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Theses/Dissertations

Optimization

Northern Illinois University

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Full-Text Articles in Physical Sciences and Mathematics

An Upgraded Photoinjector For The Argonne Wakefield Accelerator, Emily Frame Jan 2022

An Upgraded Photoinjector For The Argonne Wakefield Accelerator, Emily Frame

Graduate Research Theses & Dissertations

The Argonne Wakefield Accelerator (AWA) is planning an upgrade of the drive-beam accelerator’s photoinjector, the driving force of electron generation. The upgrade’s main goal is to improve beam brightness using linear accelerating cavities and a radiofrequency-gun cavity. In the process of this upgrade, one of the beam focusing solenoids is being redesigned. A beam dynamics optimization is performed for two new solenoid designs, with considerations for producing low-charge (∼ 1 nC) electron bunches as well as operations at higher charges (∼ 50 nC). This project focuses on the optimization study for both the low- and high-charge regimes, exploring the impact …


Methods For Computing The Global Optimum Of Non-Convex Objectives, Isaac Michael Hawn Jan 2022

Methods For Computing The Global Optimum Of Non-Convex Objectives, Isaac Michael Hawn

Graduate Research Theses & Dissertations

\begin{abstract}In this thesis, we concern ourselves with solving the unconstrained optimization problem % \begin{gather*} \text{Minimize}\; f(x)\\\text{subject to}\; x\in X \end{gather*} % where $f\colon\mathbb{R}^N\to \mathbb{R}$ is a non-convex function, possibly with infinitely many local minima. Solving such a problem, especially in higher dimensions often proves to be an extraordinarily difficult task, either in time complexity or in the methodology itself. Indeed, mathematicians must often resort to algorithms which make use of problem structure and which may not generalize well. In this thesis, we present two algorithms which solve this problem, albeit with their own shortcomings.

First, we present a new, $N$-dimensional …


Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan Jan 2020

Optimizing Cluster Sets For The Scan Statistic Using Local Search, James Shulgan

Graduate Research Theses & Dissertations

In recent years, scattering sensors to produce wireless sensor networks (WSN) has been proposed for detecting localized events in large areas. Because sensor measurements are noisy, the WSN needs to use statistical methods such as the scan statistic. The scan statistic groups measurements into various clusters, computes a cluster statistic for each cluster, and decides that an event has happened if any of the statistics exceeds a threshold. Previous researchers have investigated the performance of the scan statistic to detect events; however, little attention was given to the optimization of which clusters the scan statistic should use. Using the scan …