Abstract
A holographic microscope captures interference patterns, or holograms, that encode three-dimensional (3-D) information about the object being viewed. Computation is essential to extract that 3-D information. By wrapping low-level scattering codes and taking advantage of Python's data analysis ecosystem, HoloPy makes it easy for experimentalists to use modern, sophisticated inference methods to analyze holograms. The resulting data can be used to understand how small particles or microorganisms move and interact. The project illustrates how computational tools can enable experimental methods and new experiments.
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