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2023:topics [2023/06/06 00:20]
emanuele.re_admin
2023:topics [2023/06/21 11:13]
gregor.kasieczka [Session 2]
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   * starting from state-of-the-art ML-taggers, estimate how much they are correlated to the physics in the measurements of substructure we already have. Discuss good procedures to best tune MC to describe ML-taggers. Discuss good procedures to estimate uncertainties on ML-taggers, given the physics understanding of various effects (an example is scale-variations,​ where our constraints from data are certainly stronger than the factor 2 variations in many cases, but sometimes the opposite).   * starting from state-of-the-art ML-taggers, estimate how much they are correlated to the physics in the measurements of substructure we already have. Discuss good procedures to best tune MC to describe ML-taggers. Discuss good procedures to estimate uncertainties on ML-taggers, given the physics understanding of various effects (an example is scale-variations,​ where our constraints from data are certainly stronger than the factor 2 variations in many cases, but sometimes the opposite).
   * take stock of how well most recent generator developments have improved description of multiple new measurements of substructure. (Followup from a previous Les Houches 2015 on q/​g-tagging)   * take stock of how well most recent generator developments have improved description of multiple new measurements of substructure. (Followup from a previous Les Houches 2015 on q/​g-tagging)
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 +**__Tools, Event Generators and Machine Learning:​__**
  
  
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 ==== Session 2 ==== ==== Session 2 ====
  
-....+**__Higgs:​__**
  
 +  * "​Precision":​
 +    * Trilinear and quadrilinear Higgs couplings
 +    * Lepton flavour violation in the Higgs sector
 +    * Constraining the CP structure of the Higgs couplings
 +    * Higgs and EFT
 +    * Characterizing Higgs boson production and decay
 +  * "​Novelties":​
 +    * Exotic decays of the 125 GeV Higgs boson
 +    * Additional Higgs bosons (low/high mass) - uncovered parameter space
 +    * Naturalness
 +       * Gaps in searches for traditional models (SUSY, compositness)
 +       * Searches for cosmological triggers (new Higgs bosons and v-like leptons)
 +       * Unexpected signatures of naturalness
  
----- 
  
-----+**__Machine Learning and Tools:​__** 
 +   * Model Agnostic Searches 
 +   * Likelihood Learning 
 +   * SMEFT progresses
  
2023/topics.txt · Last modified: 2023/06/22 16:06 by gregor.kasieczka