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The detailed analysis of the global structure of the renormalization-group (RG) flow diagram for a model with isotropic and cubic interactions is carried out in the framework of the massive field theory directly in three dimensions (3D)…

Statistical Mechanics · Physics 2008-12-18 Konstantin Varnashev

The global clustering coefficient serves as a powerful metric for the structural analysis and comparison of complex networks. Random geometric graphs offer a realistic framework for representing the spatial constraints and geometry often…

Statistics Theory · Mathematics 2026-02-23 Mingao Yuan , Md. Niamul Islam Sium

We propose a cross-order Laplacian renormalization group (X-LRG) scheme for arbitrary higher-order networks. The renormalization group is a pillar of the theory of scaling, scale-invariance, and universality in physics. An RG scheme based…

Statistical Mechanics · Physics 2024-02-07 Marco Nurisso , Marta Morandini , Maxime Lucas , Francesco Vaccarino , Tommaso Gili , Giovanni Petri

The Wilsonian renormalization group (RG) properties of the conformal factor of the metric are profoundly altered by the fact that it has a wrong-sign kinetic term. The result is a novel perturbative continuum limit for quantum gravity,…

High Energy Physics - Theory · Physics 2020-07-15 Alex Mitchell , Tim R. Morris

We analyze the renormalization-group (RG) flows of two effective Lagrangians, one for measurement induced transitions of monitored quantum systems and one for entanglement transitions in random tensor networks. These Lagrangians, previously…

Statistical Mechanics · Physics 2024-09-20 Adam Nahum , Kay Joerg Wiese

Reentrant computation-recursive self-coupling in which a network continuously reinjects and reinterprets its own internal state-plays a central role in biological cognition but remains poorly characterized in neural network architectures.…

Computational Physics · Physics 2025-12-23 Byung Gyu Chae

The renormalization group (RG) is an essential technique in statistical physics and quantum field theory, which considers scale-invariant properties of physical theories and how these theories' parameters change with scaling. Deep learning…

Statistical Mechanics · Physics 2023-08-23 Kelsie Taylor

A random algebraic graph is defined by a group $G$ with a uniform distribution over it and a connection $\sigma:G\longrightarrow[0,1]$ with expectation $p,$ satisfying $\sigma(g)=\sigma(g^{-1}).$ The random graph…

Probability · Mathematics 2023-05-10 Kiril Bangachev , Guy Bresler

We extend the Wilson renormalization group (RG) to supersymmetric theories. As this regularization scheme preserves supersymmetry, we exploit the superspace technique. To set up the formalism we first derive the RG flow for the massless…

High Energy Physics - Theory · Physics 2009-10-31 M. Bonini , F. Vian

We propose a generalization of the random matrix theory following the basic prescription of the recently suggested concept of superstatistics. Spectral characteristics of systems with mixed regular-chaotic dynamics are expressed as weighted…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

In this work we formulate the nonequilibrium dynamical renormalization group (ndRG). The ndRG represents a general renormalization-group scheme for the analytical description of the real-time dynamics of complex quantum many-body systems.…

Disordered Systems and Neural Networks · Physics 2015-09-08 Markus Heyl , Matthias Vojta

We propose a new real-space renormalization group transformation for dynamical triangulations. It is shown to preserve geometrical exponents such as the string susceptibility and Hausdorff dimension. We furthermore show evidence for a fixed…

High Energy Physics - Lattice · Physics 2009-10-28 G. Thorleifsson , S. Catterall

The renormalization group (RG) properties of quantum gravity are explored, using the vielbein and the spin connection as the fundamental field variables. The scale dependent effective action is required to be invariant both under space time…

High Energy Physics - Theory · Physics 2015-05-20 J. -E. Daum , M. Reuter

We review recent developments in the theory of renormalisation group flows in minimal models with boundaries. Among these, we discuss in particular the perturbative calculations of Recknagel et al, not only as a tool to predict the IR…

High Energy Physics - Theory · Physics 2007-05-23 K. Graham , I. Runkel , G. M. T. Watts

We present a renormalization-group (RG) flow argument for s-wave kaon condensation in dense nuclear-star matter predicted in chiral perturbation theory. It is shown that it is the {\it relevant} mass term together with {\it any} attractive…

High Energy Physics - Phenomenology · Physics 2009-10-28 Hyun Kyu Lee , Mannque Rho , Sang-Jin Sin

We study the ``renormalization group action'' induced by cycles of cosmic expansion and contraction, within the context of a family of stochastic dynamical laws for causal sets derived earlier. We find a line of fixed points corresponding…

General Relativity and Quantum Cosmology · Physics 2009-10-31 X. Martin , D. O'Connor , D. P. Rideout , R. D. Sorkin

The free energy of the Coulomb Gap problem is expanded as a set of Feynman diagrams, using the standard diagrammatic methods of perturbation theory. The gap in the one-particle density of states due to long-ranged interactions corresponds…

Condensed Matter · Physics 2018-05-09 S. R. Johnson , D. E. Khmelnitskii

We study of the effect of weak noise on critical one dimensional maps; that is, maps with a renormalization theory. We establish a one dimensional central limit theorem for weak noises and obtain Berry--Esseen estimates for the rate of this…

Dynamical Systems · Mathematics 2007-05-23 Oliver Diaz-Espinosa , Rafael de la Llave

A sum of lognormal random variables (RVs) appears in many problems of science and engineering. For example, it is invloved in computing the distribution of recevied signal and interference powers for radio channels subject to lognormal…

Signal Processing · Electrical Eng. & Systems 2024-05-16 Fredrik Berggren

The Renormalization Group (RG) is a set of methods that have been instrumental in tackling problems involving an infinite number of degrees of freedom. What all these methods have in common -- which is what explains their success -- is that…

Statistical Mechanics · Physics 2020-04-30 Pedro Pessoa , Ariel Caticha