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master's thesis
Primjena statističkog učenja na proširenu semi-empirijsku formulu mase
Zagreb: University of Zagreb, Faculty of Science, 2019. urn:nbn:hr:217:224872
Bezak, Mihaela
University of Zagreb
Faculty of Science
Department of Physics

Institutional repository: Repository of the Faculty of Science

Cite this document

Bezak, M. (2019). Primjena statističkog učenja na proširenu semi-empirijsku formulu mase (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:224872

Bezak, Mihaela. "Primjena statističkog učenja na proširenu semi-empirijsku formulu mase." Master's thesis, University of Zagreb, Faculty of Science, 2019. https://urn.nsk.hr/urn:nbn:hr:217:224872

Bezak, Mihaela. "Primjena statističkog učenja na proširenu semi-empirijsku formulu mase." Master's thesis, University of Zagreb, Faculty of Science, 2019. https://urn.nsk.hr/urn:nbn:hr:217:224872

Bezak, M. (2019). 'Primjena statističkog učenja na proširenu semi-empirijsku formulu mase', Master's thesis, University of Zagreb, Faculty of Science, accessed 26 November 2024, https://urn.nsk.hr/urn:nbn:hr:217:224872

Bezak M. Primjena statističkog učenja na proširenu semi-empirijsku formulu mase [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2019 [cited 2024 November 26] Available at: https://urn.nsk.hr/urn:nbn:hr:217:224872

M. Bezak, "Primjena statističkog učenja na proširenu semi-empirijsku formulu mase", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:217:224872

Metadata
TitlePrimjena statističkog učenja na proširenu semi-empirijsku formulu mase
Title (english)Application of statistical learning to expanded semi-empirical mass formula
AuthorMihaela Bezak
MentorNils Paar (mentor)
Committee memberNils Paar (predsjednik povjerenstva)
Committee memberMatko Milin (član povjerenstva)
Committee memberDavor Horvatić (član povjerenstva)
Committee memberTamara Nikšić (član povjerenstva)
Committee memberMihael Makek (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Physics)
Zagreb
Defense date and country2019-06-06, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Abstract
U nuklearnoj fizici već više od osamdeset godina u primjeni je Bethe–Weizsäcker formula mase (BW). BW formula sadrži osnovne elemente koji su dovoljni za kvantitativan opis energija vezanja. Unatoč postojanju modernih, mnogo kompleksnijih modela mase, zbog svoje jednostavnosti i intuitivne povezanosti s fizikom atomske jezgre BW formula je i dalje interesantna tema istraživanja. Motiv ovog rada je opisivanje karakteristika BW formule uporabom podataka izmjerenih energija vezanja. Metode statističkog učenja u tome predstavljaju vrlo efikasan alat koji može uvidjeti pravilnosti te značajnost pojedinih doprinosa. Dobiva se zanimljiv rezultat da najznačajniji doprinos energiji vezanja imaju osnovni članovi iz BW formule, dok novo pridodani članovi predstavljaju korekcije manjeg doprinosa na osnovnu formulu. Dodavanje novih članova sustavu opravdano je samo ako novo pridodan član sa sobom nosi novi fizikalni sadržaj, koji prethodno nije bio uključen u modelu. Povećavanjem kompleksnosti, povećavamo varijabilnost na štetu generalizacije što je prikazano pomoću train-test pogreške.
Abstract (english)
Bethe–Weizsäcker (BW) formula has been used by nuclear physicists for more than eighty years. The BW formula contains the basic terms sufficient for a quantitative description of nuclear binding energies. Although more modern and complex mass models exist, the BW formula is still widely used and studied due to its simplicity and intuitive connection with atomic physics. The aim of this thesis is to describe characteristics of the BW formula by using experimentally observed binding energies. Statistical learning methods are shown to be a very effective tool for identifying patterns and the weights of contributing terms. We come to conclusion that the most relevant contribution to binding energies comes from the basic terms of the BW formula, and any additional terms only give small corrections. Adding a new term to the system is only justified if it introduces physics ignored by the basic model. Adding complexity also increases variability at the expense of generalisation, as it is shown by the train-test error.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:224872
Study programmeTitle: Physics; specializations in: Research
Course: Research
Study programme type: university
Study level: integrated undergraduate and graduate
Academic / professional title: magistar/magistra fizike (magistar/magistra fizike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-09-05 11:28:49