Speaker
Description
NIFTy[1], a probabilistic programming framework developed for astrophysics,
has recently been adapted to be used in partial wave analyses (PWA) at the
COMPASS [2] experiment located in CERN. A non-parametric model, described
as a correlated field, is used to characterize kinematically-smooth complex-
binned amplitudes. Parametric models, like a Breit-Wigner distribution, can
also be mixed in. This method is being investigated for use in the GlueX ex-
periment located in Jefferson Lab.
I will introduce iftpwa[3], a flexible model-building framework that can
construct and interfere both parametric and non-parametric amplitudes. A
single configuration file is used to build a model and describe the optimiza-
tion procedure resulting in a variationally approximated posterior distribution.
This framework is designed to be modular which provides an avenue for inter-
collaboration use and development.
References
[1] G. Edenhofer, P. Frank, J. Roth, R. H. Leike, M. Guerdi, L. I. Scheel-Platz,
M. Guardiani, V. Eberle, M. Westerkamp, and T. A. Enßlin. Re-Envisioning
Numerical Information Field Theory (NIFTy.re): A Library for Gaussian
Processes and Variational Inference, 2024.
[2] F. M. Kaspar, J. Beckers, and J. Knollm ̈uller. Progress in the Partial-Wave
Analysis Methods at COMPASS. EPJ Web Conf., 291:02014, 2024.
[3] F. M. Kasper and L. Ng. iftpwa, 2024. Github Repository.
