Surface Preparation Study

This work explores a custom air atmospheric pressure plasma treatment (APPT) machine’s effectiveness in cleaning and chemically activating a CFRP surface. It is explore by implementing water contact angle (WCA) measurements, water-break free (WBF) testing, and adhesive tubular lap-joint (TLJ) tensile testing. An 8x3 test matrix of different machine parameters is defined with the bounding conditions being the machine’s capabilities and industry standard recommendations. Each configuration of the test matrix is explored after treatment at multiple time intervals up to 2 weeks afterwards to gain insight into the outlife of the treatments with the intention of adhesively bonding to the surfaces. Multiple data analysis processes such as one-way ANOVA studies, box and whisker plot interpretations, and visualizations of (24) different process parameters at once are performed to understand the custom plasma machine’s effect on the surface of the CFRP components. Results show that treatments that are closer to the tube are best for uniformly treating the surface which is supported with all of the tests performed. It is also shown that there is a statistical difference between the surface chemistry of different CFRP tows visible on the surface of the CFRP tube

Retooling : experiments in digital apprenticeship

Over the past decade, rapid advancement in the fields of artificial intelligence and machine learning has led to an abrupt shift in the skills we designate as “human” and the skills we delegate to machines. This shift can be characterized, to some degree, by the transformation of tacit knowledge–knowledge that is difficult to transfer or quantify, into explicit knowledge–a language that machines can both understand and act on. An adjacent surge in democratized education platforms has made it possible for anyone to begin learning a new skill. Mastering a skill however, especially hands-on skills, often requires a level of tacit knowledge and expertise that a static YouTube tutorial cannot deliver. This thesis explores a future in which tools act as educators–a medium to transmit the tacit knowledge of expert tool users to novices. Experiments with homemade flamethrowers, exoskeleton gloves, and a hacked pottery wheel have helped me draft a framework for successfully embedding digital augmentation into tools while avoiding the pitfalls of digital dependency

F22RS SGR No. 1 (Allen Hall Murals)

To Urge and Request Louisiana State University paint a new representation of Student Life over the Mural in Allen Hall depicting segregation and people of color picking cotto

Investigating emotional facial recognition in trait anxious individuals: an eye-tracking study

The current study examined the relationship between the recognition of the six basic emotions as a function of trait anxiety. Previous research has led to conflicting findings; one study reported increased accuracy for expressions of fear, and another finding no differences as a function of trait anxiety. As suggested by previous literature, the current study included eye movement measures to further investigate the processing of emotional expressions in anxious individuals. The current study also utilized four intensities of emotional expressions, a new addition to anxiety literature, as well as incorporated a measure of emotional dysregulation. The task consisted of a free viewing recognition task of expressions of the six basic emotions. Results from the current study revealed no accuracy or viewing time differences as a function of trait anxiety, however, a robust relationship was found between level of trait anxiety and emotional dysregulation. Clinical implications and future directions are discussed.Master of Arts (MA) in Psycholog

Give me a verb! Give me a noun!: an ERP investigation of perceptual words with ambiguous word classes

Previous research has demonstrated that retrieving a verb from memory elicits different neural activity than retrieving a noun, however, what about words that can be both? It has been found that the context surrounding a target word hold primary importance in the classification of a word as being either a verb or a noun in the case of an ambiguous target word. Using Event-Related Potentials as a physiological instrument to measure cognitive processes through the means of a lexical decision task; the current study will examine brain activity when context is manipulated for words that are considered both verbs and nouns. The target words consisted of 5 English words: view, watch, witness, notice, sense. During the task, there were 2 sets of conditions presented to the participants twice. The first condition consisted of the words ‘to’ and ‘the’ preceding the target word in a random order. The second condition consisted of the word ‘this’ preceding or succeeding the target word in a random order. After the completion of all conditions, participants were prompted to complete a counterbalanced 9-point likert scale for each target word. They were asked to rate their opinion of how strongly each word was classified as a verb or a noun. Resulting ERP data was examined for contextual differences across word context category and between regions of interest montages.Honours Essa

Variational Quantum Eigensolvers Applied to Problems in High Energy Physics

Variational methods have long been used to study strongly-correlated quantum systems. Despite the successes of classical protocols, these are limited in the study of quantum systems, either due to numerical errors like the sign problem or the massive memory requirement to represent large quantum systems. Variational quantum eigensolvers (VQEs) overcome these problems and as a result have been an exciting area of research for the past decade. VQEs use a hybrid classical-quantum set-up, where a cost function (usually the expectation value of an operator) is produced by the quantum processor and then optimized on a classical computer. VQEs have been applied to fields such as quantum chemistry, condensed matter physics, high-energy physics, and classical optimization problems. In this thesis, we investigate VQEs to study gauge theories, which describe fundamental physical interactions and are hard to simulate classically. We use two different approaches in implementing a VQE to study two classes of problems. In the first half of the thesis, we design a VQE to study the U(1) Higgs gauge theory in one spatial dimension. This model is particularly interesting due to the presence of a topological term, which is a candidate to explain the observed CP violation in the universe. In order to perform a quantum simulation of the U(1) Higgs model, the theory is cast on a lattice. In the limit where the lattice size is large and the lattice spacing is small, the continuum limit can be reached and the results correctly resemble the original theory. However, when the lattice is too small or the spacing too big, results are spoiled by finite size effects. In this thesis, we investigate the effects of a finite lattice and determine the parameters to correctly reproduce a first-order phase transition of the continuous theory. Importantly, to resemble a realistic experiment, we include the statistical and intrinsic quantum noise in our VQE. We design the protocol to be applied on a microwave-photonic platform, which is well-suited due to the bosonic nature of the theory's electrical modes. In the second half of the thesis, we design a new class of VQEs, based on a measurement-based quantum computer (MBQC) instead of the typical circuit-based set-up. Rather than performing gates on an initial state, a MBQC transforms an initial state by entangling it with a number of auxiliary qubits which are subsequently measured, resulting in a modification of the initial state. In this part of the thesis, we compare the standard, circuit-based VQE with our newly-designed measurement-based VQE (MB-VQE) through two meaningful examples. First, we introduce a novel way to construct variational state families, using measurement-based techniques, that is more costly to access with circuit-based VQEs. We apply this technique to find the ground state of a two-dimensional, periodic Z2 matter-free lattice gauge theory. In the second approach, we directly translate the circuit-based VQE to a MB-VQE and apply this to the U(1) Schwinger lattice gauge theory, which is used as a benchmarking problem for VQEs. These examples demonstrate that there are specific problems which are better suited for a MB-VQE