Speaker
Description
Abstract
PyPWA is a toolkit designed to fit (regression) parametric models to data and to generate distributions (simulation) according to a given model (function). PyPWA software has been written under the python ecosystem with the goal of performing Amplitude or Partial Wave Analysis (PWA) in nuclear and particle physics experiments. The aim of spectroscopy experiments is often the identification short lived (strongly interacting) resonances that have decayed to the observed multi-particle final states. The PyPWA toolkit is built from individual and mostly disjoint components that the user can arrange in a variety of ways. PyPWA can solve broad collection of problems. Users just need to provide a function (model), data and simulation in their preferred formats. PyPWA will provide tools for two basic components, Data Processing (read, write, splitting) and Analysis (simulation, fitting and prediction). It also provides various ways of speeding up calculations through multi-threading and the use of GPUs. The flexibility of PyPWA and its use of many standard packages make it an ideal tool for both new and experienced scientists wanting to perform fits of models to data. The examples provided with the code allow for a quick start and the user-friendly Python ecosystem comes with a large user base with a lot of support. We will briefly describe the general features of amplitude analysis and describe the PyPWA software philosophy, structure and use.
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