A Jupyter Notebook Based Tool for Building Skills in Computational Statistical Mechanics

Workshop: A Jupyter Notebook Based Tool for Building Skills in Computational Statistical Mechanics

Abstract: When learning about High-Performance Computing, almost of equal importance to developing computational skills is building an understanding of the applications and implications computational research can have. One field in which high-performance computing is particularly important is computational physics. Many physicists depend on high-performance hardware and software to carry out their research. This project describes an open-source, Jupyter notebook-based web app which helps students both develop skills relating to and appreciation for HPC techniques and builds understanding of complex physical models in the domain of thermodynamics/quantum field theory. This project is designed to help students understand, appreciate, and build skills relating to simulations of statistical systems, which are too complex to describe analytically and instead need to be described by complex monte-carlo simulations.

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