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相关论文: Functional renormalization group of the non-linear…

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We study the non-perturbative renormalization group flow of the nonlinear O(N) sigma model in two and three spacetime dimensions using a scheme that combines an effective local Hybrid Monte Carlo update routine, blockspin transformations…

高能物理 - 格点 · 物理学 2015-06-18 Björn H. Wellegehausen , Daniel Körner , Andreas Wipf

A study of the renormalization group flow in the three-dimensional nonlinear O(N) sigma model using Monte Carlo Renormalization Group (MCRG) techniques is presented. To achieve this, we combine an improved blockspin transformation with the…

高能物理 - 格点 · 物理学 2013-10-31 Daniel Koerner , Bjoern H. Wellegehausen , Andreas Wipf

The flow equations of the Functional Renormalization Group are applied to the O(N)-symmetric scalar theory, for N=1 and N=4, in four Euclidean dimensions, d=4, to determine the effective potential and the renormalization function of the…

高能物理 - 理论 · 物理学 2015-06-05 Dario Zappalà

We study the renormalization group flow of $\mathbb{Z}_2$-invariant supersymmetric and non-supersymmetric scalar models in the local potential approximation using functional renormalization group methods. We focus our attention to the fixed…

高能物理 - 理论 · 物理学 2015-10-28 Tobias Hellwig , Andreas Wipf , Omar Zanusso

We demonstrate the power of a recently-proposed approximation scheme for the non-perturbative renormalization group that gives access to correlation functions over their full momentum range. We solve numerically the leading-order flow…

统计力学 · 物理学 2009-11-19 F. Benitez , J. -P. Blaizot , H. Chate , B. Delamotte , R. Mendez-Galain , N. Wschebor

We study the critical behavior and phase diagram of the $d$-dimensional random field O(N) model by means of the nonperturbative functional renormalization group approach presented in the preceding paper. We show that the dimensional…

统计力学 · 物理学 2011-07-20 Matthieu Tissier , Gilles Tarjus

We elaborate on a previous attempt to prove the irreversibility of the renormalization group flow above two dimensions. This involves the construction of a monotonically decreasing $c$-function using a spectral representation. The missing…

高能物理 - 理论 · 物理学 2009-10-22 Andrea Cappelli , José Ignacio Latorre , Xavier Vilasis-Cardona

In the present article we analyze Non-Perturbative Renormalization Group flow equations in the order phase of $\mathbb{Z}_2$ and $O(N)$ invariant scalar models in the derivative expansion approximation scheme. We first address the behavior…

统计力学 · 物理学 2016-11-02 Marcela Peláez , Nicolás Wschebor

Renormalization group flow equations for scalar lambda Phi^4 are generated using three classes of smooth smearing functions. Numerical results for the critical exponent nu in three dimensions are calculated by means of a truncated series…

高能物理 - 理论 · 物理学 2009-10-31 Sen-Ben Liao , Janos Polonyi , Michael Strickland

This is a lecture note on the renormalization group theory for field theory models based on the dimensional regularization method. We discuss the renormalization group approach to fundamental field theoretic models in low dimensions. We…

统计力学 · 物理学 2018-04-10 Takashi Yanagisawa

The renormalization group flow of an integrable two dimensional quantum field theory which contains unstable particles is investigated. The analysis is carried out for the Virasoro central charge and the conformal dimensions as a function…

高能物理 - 理论 · 物理学 2009-12-31 O. A. Castro-Alvaredo , A. Fring

In the framework of the functional renormalization group (FRG) we present a simple truncation scheme for the computation of real-time mesonic n-point functions, consistent with the derivative expansion of the effective action. Via analytic…

高能物理 - 唯象学 · 物理学 2014-03-19 Kazuhiko Kamikado , Nils Strodthoff , Lorenz von Smekal , Jochen Wambach

The novel functional dimensional regularization (FDR) scheme has proven capable of yielding results that are competitive with the state-of-the-art in the computation of critical exponents in $d=3$, while also reproducing those from the…

高能物理 - 理论 · 物理学 2026-04-30 P. Beretta , A. Codello

We review the theoretical description of the random field Ising and $O(N)$ models obtained from the functional renormalization group, either in its nonperturbative implementation or, in some limits, in perturbative implementations. The…

无序系统与神经网络 · 物理学 2020-04-22 Gilles Tarjus , Matthieu Tissier

We study the universal critical behaviour near weakly first-order phase transitions for a three-dimensional model of two coupled scalar fields -- the cubic anisotropy model. Renormalization-group techniques are employed within the formalism…

高能物理 - 理论 · 物理学 2009-10-30 N. Tetradis

Functional renormalization group equations are analytically continued from imaginary Matsubara frequencies to the real frequency axis. On the example of a scalar field with O(N) symmetry we discuss the analytic structure of the flowing…

高能物理 - 理论 · 物理学 2012-08-20 Stefan Floerchinger

We recalculate four-loop renormalization group functions in 2-dimensional nonlinear O(n) {\sigma}-model using coordinate-space method. The high accuracy of calculation allow us to find the analytical form of {\beta}- and {\gamma}-function…

高能物理 - 唯象学 · 物理学 2013-06-13 O. Veretin

We have developed a nonperturbative functional renormalization group approach for random field models and related disordered systems for which, due to the existence of many metastable states, conventional perturbation theory often fails.…

统计力学 · 物理学 2011-07-20 Gilles Tarjus , Matthieu Tissier

Working with scalar field theories, we discuss choices of regulator that, inserted in the functional renormalization group equation, reproduce the results of dimensional regularization at one and two loops. The resulting flow equations can…

高能物理 - 理论 · 物理学 2021-04-28 Alessio Baldazzi , Roberto Percacci , Luca Zambelli

We study the long-distance behavior of the O(N) model in the presence of random fields and random anisotropies correlated as ~1/x^{d-sigma} for large separation x using the functional renormalization group. We compute the fixed points and…

无序系统与神经网络 · 物理学 2009-11-13 Andrei A. Fedorenko , Florian Kühnel
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