written by Jerome Fung and Lauri Wardell

The sophomore-level laboratory at Wellesley College emphasizes the development of data analysis and visualization skills. We use the Jupyter notebook computational environment, which combines code, output, and commentary into a single document. Here, we describe the experiment that introduces our students to nonlinear model fitting. Students translate a photodiode across a diffraction pattern to measure the spatial dependence of the pattern intensity, fit values predicted by the Fraunhofer approximation to their measured data, and determine parameters like the width of a diffracting slit with ? 0.5 µm precision. We discuss how Jupyter notebooks encourage data transparency and foster student sense-making.

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Last Modified January 17, 2019

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