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In this paper we discuss the effects of nontrivial boundary conditions or backgrounds, including non-perturbative ones, on the renormalization program for systems in two dimensions. Here we present an alternative renormalization procedure…

High Energy Physics - Theory · Physics 2008-11-26 Reza Moazzemi , Abdollah Mohammadi , Siamak S. Gousheh

We address the problems of computing operator norms of matrices induced by given norms on the argument and the image space. It is known that aside of a fistful of "solvable cases," most notably, the case when both given norms are Euclidean,…

Optimization and Control · Mathematics 2023-05-19 Anatoli Juditsky , Georgios Kotsalis , Arkadi Nemirovski

We study exact renormalization group equations in the framework of the effective average action. We present analytical approximate solutions for the scale dependence of the potential in a variety of models. These solutions display a rich…

High Energy Physics - Theory · Physics 2016-09-06 D. Litim , N. Tetradis

Variational regularisation is the primary method for solving inverse problems, and recently there has been considerable work leveraging deeply learned regularisation for enhanced performance. However, few results exist addressing the…

Optimization and Control · Mathematics 2024-06-18 Zakhar Shumaylov , Jeremy Budd , Subhadip Mukherjee , Carola-Bibiane Schönlieb

The reconstruction of an unknown quantity from noisy measurements is a mathematical problem relevant in most applied sciences, for example, in medical imaging, radar inverse scattering, or astronomy. This underlying mathematical problem is…

Optimization and Control · Mathematics 2025-10-14 Nina M. Gottschling , David Iagaru , Jakob Gawlikowski , Ioannis Sgouralis

Generalizing methods developed by Pinn, Pordt and Wieczerkowski for the hierarchical model with one component (N=1) and dimensions d between 2 and 4 we compute O(N)-symmetric fixed points of the hierarchical renormalization group equation…

Statistical Mechanics · Physics 2007-05-23 J. Goettker-Schnetmann

Guided by critical systems found in nature we develop a novel mechanism consisting of inhomogeneous polynomial regularisation via which we can induce scale invariance in deep learning systems. Technically, we map our deep learning (DL)…

Statistical Mechanics · Physics 2017-06-01 Dan Oprisa , Peter Toth

Within the exact renormalisation group, the scaling solutions for O(N) symmetric scalar field theories are studied to leading order in the derivative expansion. The Gaussian fixed point is examined for d>2 dimensions and arbitrary infrared…

High Energy Physics - Theory · Physics 2015-06-26 Daniel F. Litim

Within the framework of field-theoretical description of second-order phase transitions via the 3-dimensional O(N) vector model, accurate predictions for critical exponents can be obtained from (resummation of) the perturbative series of…

Statistical Mechanics · Physics 2011-02-16 Riccardo Guida , Paolo Ribeca

As a first application of our renormalisation group approach to non-local matrix models [hep-th/0305066], we prove (super-)renormalisability of Euclidean two-dimensional noncommutative \phi^4-theory. It is widely believed that this model is…

High Energy Physics - Theory · Physics 2016-09-06 Harald Grosse , Raimar Wulkenhaar

We establish a renormalization group approach which is implemented on the degrees of freedom defined by the overlap of two replicas to determine the critical fixed point and to extract four critical exponents for the phase transition of the…

Statistical Mechanics · Physics 2024-05-17 Dimitrios Bachtis

The multiscale entanglement renormalization ansatz is applied to the study of boundary critical phenomena. We compute averages of local operators as a function of the distance from the boundary and the surface contribution to the ground…

Quantum Physics · Physics 2015-05-14 P. Silvi , V. Giovannetti , P. Calabrese , G. E. Santoro , R. Fazio

We present a renormalization group (RG) approach to explain universal features of extreme statistics, applied here to independent, identically distributed variables. The outlines of the theory have been described in a previous Letter, the…

Statistical Mechanics · Physics 2015-05-18 G. Gyorgyi , N. R. Moloney , K. Ozogany , Z. Racz , M. Droz

The universality of renormalization group limit cycle behavior is illustrated with a simple discrete Hamiltonian model. A non-perturbative renormalization group equation for the model is soluble analytically at criticality and exhibits one…

Condensed Matter · Physics 2009-11-10 Stanislaw D. Glazek , Kenneth G. Wilson

We introduce a Renormalization scheme for the one and two dimensional Forest-Fire models in order to characterize the nature of the critical state and its scale invariant dynamics. We show the existence of a relevant scaling field…

Condensed Matter · Physics 2009-10-28 V. Loreto , L. Pietronero , A. Vespignani , S. Zapperi

In this paper a mode of using the Dynamic Renormalization Group (DRG) method is suggested in order to cope with inconsistent results obtained when applying it to a continuous family of one-dimensional nonlocal models. The key observation is…

Statistical Mechanics · Physics 2020-10-05 E. Katzav

We introduce a non-perturbative renormalization approach which identifies stable fixed points in any dimension for the Kardar-Parisi-Zhang dynamics of rough surfaces. The usual limitations of real space methods to deal with anisotropic…

Statistical Mechanics · Physics 2009-10-31 C. Castellano , M. Marsili , L. Pietronero

We study the period doubling renormalization operator for dynamics which present two coupled laminar regimes with two weakly expanding fixed points. We focus our analysis on the potential point of view, meaning we want to solve…

Dynamical Systems · Mathematics 2008-02-04 Alexandre Baraviera , Renaud Leplaideur , Artur O. Lopes

We develop a renormalization theory of non-perturbative dissipative H\'enon-like maps with combinatorics of bounded type. The main novelty of our approach is the incorporation of Pesin theoretic ideas to the renormalization method, which…

Dynamical Systems · Mathematics 2024-11-14 Jonguk Yang

In this paper, we develop efficient randomized algorithms for estimating probabilistic robustness margin and constructing robustness degradation curve for uncertain dynamic systems. One remarkable feature of these algorithms is their…

Optimization and Control · Mathematics 2008-05-13 Xinjia Chen , Kemin Zhou , Jorge L. Aravena