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Articles 1 - 11 of 11
Full-Text Articles in Other Mathematics
A Symbolic Model Of Proof Acquisition In Act-R, Beckett Morris, Kerstin Haring
A Symbolic Model Of Proof Acquisition In Act-R, Beckett Morris, Kerstin Haring
DU Undergraduate Research Journal Archive
Learning to construct mathematical proofs—formal arguments demonstrating the truth of a mathematical statement using logical deductions and previously established facts—is one of the most challenging skills in STEM education. This research aims to build the foundations for a symbolic cognitive model, using the ACT-R cognitive architecture and implementing in Python with the pyactr package, to explore how different proof strategies can be thought through with only symbols and rules. The model observes simple proofs, and its abilities are assessed based on its generalization capabilities, efficiency, and error patterns. By developing and analyzing such a model, this research provides new insights …
Machine Learning: Neural Networking With Relu And Optimization, Aidan Redmond Brownell
Machine Learning: Neural Networking With Relu And Optimization, Aidan Redmond Brownell
Undergraduate Theses, Capstones, and Recitals
At its core, learning is an algorithmic process: it begins with input data, undergoes a series of transformations or computations, and yields an output intended to solve a specific task. This output is then compared against a target or desired result, and the internal mechanisms are updated based on how well the output aligns with expectations. While this feedback-driven process occurs almost effortlessly in humans, it is a far more structured, deliberate, and computationally intensive undertaking for machines.
Basic Theory And Implementations Of Quantum Error Correction, Derek Rodriguez
Basic Theory And Implementations Of Quantum Error Correction, Derek Rodriguez
Undergraduate Theses, Capstones, and Recitals
The introduction of quantum computing has presented algorithmic solutions to computationally difficult challenges that are far more efficient than those of classical computers. These algorithms leverage the properties of quantum mechanics to manipulate the quantum properties of subatomic particles, requiring immense precision and stability. Current quantum hardware, however, is too noisy and introduces too many errors for these algorithms to be useful in practice, necessitating the use of error correction algorithms. This field survey seeks to introduce various principles of quantum mechanics relevant to quantum computing and quantum error correction (QEC), detail the implementation and motivations of a basic QEC …
Developing A Comprehensive Cognitive Model Of Math Achievement, Nina Anderson
Developing A Comprehensive Cognitive Model Of Math Achievement, Nina Anderson
Electronic Theses and Dissertations
Recently, downward trends have been reported in U.S. children’s math performance following school disruptions during COVID-19 amidst longstanding concerns for instruction and curricula within the subject. In support of efforts to remedy these declines, the current work presents two studies dedicated to identifying cognitive factors that are most strongly related to math performance, and which therefore offer promising potential targets for assessment and intervention. Both studies use data from the Colorado Learning Disabilities Research Center, which includes participants ages 8 - 16 and multiple well-validated measures of all constructs of interest. Study 1 tests three alternative latent cognitive models of …
Combinatorial Problems On The Integers: Colorings, Games, And Permutations, Collier Gaiser
Combinatorial Problems On The Integers: Colorings, Games, And Permutations, Collier Gaiser
Electronic Theses and Dissertations
This dissertation consists of several combinatorial problems on the integers. These problems fit inside the areas of extremal combinatorics and enumerative combinatorics.
We first study monochromatic solutions to equations when integers are colored with finitely many colors in Chapter 2. By looking at subsets of {1, 2, . . . , n} whose least common multiple is small, we improved a result of Brown and Rödl on the smallest integer n such that every 2-coloring of {1, 2, . . . , n} has a monochromatic solution to equations with unit fractions. Using a recent result of Boza, …
Building Blocks For W-Algebras Of Classical Types, Vladimir Kovalchuk
Building Blocks For W-Algebras Of Classical Types, Vladimir Kovalchuk
Electronic Theses and Dissertations
The universal 2-parameter vertex algebra W∞ of type W(2, 3, 4; . . . ) serves as a classifying object for vertex algebras of type W(2, 3, . . . ,N) for some N in the sense that under mild hypothesis, all such vertex algebras arise as quotients of W∞. There is an ℕ X ℕ family of such 1-parameter vertex algebras known as Y-algebras. They were introduced by Gaiotto and Rapčák are expected to be building blocks for all W-algebras in type A, i.e, every W-(super) algebra in …
Unilinear Residuated Lattices, Xiao Zhuang
Unilinear Residuated Lattices, Xiao Zhuang
Electronic Theses and Dissertations
We characterize all residuated lattices that have height equal to 3 and show that the variety they generate has continuum-many subvarieties. More generally, we study unilinear residuated lattices: their lattice is a union of disjoint incomparable chains, with bounds added. We give the characterization of all unilinear residuated lattices. By presenting the constructions and axiomatizations for different classes of unilinear residuated lattices, we conclude that the study of unilinear residuated lattices can be reduced to the study of the ⊤-unital ones. Using the classification of unilinear residuated lattices, the idempotent unilinear residuated lattices are studied and amalgamation property and strong …
Local-Global Results On Discrete Structures, Alexander Lewis Stevens
Local-Global Results On Discrete Structures, Alexander Lewis Stevens
Electronic Theses and Dissertations
Local-global arguments, or those which glean global insights from local information, are central ideas in many areas of mathematics and computer science. For instance, in computer science a greedy algorithm makes locally optimal choices that are guaranteed to be consistent with a globally optimal solution. On the mathematical end, global information on Riemannian manifolds is often implied by (local) curvature lower bounds. Discrete notions of graph curvature have recently emerged, allowing ideas pioneered in Riemannian geometry to be extended to the discrete setting. Bakry- Émery curvature has been one such successful notion of curvature. In this thesis we use combinatorial …
Local Finiteness And Automorphism Groups Of Low Complexity Subshifts, Ronnie Pavlov, Scott Schmieding
Local Finiteness And Automorphism Groups Of Low Complexity Subshifts, Ronnie Pavlov, Scott Schmieding
Mathematics: Faculty Scholarship
We prove that for any transitive subshift X with word complexity function cn(X), if lim inf(log(cn(X)/n)/(log log log n)) = 0, then the quotient group Aut(X, σ)/〈 σ〉 of the automorphism group of X by the subgroup generated by the shift σ is locally finite. We prove that significantly weaker upper bounds on cn(X) imply the same conclusion if the gap conjecture from geometric group theory is true. Our proofs rely on a general upper bound for the number of automorphisms of X of range n in terms of word complexity, which may be …
Exponential Random Graphs And A Generalization Of Parking Functions, Ryan Demuse
Exponential Random Graphs And A Generalization Of Parking Functions, Ryan Demuse
Electronic Theses and Dissertations
Random graphs are a powerful tool in the analysis of modern networks. Exponential random graph models provide a framework that allows one to encode desirable subgraph features directly into the probability measure. Using the theory of graph limits pioneered by Borgs et. al. as a foundation, we build upon the work of Chatterjee & Diaconis and Radin & Yin. We add complexity to the previously studied models by considering exponential random graph models with edge-weights coming from a generic distribution satisfying mild assumptions. In particular, we show that a large family of two-parameter, edge-weighted exponential random graphs display a phase …
Discrepancy Inequalities In Graphs And Their Applications, Adam Purcilly
Discrepancy Inequalities In Graphs And Their Applications, Adam Purcilly
Electronic Theses and Dissertations
Spectral graph theory, which is the use of eigenvalues of matrices associated with graphs, is a modern technique that has expanded our understanding of graphs and their structure. A particularly useful tool in spectral graph theory is the Expander Mixing Lemma, also known as the discrepancy inequality, which bounds the edge distribution between two sets based on the spectral gap. More specifically, it states that a small spectral gap of a graph implies that the edge distribution is close to random. This dissertation uses this tool to study two problems in extremal graph theory, then produces similar discrepancy inequalities based …