Changes for page Richard Williams
Last modified by Ricardo Julio Rodríguez Fernández on 2026/06/15 19:47
From version 11.1
edited by Ricardo Julio Rodríguez Fernández
on 2026/06/15 19:32
on 2026/06/15 19:32
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To version 10.1
edited by Ricardo Julio Rodríguez Fernández
on 2026/06/15 19:31
on 2026/06/15 19:31
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... ... @@ -1,6 +1,6 @@ 1 -=== Tau ReconstructionStrategiesat LHCb ===1 +=== Background Rejection in the Search for Λb⁰ → pKτ⁺τ⁻ at LHCb === 2 2 ==== Titor: [[María>>https://igfae.usc.es/igfae/persoa/vieites-diaz-maria/201/||target="_blank"]] Vieites Díaz ==== 3 3 ==== Supervisor: Richard Williams 4 4 ==== 5 5 6 - Raredecays involving tauleptonsarecurrentlyoneofthemostexcitingtopicsin particlephysics, astheyprovide auniqueopportunity touncoverhintsof physicsbeyondtheStandard Model. However, thereconstructionoftauleptonsisoneofthegreatestexperimentalchallengesin flavourphysics,sincetheirdecaysproduceneutrinosthatescapedetection,severely degrading theresolutionof key observables andincreasingbackground contamination.In thisproject, theselected studentwillstudy both leptonicand hadronic tau decaymodes,comparingtheirreconstructionperformance using simulated LHCb data. Advanced analysistechniques, including BoostedDecisionTrees, Neural Networks, and modernoptimisation tools,will be usedto maximisesignalsensitivityandidentifythe mostpromising strategy for future measurements withtauleptons in the final state.6 +The unobserved transition b → sττ is a promising probe to perform Lepton Flavour Universality tests and search for possible New Physics effects. In this project, the selected student will investigate signal and background characteristics in the decay Λb⁰ → pKτ⁺τ⁻ and develop strategies to maximize background rejection while preserving signal efficiency. The work will involve the use of modern machine-learning techniques, including BDTs, Neural Networks, and hyperparameter optimization tools such as Optuna, applied to realistic LHCb datasets.