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Abstract <p>For the process of single top quark production within the ‘‘simplified model’’ with a scalar dark matter mediator, a new variable based on angular correlations was presented, for the proper reconstruction of which it is necessary to separate the contributions of two undetectable particles: the neutrino and the mediator. In this work, various machine learning approaches for reconstructing the momenta of these particles are analyzed. A comparison is made between the results obtained using a multilayer perceptron and the Normalizing Flows architectures. The neural networks based on Normalizing Flows, presented in this work, demonstrate a high quality of reconstruction of the target variable and can be used for collider data analysis when applying the unfolding procedure to restore parton-level correlations.</p>

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Reconstruction of Angular Correlations in Associated Top Quark and Dark Matter Mediator Production

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • E. Abasov,
  • L. Dudko,
  • E. Iudin,
  • A. Markina,
  • P. Volkov,
  • G. Vorotnikov,
  • M. Perfilov,
  • A. Zaborenko

摘要

Abstract

For the process of single top quark production within the ‘‘simplified model’’ with a scalar dark matter mediator, a new variable based on angular correlations was presented, for the proper reconstruction of which it is necessary to separate the contributions of two undetectable particles: the neutrino and the mediator. In this work, various machine learning approaches for reconstructing the momenta of these particles are analyzed. A comparison is made between the results obtained using a multilayer perceptron and the Normalizing Flows architectures. The neural networks based on Normalizing Flows, presented in this work, demonstrate a high quality of reconstruction of the target variable and can be used for collider data analysis when applying the unfolding procedure to restore parton-level correlations.