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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…

Statistical Mechanics · Physics 2011-07-20 Matthieu Tissier , Gilles Tarjus

Optimization-based problems have become of great interest for signal approximation purposes, as they achieved good accuracy results while being extremely flexible and versatile. In this work, we put our focus on the context of periodic…

Optimization and Control · Mathematics 2021-11-30 Adrian Jarret

The functional renormalisation group (fRG) has evolved into a versatile tool in condensed matter theory for studying important aspects of correlated electron systems. Practical applications of the method often involve a high numerical…

Computational Physics · Physics 2016-09-21 Daniel Rohe

We present numerical renormalization group (NRG) calculations for a single-impurity Anderson model with a linear coupling to a local phonon mode. We calculate dynamical response functions, spectral densities, dynamic charge and spin…

Strongly Correlated Electrons · Physics 2009-11-07 A. Hewson , D. Meyer

The perturbation series for the renormalization group functions of the $O(N)-$symmetric $\phi^4$ field theory are divergent but asymptotic. They are usually followed by Resummation calculations to extract reliable results. Although the same…

High Energy Physics - Theory · Physics 2024-09-04 Abouzeid M. Shalaby

We study the limits of the energy resolution that can be achieved in the calculations of spectral functions of quantum impurity models using the numerical renormalization group (NRG) technique with interleaving (z-averaging). We show that…

Strongly Correlated Electrons · Physics 2009-03-05 Rok Zitko , Thomas Pruschke

We review current progress in the functional renormalization group treatment of disordered systems. After an elementary introduction into the phenomenology, we show why in the context of disordered systems a functional renormalization group…

Condensed Matter · Physics 2007-05-23 Kay Joerg Wiese

In this paper we study $L_2$-norm sampling discretization and sampling recovery of complex-valued functions in RKHS on $D \subset \R^d$ based on random function samples. We only assume the finite trace of the kernel (Hilbert-Schmidt…

Numerical Analysis · Mathematics 2021-05-03 Moritz Moeller , Tino Ullrich

The conventional absence of field renormalization in the local potential approximation (LPA) --implying a zero value of the critical exponent \eta -- is shown to be incompatible with the logic of the derivative expansion of the exact…

High Energy Physics - Theory · Physics 2013-09-25 C. Bervillier

Scalar field theories with $\mathbb{Z}_{2}$-symmetry are the traditional playground of critical phenomena. In this work these models are studied using functional renormalization group (FRG) equations at order $\partial^2$ of the derivative…

High Energy Physics - Theory · Physics 2018-08-01 N. Defenu , A. Codello

The fractional Laplacian $(-\Delta)^{\alpha/2}$ is a non-local operator which depends on the parameter $\alpha$ and recovers the usual Laplacian as $\alpha \to 2$. A numerical method for the fractional Laplacian is proposed, based on the…

Numerical Analysis · Mathematics 2014-11-14 Yanghong Huang , Adam Oberman

Approximation only by derivative (or more generally momentum) expansions, combined with reparametrization invariance, turns the continuous renormalization group for quantum field theory into a set of partial differential equations which at…

High Energy Physics - Theory · Physics 2011-04-15 Tim R. Morris

The renormalization group (RG) method is one of the singular perturbation methods which is used in search for asymptotic behavior of solutions of differential equations. In this article, time-independent vector fields and time (almost)…

Dynamical Systems · Mathematics 2015-05-14 Hayato Chiba

We introduce an equilibrium formulation of the functional renormalization group (fRG) for inhomogeneous systems capable of dealing with spatially finite-ranged interactions. In the general third order truncated form of fRG, the dependence…

Strongly Correlated Electrons · Physics 2017-01-17 Lukas Weidinger , Florian Bauer , Jan von Delft

We consider parameter estimation of ordinary differential equation (ODE) models from noisy observations. For this problem, one conventional approach is to fit numerical solutions (e.g., Euler, Runge--Kutta) of ODEs to data. However, such a…

Methodology · Statistics 2021-09-01 Takeru Matsuda , Yuto Miyatake

Practical diffusion sampling is a numerical approximation problem: under a fixed inference budget, one must simulate a reverse-time ODE or SDE using only a limited number of denoising steps, so discretization error is often the dominant…

Machine Learning · Computer Science 2026-05-12 Samuel Hurault , Thomas Moreau , Gabriel Peyré

We confirm the convergence of the derivative expansion in two supersymmetric models via the functional renormalization group method. Using pseudo-spectral methods, high-accuracy results for the lowest energies in supersymmetric quantum…

High Energy Physics - Theory · Physics 2015-06-22 Marianne Heilmann , Tobias Hellwig , Benjamin Knorr , Marcus Ansorg , Andreas Wipf

In this paper, we propose accurate and efficient finite difference methods to discretize the two- and three-dimensional fractional Laplacian $(-\Delta)^{\frac{\alpha}{2}}$ ($0 < \alpha < 2$) in hypersingular integral form. The proposed…

Numerical Analysis · Mathematics 2019-10-30 Siwei Duo , Yanzhi Zhang

Computable estimates for the error of finite element discretisations of parabolic problems in the $L^\infty(0,T; L^2)$ norm are developed, which exhibit constant effectivities (the ratio of the estimated error to the true error) with…

Numerical Analysis · Mathematics 2018-03-09 Oliver J. Sutton

Researchers have widely used exploratory factor analysis (EFA) to learn the latent structure underlying multivariate data. Rotation and regularised estimation are two classes of methods in EFA that they often use to find interpretable…

Methodology · Statistics 2023-02-01 Xinyi Liu , Gabriel Wallin , Yunxiao Chen , Irini Moustaki
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