Home > Amplitude analysis of four-body decays using a massively-parallel fitting framework |
Published Articles | |
Report number | arXiv:1702.06735 |
Title | Amplitude analysis of four-body decays using a massively-parallel fitting framework |
Related title | Amplitude analysis of four-body decays using a massively-parallel fitting framework |
Author(s) | Hasse, C. (CERN ; Tech. U., Dortmund (main) ; Cincinnati U.) ; Albrecht, J. (Tech. U., Dortmund (main)) ; Alves, A.A. (Cincinnati U.) ; d'Argent, P. (Heidelberg U.) ; Evans, T.D. (Oxford U.) ; Rademacker, J. (Bristol U.) ; Sokoloff, M.D. (Cincinnati U.) |
Publication | 2017-11-20 |
Imprint | 2017-02-22 |
Number of pages | 7 |
Note | Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016 |
In: | J. Phys.: Conf. Ser. 898 (2017) 072016 |
In: | 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072016 |
DOI | 10.1088/1742-6596/898/7/072016 |
Subject category | physics.data-an ; Computing and Computers ; physics.comp-ph ; hep-ex ; Particle Physics - Experiment |
Abstract | The GooFit Framework is designed to perform maximum-likelihood fits for arbitrary functions on various parallel back ends, for example a GPU. We present an extension to GooFit which adds the functionality to perform time-dependent amplitude analyses of pseudoscalar mesons decaying into four pseudoscalar final states. Benchmarks of this functionality show a significant performance increase when utilizing a GPU compared to a CPU. Furthermore, this extension is employed to study the sensitivity on the $D^0 - \bar{D}^0$ mixing parameters $x$ and $y$ in a time-dependent amplitude analysis of the decay $D^0 \rightarrow K^+\pi^-\pi^+\pi^-$. Studying a sample of 50 000 events and setting the central values to the world average of $x = (0.49 \pm0.15) \%$ and $y = (0.61 \pm0.08) \%$, the statistical sensitivities of $x$ and $y$ are determined to be $\sigma(x) = 0.019 \%$ and $\sigma(y) = 0.019 \%$. |
Copyright/License | CC-BY-4.0 |