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 mixing parameters x and y in a time-dependent amplitude analysis of the decay D0 → K+π−π+π−. Studying a sample of 50 000 events and setting the central values to the world average of x = (0.49 ± 0.15)% and y = (0.61 ± 0.08)%, the statistical sensitivities of x and y are determined to be σ(x) = 0.019 % and σ(y) = 0.019 %.

Highlights

  • 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

  • In physics analyses it is common to fit a theoretical model to observed data to extract parameters of interest

  • The GooFit [1,2,3] framework has been designed to address this issue by allowing such computations to be performed in parallel. It is built upon the Thrust library [4] to be able to run on different parallel architectures, while maintaining a control flow similar to the RooFit package [5], which is commonly used in high energy physics to fit theoretical models to data, and which only runs on CPUs

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Summary

Introduction

In physics analyses it is common to fit a theoretical model to observed data to extract parameters of interest. 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. This extension is employed to study the sensitivity on the D0 − D0 mixing parameters x and y in a time-dependent amplitude analysis of the decay D0 → K+π−π+π− .

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