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A field theoretic renormalization group method is presented which is capable of dealing with crossover problems associated with a change in the upper critical dimension. The method leads to flow functions for the parameters and coupling…

Condensed Matter · Physics 2015-06-25 Erwin Frey

The Polchinski exact renormalization group equation for a scalar field theory in arbitrary dimensions is translated, by means of a covariant Hamiltonian formalism, into a partial differential equation for an effective Hamiltonian density…

High Energy Physics - Theory · Physics 2015-11-02 Luca Zambelli

The Wilsonian exact renormalization group gives a natural framework in which ultraviolet and infrared divergences can be treated separately. In massless QED we introduce, as the only mass parameter, a renormalization scale $\L_R > 0$. We…

High Energy Physics - Theory · Physics 2009-10-30 M. Pernici , M. Raciti , F. Riva

We show how the exact renormalization group for the effective action with a sharp momentum cutoff, may be organised by expanding one-particle irreducible parts in terms of homogeneous functions of momenta of integer degree (Taylor…

High Energy Physics - Theory · Physics 2009-10-28 Tim R. Morris

We carry out a field-theoretical renormalization group procedure based on the Callan-Symanzik equation to calculate the detailed flow for the (multi) two-channel Kondo model and its compactified versions. In doing so, we go beyond the…

Strongly Correlated Electrons · Physics 2024-08-12 Aleksandar Ljepoja , C. J. Bolech , Nayana Shah

We use the renormalization group theory to study the directed bond percolation (Gribov process) near its second-order phase transition between absorbing and active state. We present a numerical calculation of the renormalization group…

Statistical Mechanics · Physics 2016-02-10 L. Ts. Adzhemyan , M. Hnatič , M. Kompaniets , T. Lučivjanský , L. Mižišin

We consider a functional relation between a given Wilsonian RG flow, which has to be related to a specific coarse-graining procedure, and an infinite family of (UV cutoff) scale dependent field redefinitions. Within this framework one can…

High Energy Physics - Theory · Physics 2020-03-03 Gian Paolo Vacca

The renormalization group functions are calculated in $D=4-\epsilon$ dimensions for the $\phi^4$-theory with two coupling constants associated with an ${O}(N)$-symmetric and a cubic interaction. Divergences are removed by minimal…

Condensed Matter · Physics 2009-10-28 H. Kleinert , V. Schulte-Frohlinde

We present a new method for renormalisation group improvement of the effective potential of a quantum field theory with an arbitrary number of scalar fields. The method amounts to solving the renormalisation group equation for the effective…

High Energy Physics - Phenomenology · Physics 2018-03-12 Leonardo Chataignier , Tomislav Prokopec , Michael G. Schmidt , Bogumila Swiezewska

We apply effective field theory (EFT) methods to compute the renormalization group improved effective potential for theories with a large mass hierarchy. Our method allows one to compute the effective potential in a systematic expansion in…

High Energy Physics - Phenomenology · Physics 2021-04-28 Aneesh V. Manohar , Emily Nardoni

The Wilsonian renormalisation group is applied to a system of two nonrelativistic particles interacting via short-range forces and coupled to an external EM field. By demanding that a fully off-shell one-particle-irreducible 5-point…

Nuclear Theory · Physics 2019-01-30 A. N. Kvinikhidze , M. C. Birse

We study the problem of the computation of the effective diffusion constant of a Brownian particle diffusing in a random potential which is given by a function $V(\phi)$ of a Gaussian field $\phi$. A self similar renormalization group…

Statistical Mechanics · Physics 2009-01-27 David S. Dean , Clement Touya

The exact or Wilson renormalization group equations can be formulated as a functional Fokker-Planck equation in the infinite-dimensional configuration space of a field theory, suggesting a stochastic process in the space of couplings.…

High Energy Physics - Theory · Physics 2008-11-26 Jose Gaite

We introduce a new family of tensorial field theories by coupling different fields in a non-trivial way, with a view towards the investigation of the coupling between matter and gravity in the quantum regime. As a first step, we consider…

High Energy Physics - Theory · Physics 2020-03-11 Vincent Lahoche , Dine Ousmane Samary , Antonio D. Pereira

We formulate a method of performing non-perturbative calculations in quantum field theory, based upon a derivative expansion of the exact renormalization group. We then proceed to apply this method to the calculation of critical exponents…

High Energy Physics - Theory · Physics 2007-05-23 Michael D. Turner

A new method, called the method of self-similar approximants, and its recent developments are described. The method is based on the ideas of renormalization group theory and optimal control theory. It allows for the effective extrapolation…

Mathematical Physics · Physics 2025-05-20 V. I. Yukalov , E. P. Yukalova

We present results for Wilson loops smoothed with the Yang-Mills gradient flow and matched through the scale $t_0$. They provide renormalized and precise operators allowing to test the $1/N^2$ scaling both at finite lattice spacing and in…

High Energy Physics - Lattice · Physics 2017-10-18 Miguel García Vera , Rainer Sommer

Renormalization-group (RG) flow equations have been derived for the generalized sine-Gordon model (GSGM) and the Coulomb gas (CG) in d >= 3 of dimensions by means of Wegner's and Houghton's, and by way of the real-space RG approaches. The…

High Energy Physics - Theory · Physics 2009-11-10 I. Nandori , U. D. Jentschura , K. Sailer , G. Soff

We investigate the influence of the momentum cutoff function on the field-dependent nonperturbative renormalization group flows for the three-dimensional Ising model, up to the second order of the derivative expansion. We show that, even…

High Energy Physics - Theory · Physics 2009-11-10 Léonie Canet

Normalizing flows are exact-likelihood generative neural networks which approximately transform samples from a simple prior distribution to samples of the probability distribution of interest. Recent work showed that such generative models…

Machine Learning · Statistics 2020-10-27 Jonas Köhler , Leon Klein , Frank Noé