Development of an algorithm for linear particle track reconstruction in SuperNEMO detector
- NázevTitle
- Development of an algorithm for linear particle track reconstruction in SuperNEMO detectorDevelopment of an algorithm for linear particle track reconstruction in SuperNEMO detector
- Druh výsledkuResult type
- Kvalifikační práceThesis
- AutořiAuthors
- T. Křižák
- Vedoucí, konzultanti, oponentiSupervisors, advisors, reviewers
- M. Macko
- Klíčová slovaKeywords
- Legendre transform, neutrinoless double beta decay, neutrino physics, SuperNEMO, track reconstruction
- Časopis / citaceJournal / citation
- 2023. Master Thesis. CTU IEAP. Underground Laboratory LSM.
- RokYear
- 2023
- JazykLanguage
- eng
- ZáznamyRecords
- ProjektProject
- Institucionální podpora na rozvoj výzkumné org.Institucionální podpora na rozvoj výzkumné org.; LSM-CZ III - Podzemní laboratoř LSM - účast České republiky - LM2023063 (2023–2026)LSM-CZ III - Podzemní laboratoř LSM - účast České republiky - LM2023063 (2023–2026)
- Citace ke staženíDownload citation
- TXT · BibTeX
AbstraktAbstract
The SuperNEMO experiment stands out in the field of neutrinoless double beta decay thanks to its unique tracko-calo design, which promises background rejection capabilities unmatched by other approaches. However, to reach its full potential, a powerful reconstruction algorithm is needed in order to detect the elusive decay. Withing the presented work, we have developed the first version of the reconstruction software based on the application of the Legendre transform. In the thesis we demonstrate its power and the opportunities for improvement.
The SuperNEMO experiment stands out in the field of neutrinoless double beta decay thanks to its unique tracko-calo design, which promises background rejection capabilities unmatched by other approaches. However, to reach its full potential, a powerful reconstruction algorithm is needed in order to detect the elusive decay. Withing the presented work, we have developed the first version of the reconstruction software based on the application of the Legendre transform. In the thesis we demonstrate its power and the opportunities for improvement.