The PyPWA Project aims to develop a software framework that can be used to perform parametric model fitting to data. In particular, Partial Wave and Amplitude Analysis (PWA) of multiparticle final states. PyPWA is designed for photoproduction experiments using linearly polarized photon beams. The software makes use of the resources at the JLab Scientific Computer Center (Linux farm). PyPWA extract model parameters from data by performing extended likelihood fits. Two versions of the software are develop: one where general amplitudes (or any parametric model) can be used in the fit and simulation of data, and a second where the framework starts with a specific realization of the Isobar model, including extensions to Deck-type and baryon vertices corrections.
Tutorials (Step-by-step instructions) leading to a full fit of data and the use of simulation software are included. Most of the code is in Python, but hybrid code (in Cython or Fortran) has been used when appropriate. Scripting to make use of vectorization and parallel coprocessors (Xeon-Phi and/or GPUs) are expected in the near future. The goal of this software framework is to create a user friendly environment for the spectroscopic analysis of linear polarized photoproduction experiments. The PyPWA Project software expects to be in a continue flow (of improvements!), therefore, please check on the more recent software download version.
What can PyPWA do?¶
Likelihood fitting with ChiSquared and Log Likelihood
Simulation using the Monte-Carlo Rejection Sampling method
Multi-variable binning for 4 vector particle data (in GAMP Format)
Convert and mask data between similar data types
Load data into an HDF5 dataset
Current PyPWA Staff
Previous PyPWA Staff
High School Interns
Ryan Wright HS
Ran Amplitude benchmarks on the XeonPhi
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