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Articles 1 - 5 of 5
Full-Text Articles in Physics
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Physics-Constrained Hyperspectral Data Exploitation Across Diverse Atmospheric Scenarios, Nicholas M. Westing
Theses and Dissertations
Hyperspectral target detection promises new operational advantages, with increasing instrument spectral resolution and robust material discrimination. Resolving surface materials requires a fast and accurate accounting of atmospheric effects to increase detection accuracy while minimizing false alarms. This dissertation investigates deep learning methods constrained by the processes governing radiative transfer to efficiently perform atmospheric compensation on data collected by long-wave infrared (LWIR) hyperspectral sensors. These compensation methods depend on generative modeling techniques and permutation invariant neural network architectures to predict LWIR spectral radiometric quantities. The compensation algorithms developed in this work were examined from the perspective of target detection performance using …
Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus
Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus
Theses and Dissertations
This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …
Qwasi: The Quantum Walk Simulator, Warren V. Wilson
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 …
Global Gradient-Based Phase Unwrapping Algorithm For Increased Performance In Wavefront Sensing, Bryan R. Bartelt
Global Gradient-Based Phase Unwrapping Algorithm For Increased Performance In Wavefront Sensing, Bryan R. Bartelt
Theses and Dissertations
As the reliance on satellite data for military and commercial use increases, more effort must be exerted to protect our space-based assets. In order to help increase our space domain awareness (SDA), new approaches to ground-based space surveillance via wavefront sensing must be adopted. Improving phase-unwrapping algorithms in order to assist in phase retrieval methods is one way of increasing the performance in current adaptive optics (AO) systems. This thesis proposes a new phase-unwrapping algorithm that uses a global, gradient-based technique to more rapidly identify and correct for areas of phase wrapping during particular phase retrieval methods. This is beneficial …
Sparsity And Weak Supervision In Quantum Machine Learning, Seyran Saeedi
Sparsity And Weak Supervision In Quantum Machine Learning, Seyran Saeedi
Theses and Dissertations
Quantum computing is an interdisciplinary field at the intersection of computer science, mathematics, and physics that studies information processing tasks on a quantum computer. A quantum computer is a device whose operations are governed by the laws of quantum mechanics. As building quantum computers is nearing the era of commercialization and quantum supremacy, it is essential to think of potential applications that we might benefit from. Among many applications of quantum computation, one of the emerging fields is quantum machine learning. We focus on predictive models for binary classification and variants of Support Vector Machines that we expect to be …