Analiza korelacija u relativističkom modelu srednjeg polja

master's thesis

• Title (english): Correlation analysis in a relativistic mean-field model
• Author: Ines Markulin
• Mentor: Tomislav Marketin (mentor)
• Committee member: Tomislav Marketin (predsjednik povjerenstva)
• Committee member: Nils Paar (član povjerenstva)
• Committee member: Matko Milin (član povjerenstva)
• Committee member: Davor Horvatić (član povjerenstva)
• Committee member: Mihael Makek (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Physics); Zagreb
• Defense date and country: 2017-02-28, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Physics

Abstract

Teorijska predviđanja nepreciznosti rezultata dobivenih nekim modelom postaju značajna u procjeni njihove valjanosti u slučaju nedostatka eksperimentalnih podataka kojim bi se provjerila uspješnost modela. No, često su te procjene nepreciznosti velike i potrebno ih je smanjiti poboljšanjem modela korelacijskom analizom. Zato se u ovom radu fokusiramo na teoriju funkcionala gustoće i standardni postupak za određivanje parametra modela pomoću X2-minimizacije. Ona se temelji na odabiru skupa precizno izmjerenih opservabli osnovnog stanja, te određivanju razlika između tih opservabli i vrijednosti za koje model predviđa minimizaciju. Dijagonalizacijom matrice drugih derivacija dobivamo korelacijske koeficijente koji nam pružaju mnoštvo informacija o korištenim parametrima i opservablama koje drugim pristupima nisu dostupne. Također, pronalaze opservable koje mogu pomoći u smanjivanju predviđenih nepreciznosti rezultata.

Abstract (english)

Theoretical uncertainties in the predictions of some models become necessary due to the lack of experimental data which are needed to verify the performance of the model. However, this theoretical errors are often large, so we have to reduce them using correlation analysis to improve model. Therefore, in this paper we focus on the density functional theory and standard procedure for determining the parameters of the model using the X2 -minimization. It is based on the selection of a set of precisely measured observables in ground state, and determining the difference between these observables and the values for which the model predicts minimization. Diagonalization matrix of second derivation gain correlation coefficients that are providing us with a wealth of information on the parameters and observables that other approaches don‘t have. Also, a theoretical estimate uncertainties become significant in assessing the validity of the results obtained from the model.

• Keywords: teorijska predviđanja nepreciznosti rezultata
• Language: croatian
• URN:NBN: urn:nbn:hr:217:530752
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2017-06-13 15:13:07