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We establish a correspondence between anomaly detection in high-noise regimes and the renormalization group flow of non-equilibrium field theories. We provide a physical grounding for this framework by proving that the detection of phase…

Statistical Mechanics · Physics 2026-05-25 Riccardo Finotello , Vincent Lahoche , Parham Radpay , Dine Ousmane Samary

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

Complex quantum systems are often multiscale in nature with strong interactions between different scales. We present a novel idea: iteratively suppressing, rather than tracing out, the fast, high-energy degrees of freedom in strongly…

Quantum Physics · Physics 2026-05-01 Bing Gu

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

In many-body physics, renormalization techniques are used to extract aspects of a statistical or quantum state that are relevant at large scale, or for low energy experiments. Recent works have proposed that these features can be formally…

Machine Learning · Computer Science 2018-12-20 Cédric Bény

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

Graph neural networks process information on graphs represented at a given resolution scale. We analyze the effect of using different coarse-grained graph resolutions, obtained through the Laplacian renormalization group theory, on node…

Machine Learning · Computer Science 2025-04-15 Francesco Caso , Giovanni Trappolini , Andrea Bacciu , Pietro Liò , Fabrizio Silvestri

We establish the functional Renormalization Group as an exploratory tool to investigate a possible phase transition between a pre-geometric discrete phase and a geometric continuum phase in quantum gravity. In this paper, based on the…

General Relativity and Quantum Cosmology · Physics 2014-12-03 Astrid Eichhorn , Tim Koslowski

We study the critical behaviour of a model with non-dissipative couplings aimed at describing the collective behaviour of natural swarms, using the dynamical renormalization group. At one loop, we find a crossover between a conservative yet…

Statistical Mechanics · Physics 2020-01-01 Andrea Cavagna , Luca Di Carlo , Irene Giardina , Luca Grandinetti , Tomas S. Grigera , Giulia Pisegna

Motivated by experimental observations of patterning at the leading edge of motile eukaryotic cells, we introduce a general model for the dynamics of nearly-flat fluid membranes driven from within by an ensemble of activators. We include,…

Statistical Mechanics · Physics 2022-02-09 Francesco Cagnetta , Viktor Skultety , Martin R. Evans , Davide Marenduzzo

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

We study the surface critical behavior of semi-infinite systems belonging to the bulk universality class of the Ising model. Special attention is paid to the local behavior of experimentally relevant quantities such as the order parameter…

Condensed Matter · Physics 2009-10-28 A. Ciach , U. Ritschel

Critical behaviour of a fluid, subjected to strongly anisotropic turbulent mixing, is studied by means of the field theoretic renormalization group. As a simplified model, relaxational stochastic dynamics of a non-conserved scalar order…

Statistical Mechanics · Physics 2008-11-26 N. V. Antonov , A. A. Ignatieva

Background: Current neuronal monitoring techniques, such as calcium imaging and multi-electrode arrays, enable recordings of spiking activity from hundreds of neurons simultaneously. Of primary importance in systems neuroscience is the…

Neurons and Cognition · Quantitative Biology 2014-11-11 Yazan N. Billeh , Michael T. Schaub , Costas A. Anastassiou , Mauricio Barahona , Christof Koch

Renormalization group theory is a powerful and intriguing technique with a wide range of applications. One of the main successes of renormalization group theory is the description of continuous phase transitions and the development of…

Statistical Mechanics · Physics 2025-02-04 Luca Di Carlo

The critical region of the two flavour quark-meson model with vector interactions is explored using the Functional Renormalization Group technique, a non-perturbative method that takes into account quantum and thermal fluctuations. Special…

High Energy Physics - Phenomenology · Physics 2020-09-09 Renan Câmara Pereira , Rainer Stiele , Pedro Costa

Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These…

Disordered Systems and Neural Networks · Physics 2022-05-04 Lorenzo Tiberi , Jonas Stapmanns , Tobias Kühn , Thomas Luu , David Dahmen , Moritz Helias

We present an extension of the so-called cumulant crossing method which is used for determination of critical point in Monte Carlo simulations.The new method uses linear combination of several different order-parameter moments and almost…

Condensed Matter · Physics 2007-05-23 M. Itakura

This paper contains an analysis of a simple neural network that exhibits self-organized criticality. Such criticality follows from the combination of a simple neural network with an excitatory feedback loop that generates bistability, in…

Neurons and Cognition · Quantitative Biology 2015-06-11 J D Cowan , J Neuman , W van Drongelen

We give a pedagogical introduction into the functional renormalization group treatment of disordered systems. After a review of its phenomenology, we show why in the context of disordered systems a functional renormalization group treatment…

Disordered Systems and Neural Networks · Physics 2008-02-09 Kay Joerg Wiese , Pierre Le Doussal
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