2022 Student Research Conference:
35th Annual Student Research Conference

A simulation of a one-dimensional discrete toy universe

Andrew R. McCandliss
Prof. Taner Edis, Faculty Mentor

Using a computer simulation, we studied a discrete circular one-dimensional space occupied by matter behaving according to simple probabilistic rules. Even this radically simplified, physically unrealistic toy model presented a series of programming challenges. Implementing the model requires new ways to define zeros and relationships between objects. Tracking the average location of objects in a periodic space with its own dynamics of growing and shrinking can be a difficult computation, particularly if any optimization for speed is required. We propose to handle these practical difficulties through built-in Python operators, an object-oriented approach, and methods written into the classes for movement in our space. Special handling of the positions was required for the expansion of the space, with multiple variables tracked over every position. I describe some of the programming details as an illustration of complications that can arise when developing even simple models that might exhibit physically interesting behaviors.

Keywords: statistical physics, computational physics


Presentation Type: Oral Presentation

Session: 307-4
Location: MG 1098
Time: 2:00

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