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Optimization-based Bayesian sensitivity on neutrino mass and constraints on cosmology with the KATRIN experiment

Hickford, Stephanie; Köllenberger, Leonard ORCID iD icon 1; Xu, Weiran
1 Institut für Astroteilchenphysik (IAP), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

The Karlsruhe Tritium Neutrino (KATRIN) experiment has pushed the direct bound of the neutrino mass down to sub-eV level in their first two scientific campaigns. The upcoming data release using a frequentist approach which includes the most recent three measurement campaigns is currently in preparation.

A comprehensive Bayesian analysis provides an alternative interpretation for the prior information and the neutrino mass results. Performing Bayesian sampling is computationally intensive and challenging when including all the systematic uncertainties, e.g. for the shifted analyzing plane configuration of the main spectrometer. New methods to optimize the model calculation will be presented, together with the Bayesian sensitivity for KATRIN's first five measurement campaigns. Constraints on cosmological models with the released data will also be presented within the Bayesian framework.


Zugehörige Institution(en) am KIT Institut für Astroteilchenphysik (IAP)
Publikationstyp Vortrag
Publikationsdatum 23.03.2023
Sprache Englisch
Identifikator KITopen-ID: 1000156024
HGF-Programm 51.13.01 (POF IV, LK 01) Neutrinophysik und Dunkle Materie
Veranstaltung 86th Jahrestagung der DPG und DPG-Frühjahrstagung der Sektion Materie und Kosmos - Arbeitskreis Beschleunigerphysik (SMuK 2023), Dresden, Deutschland, 20.03.2023 – 24.03.2023
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