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We explore the possibilities of using the fermionic functional renormalization group to compute the phase diagram of systems with competing instabilities. In order to overcome the ubiquituous divergences encountered in RG flows, we propose…

Strongly Correlated Electrons · Physics 2009-11-30 M. Ossadnik , C. Honerkamp

We construct exact functional renormalization group (RG) flow equations for non-relativistic fermions in arbitrary dimensions, taking into account not only mode elimination but also the rescaling of the momenta, frequencies and the…

Strongly Correlated Electrons · Physics 2009-11-07 Peter Kopietz , Tom Busche

In order to find reliable and efficient numerical approximation schemes, we suggest to identify the Functional Renormalization Group flow equations of one-particle irreducible two-point functions as Hamilton-Jacobi(-Bellman)-type partial…

High Energy Physics - Theory · Physics 2025-12-30 Adrian Koenigstein , Martin J. Steil , Stefan Floerchinger

In this paper, we show how the finite formulation of QFT based on Callan-Symanzik equations can be generalised to the case of non-renormalizable theories. We derive an equation for effective action for an arbitrary single scalar field…

High Energy Physics - Theory · Physics 2025-04-10 Y. Ageeva , P. Petrov , M. Shaposhnikov

We study a new generating functional of one-particle irreducible diagrams in quantum field theory, called master functional, which is invariant under the most general perturbative changes of field variables. The usual functional Gamma does…

High Energy Physics - Theory · Physics 2016-04-06 Damiano Anselmi

A continuous sequence of infinitesimal unitary transformations is used to diagonalize the quantum sine-Gordon model for \beta^2\in(2\pi,\infty). This approach can be understood as an extension of perturbative scaling theory since it links…

Statistical Mechanics · Physics 2009-10-31 Stefan Kehrein

A continuous sequence of infinitesimal unitary transformations, combined with an operator product expansion for vertex operators, is used to diagonalize the quantum sine-Gordon model for 2 pi < beta^2 < infinity. The leading order of this…

Statistical Mechanics · Physics 2009-10-31 Stefan Kehrein

The freedom in choosing finite renormalizations in quantum field theories (QFT) is characterized by a set of parameters $\{c_i \}, i = 1 ..., n >...$, which specify the renormalization prescriptions used for the calculation of physical…

High Energy Physics - Theory · Physics 2009-01-07 A. Peterman

A novel general framework for the study of $\Gamma$-convergence of functionals defined over pairs of measures and energy-measures is introduced. This theory allows us to identify the $\Gamma$-limit of these kind of functionals by knowing…

Analysis of PDEs · Mathematics 2020-04-22 Marco Caroccia , Riccardo Cristoferi

We apply the functional renormalization group theory to the dynamics of first-order phase transitions and show that a potential with all odd-order terms can describe spinodal decomposition phenomena. We derive a momentum-dependent dynamic…

Statistical Mechanics · Physics 2011-11-09 Yantao Li , Fan Zhong

We adapt the precise definition of the flowing effective action in order to obtain a functional flow equation with simple properties close to physical intuition. The simplified flow equation is invariant under local gauge transformations…

High Energy Physics - Theory · Physics 2025-04-09 C. Wetterich

The functional renormalization group provides an efficient description of the interplay and competition of correlations on different energy scales in interacting Fermi systems. An exact hierarchy of flow equations yields the gradual…

Strongly Correlated Electrons · Physics 2008-10-06 Sabine Andergassen , Tilman Enss , Christoph Karrasch , Volker Meden

We present a new general method to construct an action functional for a non-potential field theory. The key idea relies on representing the governing equations of the theory relative to a diffeomorphic flow of curvilinear coordinates which…

Mathematical Physics · Physics 2015-03-19 Daniele Venturi

Within the real-time formulation of nonequilibrium field theory, generalized transport equations are derived avoiding the standard quasiparticle approximation. They permit to include unstable particles into the transport scheme. In order to…

Nuclear Theory · Physics 2011-07-19 Yu. B. Ivanov , J. Knoll , D. N. Voskresensky

We use a novel parameterization of the flowing Hamiltonian to show that the flow equations based on continuous unitary transformations, as proposed by Wegner, can be implemented through a nonlinear partial differential equation involving…

Other Condensed Matter · Physics 2015-06-24 J. N. Kriel , A. Y. Morozov , F. G. Scholtz

We study a class of Lorentz violating quantum field theories that contain higher space derivatives, but no higher time derivatives, and become renormalizable in the large N expansion. The fixed points of their renormalization-group flows…

High Energy Physics - Theory · Physics 2014-11-18 Damiano Anselmi

We investigate the renormalization group flows of multicomponent scalar theories with $U(1)$ gauge symmetry using the functional renormalization group method. The scalar sector is built up from traces of matrix fields that belong to simple,…

High Energy Physics - Phenomenology · Physics 2019-08-28 G. Fejos , T. Hatsuda

Sampling from high-dimensional and structured probability distributions is a fundamental challenge in computational physics, particularly in the context of lattice field theory (LFT), where generating field configurations efficiently is…

Quantum Physics · Physics 2026-02-10 Jehu Martinez , Andrea Delgado

We derive from first principles (without resorting to the replica trick) a density functional theory for fluids in quenched disordered matrices (QA-DFT). We show that the disorder-averaged free energy of the fluid is a functional of the…

Soft Condensed Matter · Physics 2007-07-18 Luis Lafuente , Jose A. Cuesta

We introduce a method for reconstructing an infinitesimal normalizing flow given only an infinitesimal change to a (possibly unnormalized) probability distribution. This reverses the conventional task of normalizing flows -- rather than…

Machine Learning · Statistics 2020-12-04 David Pfau , Danilo Rezende