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Monte Carlo, fitting and Machine Learning for Tau leptons

by V. Cherepanov, E. Richter-Was, Z. Was

This is not the latest submitted version.

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Submission summary

Authors (as registered SciPost users): Zbigniew Andrzej Was
Submission information
Preprint Link:  (pdf)
Date submitted: 2018-11-27 01:00
Submitted by: Was, Zbigniew Andrzej
Submitted to: SciPost Physics Proceedings
Proceedings issue: The 15th International Workshop on Tau Lepton Physics (TAU2018)
Ontological classification
Academic field: Physics
  • High-Energy Physics - Phenomenology
Approaches: Theoretical, Computational


Status of tau lepton decay Monte Carlo generator TAUOLA, and its main recent applications are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care. Studies for H to tau tau; tau to hadrons indeed demonstrate that multi-dimensional nature of distributions is important and available for evaluation of observables where tau leptons are used to constrain experimental data. For that part of the presentation, use of the TAUOLA program for phenomenology of H and Z decays at LHC is discussed, in particular in the context of the Higgs boson parity measurements with the use of Machine Learning techniques. Some additions, relevant for QED lepton pair emission and electroweak corrections are mentioned as well.

Author comments upon resubmission

I have rewritten sections, following suggestions by the conference team.

List of changes

Changes, mostly reformulation of the content with slight change of accent are in Sections 1, 2 and 3

Current status:
Has been resubmitted

Reports on this Submission

Anonymous Report 1 on 2018-12-6 (Invited Report)

  • Cite as: Anonymous, Report on arXiv:1811.03969v2, delivered 2018-12-06, doi: 10.21468/SciPost.Report.710


Machine Learning approaches to measure the spin of the Z and H bosons and in particular the CP state of the Higgs boson are an exciting topic and a strong potential for the future.


None of importance.


The author discusses a very interesting approach to evaluate tau observables sensitive to the spin of the Z and H bosons and in particular to the CP state of the Higgs boson.
After a reminder of the existing tools used to simulate the tau decays at the LHC, the manuscript describes the state of the techniques to measure the Higgs boson CP.
Finally a Machine Learning approach is proposed to separate Scalar and Pseudoscalar hypotheses and performance of several configurations is presented.

Requested changes

1- Short list of changes sent to the author.

  • validity: high
  • significance: high
  • originality: top
  • clarity: high
  • formatting: excellent
  • grammar: good

Author:  Zbigniew Andrzej Was  on 2018-12-11  [id 368]

(in reply to Report 1 on 2018-12-06)

I have introduced changes and installed with update available from today at arxiv, it is v3 now

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