2018-2019
https://dspace.carthage.edu/handle/20.500.13007/10659
Wed, 01 Dec 2021 10:16:09 GMT2021-12-01T10:16:09ZInfinite Snowman
https://dspace.carthage.edu/handle/20.500.13007/9552
Infinite Snowman
Montoya, Gladys
In this research paper we explore how to create an infinite snowman within an isosceles triangle to find the sum of its total area. Our main objective was to find the sum of the areas of the circles inscribed within the isosceles triangle.
Fri, 17 May 2019 00:00:00 GMThttps://dspace.carthage.edu/handle/20.500.13007/95522019-05-17T00:00:00ZMinimizing Transpositions in Permutations with Indistinct Variables
https://dspace.carthage.edu/handle/20.500.13007/9551
Minimizing Transpositions in Permutations with Indistinct Variables
Hussey, Mary
In any permutation within a symmetric group, the minimum number of transpositions required to return the permutation to the identity can be algorithmically determined. In fact, this algorithm determines this required number of transpositions based on the degree of the group and the cycle structure of the given permutation. This consistent property changes as the set acted upon by Sn becomes a multiset. In this paper, we explore how introducing these duplicates of some of the variables may reduce the required number of transpositions and determine the altered algorithm for this change in required number of transpositions. We find that this reduction is reliant on the number of indistinct variables for each unique variable, as well as the distribution of variables in the permutation and the cycles within the permutation. Since there are more intricacies to this algorithm than the base case of strictly unique variables, for any given cycle structure there are multiple possibilities of the required number of transpositions to return all variables to their original position.
Fri, 17 May 2019 00:00:00 GMThttps://dspace.carthage.edu/handle/20.500.13007/95512019-05-17T00:00:00ZMathematically Modeling the Josephson Junction
https://dspace.carthage.edu/handle/20.500.13007/9550
Mathematically Modeling the Josephson Junction
Fiege, Nathan
Josephson junctions are widely used in applications where a very precise voltage source is required, one example being metrology, where they are used to help define the values of several fundamental constants of nature. Modeling the Josephson junction furthers our understanding of the behavior of the junction which has had profound impacts in the metrological world. This junction and its voltage can be described by a nonlinear differential equation similar to that of the simple pendulum. Differential
equations of this type are difficult to understand and very difficult if not impossible to solve explicitly. After deriving this nonlinear differential equation using quantum mechanical arguments, the solutions are found independently using both analytical and numerical approaches. The qualitative behavior of solutions change at a critical current, resulting in either no voltage across the junction or voltage asymptotically approaching the classical Ohm's law. Further modeling of this system could include
modeling specific behaviors including the AC and DC Josephson effects.
Fri, 17 May 2019 00:00:00 GMThttps://dspace.carthage.edu/handle/20.500.13007/95502019-05-17T00:00:00ZReaction-Diffusion Equations and Biochemical Pattern Formation
https://dspace.carthage.edu/handle/20.500.13007/9549
Reaction-Diffusion Equations and Biochemical Pattern Formation
Bresnahan, Brady
Many biochemical reactions can be modeled using reaction-diffusion equations, some of which form patterns. Reaction-diffusion equations are partial differential equations that describe how the concentrations of two species change over time when subjected to diffusion and chemical reaction. Diffusion is represented in all cases by a first derivative with respect to time and a second derivative with respect to space. Chemical interactions are represented differently depending on the model, though they are typically described by nonlinear combinations of the dependent variables or concentrations. The two models explored here are the activator-substrate and the activator-inhibitor reaction-diffusion equations. We perform a stability analysis of each system and investigate solutions numerically under sinusoidal and random conditions with various parameters. The most interesting results come from the activator-inhibitor model under random conditions.
Fri, 17 May 2019 00:00:00 GMThttps://dspace.carthage.edu/handle/20.500.13007/95492019-05-17T00:00:00Z