Elementary Particles and Fields and String Theory Commons^™

Applications Of Machine Learning In Gravitational-Wave Research With Current Interferometric Detectors, Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

Physics Faculty Research & Creative Works

This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning …

Several Problems In Nonlinear Schrödinger Equations, Tim Van Hoose

Masters Theses

“We study several different problems related to nonlinear Schrödinger equations….

We prove several new results for the first equation: a modified scattering result for both an averaged version of the equation and the full equation, as well as a set of Strichartz estimates and a blowup result for the 3d cubic problem.

We also present an exposition of the classical work of Bourgain on invariant measures for the second equation in the mass-subcritical regime”--Abstract, page iv.

Improving The Background Of Gravitational-Wave Searches For Core Collapse Supernovae: A Machine Learning Approach, M. Cavaglià, S. Gaudio, T. Hansen, K. Staats, M. Szczepanczyk, M. Zanolin

Physics Faculty Research & Creative Works

Based on the priorO1-O2observing runs, about30%of the data collected by Advanced LIGO and Virgo Internext observing runs are expected tobe single-interferometer data, i.e. they will be collected at times when only one detector in the network is operating in observing mode. Searches for gravitational-wave signals from supernova events do not rely on matched filtering techniques because of the stochastic nature of the signals. If a Galactic supernova occurs during single-interferometer times, separation of its unmodelled gravitational-wave signal from noise will be even more difficult due to lack of coherence between detectors. We present a novel machine learning method to perform …

A Study Of The Potential Applications Of Am241, And Determining The Feasibility Of Using Gamma Spectroscopy For Future Physical Validation, Eric A. Feissle

Masters Theses

“Am241 is typically produced via Pu241 decay in a uranium fueled reactor. Presence of Am241 can be used as the age estimation tool for spent fuel, which is a focus of this thesis along with the interest of the measurement and the ratio of production rates of Am241’s activation products; Americium-242 and its first excited state of Americium-242m. MCNP models of the core and BEGe 3825 detector were built. These models were compared with established and physical measurements of gamma/x-ray standards that were available at the reactor. Thermal fluxes at 200 kW for potential foils centered in the source holder …