The Effect of Psychological Distance on Willingness to Engage in Ideologically Based Violence

Research on the cognitive and decision-making processes of individuals who choose to engage in ideologically based violence is vital. Our research examines how abstract and concrete construal mindsets affect likelihood to engage in ideologically based violence. Construal Level Theory (CLT) states that an abstract mindset (high-level construal), as opposed to a concrete mindset (low-level construal), is associated with a greater likelihood of engaging in goal-oriented, value-motivated behaviors. Assuming that ideologically based violence is goal-oriented, we hypothesized that high-level construal should result in an increased likelihood of engaging in ideologically based violence. In the pilot study we developed and tested 24 vignettes covering controversial topics and assessed them on features such as relatability, emotional impact, and capacity to elicit a violent reaction. The ten most impactful vignettes were selected for use in the primary investigations. The two primary investigations examined the effect of high- and low-level construal manipulations on self-reported likelihood of engaging in ideologically based violence. Self-reported willingness was measured through an ideological violence assessment. Data trends implied that participants were engaged in the study, as they reported a higher willingness to engage in ideologically based violence when they had a higher passion for the vignette's social issue topic. Our results did not indicate a significant relationship between construal manipulations and level of passion for a topic.

Spectral graph theory with applications to quantum adiabatic optimization

In this dissertation I draw a connection between quantum adiabatic optimization, spectral graph theory, heat-diffusion, and sub-stochastic processes through the operators that govern these processes and their associated spectra. In particular, we study Hamiltonians which have recently become known as ``stoquastic'' or, equivalently, the generators of sub-stochastic processes. The operators corresponding to these Hamiltonians are of interest in all of the settings mentioned above. I predominantly explore the connection between the spectral gap of an operator, or the difference between the two lowest energies of that operator, and certain equilibrium behavior. In the context of adiabatic optimization, this corresponds to the likelihood of solving the optimization problem of interest. I will provide an instance of an optimization problem that is easy to solve classically, but leaves open the possibility to being difficult adiabatically. Aside from this concrete example, the work in this dissertation is predominantly mathematical and we focus on bounding the spectral gap. Our primary tool for doing this is spectral graph theory, which provides the most natural approach to this task by simply considering Dirichlet eigenvalues of subgraphs of host graphs. I will derive tight bounds for the gap of one-dimensional, hypercube, and general convex subgraphs. The techniques used will also adapt methods recently used by Andrews and Clutterbuck to prove the long-standing ``Fundamental Gap Conjecture''.

Strong shift equivalence, algebraic K-theory, and isolating zero-dimensional dynamics on manifolds

We study the relations of shift equivalence and strong shift equivalence for matrices over a ring $\mathcal{R}$, and establish a connection between these relations and algebraic K-theory. We utilize this connection to obtain results in two areas where the shift and strong shift equivalence relations play an important role: the study of finite group extensions of shifts of finite type, and the Generalized Spectral Conjectures of Boyle and Handelman for nonnegative matrices over subrings of the real numbers. We show the refinement of the shift equivalence class of a matrix $A$ over a ring $\mathcal{R}$ by strong shift equivalence classes over the ring is classified by a quotient $NK_{1}(\mathcal{R}) / E(A,\mathcal{R})$ of the algebraic K-group $NK_{1}(\calR)$. We use the K-theory of non-commutative localizations to show that in certain cases the subgroup $E(A,\mathcal{R})$ must vanish, including the case $A$ is invertible over $\mathcal{R}$. We use the K-theory connection to clarify the structure of algebraic invariants for finite group extensions of shifts of finite type. In particular, we give a strong negative answer to a question of Parry, who asked whether the dynamical zeta function determines up to finitely many topological conjugacy classes the extensions by $G$ of a fixed mixing shift of finite type. We apply the K-theory connection to prove the equivalence of a strong and weak form of the Generalized Spectral Conjecture of Boyle and Handelman for primitive matrices over subrings of $\mathbb{R}$. We construct explicit matrices whose class in the algebraic K-group $NK_{1}(\mathcal{R})$ is non-zero for certain rings $\mathcal{R}$ motivated by applications. We study the possible dynamics of the restriction of a homeomorphism of a compact manifold to an isolated zero-dimensional set. We prove that for $n \ge 3$ every compact zero-dimensional system can arise as an isolated invariant set for a homeomorphism of a compact $n$-manifold. In dimension two, we provide obstructions and examples.

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Jiao Tong: A Grounded Theory of Chinese International Students' Transition to American Tertiary Education

University students are more globally mobile than ever before, increasingly receiving education outside of their home countries. One significant student exchange pattern is between China and the United States; Chinese students are the largest population of international students in the U.S. (Institute of International Education, 2014). Differences between Chinese and American culture in turn influence higher education praxis in both countries, and students are enculturated into the expectations and practices of their home countries. This implies significant changes for students who must navigate cultural differences, academic expectations, and social norms during the process of transition to a system of higher education outside their home country. Despite the trends in students’ global mobility and implications for international students’ transitions, scholarship about international students does not examine students’ experiences with the transition process to a new country and system of higher education. Related models were developed with American organizations and individuals, making it unlikely that they would be culturally transferable to Chinese international students’ transitions. This study used qualitative methods to deepen the understanding of Chinese international students’ transition processes. Grounded theory methods were used to invite the narratives of 18 Chinese international students at a large public American university, analyze the data, and build a theory that reflects Chinese international students’ experiences transitioning to American university life. Findings of the study show that Chinese international students experience a complex process of transition to study in the United States. Students’ pre-departure experiences, including previous exposure to American culture, family expectations, and language preparation, informed their transition. Upon arrival, students navigate resource seeking to fulfill their practical, emotional, social, intellectual, and ideological needs. As students experienced various positive and discouraging events, they developed responses to the pivotal moments. These behaviors formed patterns in which students sought familiarity or challenge subsequent to certain events. The findings and resulting theory provide a framework through which to better understand the experiences of Chinese international students in the context of American higher education.