%0 Generic
%A Albrecht, Conrad
%C Heidelberg, Germany
%D 2013
%F heidok:16240
%K Functional Renormalization, High Performance Computing, Quantum Statistical Physics, Strongly Correlated Systems, Non-Perturbative Methods in Quantum Field Theory
%R 10.11588/heidok.00016240
%T On a Numerical Framework for Functional Renormalization of Quantum Statistical Physics
%U https://archiv.ub.uni-heidelberg.de/volltextserver/16240/
%X The subject of this thesis intends to investigate and put forward the method of  functional renormalization within the field of quantum statistical physics. Our focus is on  a (generic) truncation scheme that is suited to flexibly resolve two important mathematical  objects of physical relevance: The (inverse) propagator and the effective potential, respectively.  In the former case our effort aims at a proper resolution of the momentum dependence  which is related to the particles dispersion relation. The effective potential contains valuable  thermodynamic information on e.g. the equation of state and the system’s phase diagram.  A main achievement related to our study is the implementation of a numerical library,  libfrg, which sets up a generic framework for high performance parallel computing in  conjunction with the method of functional renormalization. By licensing it under the GNU  GPL it is tailored to foster shared development by the community of scientists with research  focus on this branch of physics.