Model selection for amplitude analysis
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Williams_Model selection.pdf
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Author(s)
Guegan, Baptiste
Hardin, John Melvin
Williams, Mateo S.
Stevens, Justin
Date Issued
July 2015
Journal
Journal of Instrumentation
Publisher
IOP Publishing
Citation
Guegan, B.; Hardin, J.; Stevens, J. and Williams, M. “Model Selection for Amplitude Analysis.” Journal of Instrumentation 10, no. 09 (September 2015): P09002–P09002.
Version
Author's final manuscript
Abstract
Model complexity in amplitude analyses is often a priori under-constrained since the underlying theory permits a large number of possible amplitudes to contribute to most physical processes. The use of an overly complex model results in reduced predictive power and worse resolution on unknown parameters of interest. Therefore, it is common to reduce the complexity by removing from consideration some subset of the allowed amplitudes. This paper studies a method for limiting model complexity from the data sample itself through regularization during regression in the context of a multivariate (Dalitz-plot) analysis. The regularization technique applied greatly improves the performance. An outline of how to obtain the significance of a resonance in a multivariate amplitude analysis is also provided.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Laboratory for Nuclear Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1088/1748-0221/10/09/p09002
