing a New Frontier of Physics to Practice Generating Scientific Models
The creation of new knowledge in the form of scientific models is a cornerstone of the process of science. In physics laboratory instruction, students are very often stuck in a confirmatory mindset; they have been conditioned ... -
Developments in the application of Cyclotron Radiation Emission Spectroscopy (CRES) towards the precise determination of MeV-scale β-energy spectra
This thesis presents an apparatus for detection of cyclotron radiation yielding a frequency-based β± kinetic energy determination in the 5 keV to 2.1 MeV range, characteristic of nuclear β decays. The cyclotron frequency ... -
Probing and controlling magnetism in 2D materials
A central goal of condensed matter physics is the discovery and design of materials systems with properties and behavior that have the potential to advance technology. The rapidly expanding field of two-dimensional materials ... -
The Influence of Dark and Ordinary Matter Physics on Galaxy Formation
Overwhelming observational evidence suggests that 85$\%$ of all the matter in the universe is dark matter (DM), a particle whose microscopic properties remain poorly constrained over many orders of magnitude. The current, ... -
Laser Cooling and Trapping of 6Li: Experimental Tools for Many-Body Fermionic Dynamics and Ring Trap
This thesis delves into the laser cooling and trapping of 6Li, a fermionic atom, with the aimof creating experimental tools for the exploration of many-body fermionic dynamics in quantum degeneracy, specifically within ... -
Beam Dynamics Challenges in the Muon g-2 Experiment
The muon's anomalous magnetic moment $a_{\mu}$ has hinted at physics beyond the standard model for nearly 20 years. The Muon $g-2$ experiment at Fermilab aims to measure $a_{\mu}$ to 140 parts per billion (ppb) precision. ... -
Machine Learning for Aero-Optical Wavefront Characterization and Forecasting
The laser is a masterwork of the previous century of physics, but to harness its power coherently in the turbulent wilds of the sky remains a challenge. Free-space lasing hosts myriad applications, from direct energy ... -
The interplay between magnetism and electronic structure in topological materials
Over the past 40 years, topological materials have emerged as a fascinating new class of phases of matter, characterized by their robust fundamental properties that remain invariant under smooth changes of material parameters, ... -
Quantum Simulation of Quantum Field Theories
The theory of quantum chromodynamics (QCD) describes the nuclear forces that bind quarks into nucleons and nucleons into nuclei. The dynamics in the non-perturbative regime of QCD are of relevance for understanding inelastic ... -
Quantum magnetic imaging for DNA biophysical measurements
An outstanding challenge in biophysics is sensing the relative bio-mechanical orienta-tion of single-molecule biological systems. Prior approaches used to study single-molecule biophysics rely on attaching fluorescent or ... -
Development of a quantum, magnetic-imaging platform for biophysical measurements
Single-molecule measurements help build up the fundamental understanding of many important bio-logical functions. Due to the wide variety of molecules that have been studied, and the properties of these molecules that often ...