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Related papers: On Group Averaging for SO(n,1)

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The study of quenched random systems is facilitated by the idea that the ensemble averages describe the thermal averages for any specific realization of the couplings, provided the system is large enough. Careful examination suggests that…

Statistical Mechanics · Physics 2018-09-19 Avishay Efrat , Moshe Schwartz

We discuss the following proposition: Renormalization Group flow of quantum theory with a biased symmetry exhibits a fixed hypersurface at which the symmetry is exact. Such emergent symmetries may have important phenomenological…

High Energy Physics - Theory · Physics 2024-06-21 Zurab Berezhiani , Maicol Di Giambattista , Alessio Maiezza , Archil Kobakhidze

In contrast to standard critical phenomena, disordered systems need to be treated via the Functional Renormalization Group. The latter leads to a coarse grained disorder landscape, which after a finite renormalization becomes non-analytic,…

Disordered Systems and Neural Networks · Physics 2009-11-18 Kay Joerg Wiese , Pierre Le Doussal

The renormalization group has played an important role in the physics of the second half of the twentieth century both as a conceptual and a calculational tool. In particular it provided the key ideas for the construction of a qualitative…

Condensed Matter · Physics 2009-10-31 Giovanni Jona-Lasinio

We generalized systematically the renormalized mean field theory in the case of uniform states to the unrestricted case of general inhomogeneous states with competing spin-, charge- and superconducting orders. Applying the theory to…

Superconductivity · Physics 2009-11-11 Qiang-Hua Wang , Z. D. Wang , Yan Chen , Fu-Chun Zhang

A real space Renormalization Group approach is presented for a non-mean field spin-glass. This approach has been conceived in the effort to develop an alternative method to the Renormalization Group approaches based on the replica method.…

Disordered Systems and Neural Networks · Physics 2014-09-09 Michele Castellana

An elementary introduction to perturbative renormalization and renormalization group is presented. No prior knowledge of field theory is necessary because we do not refer to a particular physical theory. We are thus able to disentangle what…

High Energy Physics - Theory · Physics 2015-06-26 B. Delamotte

Mesoscopic systems in a slowly fluctuating environment are often well described by superstatistical models. We develop a generalized statistical mechanics formalism for superstatistical systems, by mapping the superstatistical complex…

Statistical Mechanics · Physics 2015-05-19 Christian Beck

A class of exact infinitesimal renormalization group transformations is proposed and studied. These transformations are pure changes of variables (i.e., no integration or elimination of some degrees of freedom is required) such that a…

High Energy Physics - Theory · Physics 2017-11-08 Ariel Caticha

The motivation for this paper comes from the ongoing SARS-CoV-2 Pandemic. Its goal is to present a previously neglected approach to non-adaptive group testing and describes it in terms of residuated pairs on partially ordered sets. Our…

Other Statistics · Statistics 2022-02-15 Marcus Greferath , Cornelia Roessing

A recently proposed renormalization group technique, based on the hierarchical structures present in theories with fluctuating geometry, is implemented in the model of branched polymers. The renormalization group equations can be solved…

High Energy Physics - Lattice · Physics 2009-10-28 Jan Ambjorn , Piotr Bialas , Jerzy Jurkiewicz

Dynamic critical behavior in superfluid systems is considered in a presence of external stirring and advecting processes. The latter are generated by means of the Gaussian random velocity ensemble with white-noise character in time variable…

Statistical Mechanics · Physics 2020-08-19 Michal Dančo , Michal Hnatič , Tomáš Lučivjanský , Lukáš Mižišin

The main aim of this work is to present two different methodologies for configuration averaging in disordered systems. The Recursion method is suitable for the calculation of spatial or self-averaging, while the Augmented space formalism…

We consider distributed iterative algorithms for the averaging problem over time-varying topologies. Our focus is on the convergence time of such algorithms when complete (unquantized) information is available, and on the degradation of…

Optimization and Control · Mathematics 2009-01-14 Angelia Nedić , Alex Olshevsky , Asuman Ozdaglar , John Tsitsiklis

Physical systems differring in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the…

Disordered Systems and Neural Networks · Physics 2018-09-26 Maciej Koch-Janusz , Zohar Ringel

A popular setting in medical statistics is a group sequential trial with independent and identically distributed normal outcomes, in which interim analyses of the sum of the outcomes are performed. Based on a prescribed stopping rule, one…

Statistics Theory · Mathematics 2018-04-03 Ben Berckmoes , Anna Ivanova , Geert Molenberghs

In this work we present a new class of numerical semigroups called GSI-semigroups. We see the relations between them and others families of semigroups and we give explicitly their set of gaps. Moreover, an algorithm to obtain all the…

Commutative Algebra · Mathematics 2022-07-28 E. R. García Barroso , J. I. García-García , A. Vigneron-Tenorio

Let $X$ be a finite set such that $|X|=n$. Let $\trans$ and $\sym$ denote respectively the transformation monoid and the symmetric group on $n$ points. Given $a\in \trans\setminus \sym$, we say that a group $G\leq \sym$ is $a$-normalizing…

Group Theory · Mathematics 2012-10-05 João Araújo , Peter J. Cameron , James Mitchell , Max Neunhöffer

We introduce and analyze a new family of first-order optimization algorithms which generalizes and unifies both mirror descent and dual averaging. Within the framework of this family, we define new algorithms for constrained optimization…

Optimization and Control · Mathematics 2022-06-13 Anatoli Juditsky , Joon Kwon , Éric Moulines

Categorical regressor variables are usually handled by introducing a set of indicator variables, and imposing a linear constraint to ensure identifiability in the presence of an intercept, or equivalently, using one of various coding…

Computation · Statistics 2018-05-21 Felicitas J. Detmer , Martin Slawski