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Monte Carlo, fitting and Machine Learning for Tau leptons
by V. Cherepanov, E. Richter-Was, Z. Was
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Submission summary
Authors (as registered SciPost users): | Zbigniew Andrzej Was |
Submission information | |
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Preprint Link: | https://arxiv.org/abs/1811.03969v2 (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 | |
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Academic field: | Physics |
Specialties: |
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Approaches: | Theoretical, Computational |
Abstract
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
List of changes
Changes, mostly reformulation of the content with slight change of accent are in Sections 1, 2 and 3
Current status:
Reports on this Submission
Report #1 by Anonymous (Referee 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
Strengths
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.
Weaknesses
None of importance.
Report
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.
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