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The Similarity Renormalization Group (SRG) is a continuous series of unitary transformations that can be implemented as a flow equation. When the relative kinetic energy ($\Trel$) is used in the SRG generator, nuclear structure calculations…

Nuclear Theory · Physics 2011-03-22 K. A. Wendt , R. J. Furnstahl , R. J. Perry

Abridged abstract: Inert interactions between randomly moving entities and spatial disorder play a crucial role in quantifying the diffusive properties of a system. These interactions affect only the movement of the entities, and examples…

Statistical Mechanics · Physics 2022-09-20 Seeralan Sarvaharman , Luca Giuggioli

We study inflation as a "cosmic" renormalization-group flow. The flow, which encodes the dependence on the background metric, is described by a running coupling $\alpha $, which parametrizes the slow roll, a de Sitter free, analytic beta…

High Energy Physics - Theory · Physics 2021-11-02 Damiano Anselmi , Filippo Fruzza , Marco Piva

By following the conventional similarity renormalization group (SRG) expansion of the Dirac equation developed in [J.-Y. Guo, Phys. Rev. C \textbf{85}, 021302 (2012)], we work out the analytic expression of the ${1}/{M^4}$ order and verify…

Nuclear Theory · Physics 2019-05-23 Yixin Guo , Haozhao Liang

From bird flocks and fish schools to migrating cell sheets, collective motion is a ubiquitous biological phenomenon that inspires quantitative modeling through self-propelled particle (SPP) frameworks. Conventional SPP models prescribe…

Statistical Mechanics · Physics 2025-07-15 Y. Kikuchi , M. Iwamoto

We develop a theoretical approach to ``spontaneous stochasticity'' in classical dynamical systems that are nearly singular and weakly perturbed by noise. This phenomenon is associated to a breakdown in uniqueness of solutions for fixed…

Statistical Mechanics · Physics 2020-11-04 Gregory L. Eyink , Dmytro Bandak

Decoupling via the Similarity Renormalization Group (SRG) of low-energy nuclear physics from high-energy details of the nucleon-nucleon interaction is examined for two-body observables and few-body binding energies. The universal nature of…

Nuclear Theory · Physics 2008-11-26 E. D. Jurgenson , S. K. Bogner , R. J. Furnstahl , R. J. Perry

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for…

Statistical Mechanics · Physics 2021-05-10 N. Dupuis , L. Canet , A. Eichhorn , W. Metzner , J. M. Pawlowski , M. Tissier , N. Wschebor

These notes provide a concise introduction to important applications of the renormalization group (RG) in statistical physics. After reviewing the scaling approach and Ginzburg-Landau theory for critical phenomena, Wilson's momentum shell…

Statistical Mechanics · Physics 2015-03-19 Uwe C. Tauber

The low-lying spectra of atomic nuclei display diverse behaviors, for example rotational bands, which can be described phenomenologically by simple symmetry groups such as spatial SU(3). This leads to the idea of dynamical symmetry, where…

Nuclear Theory · Physics 2020-04-30 Calvin W. Johnson

We develop a renormalization group for weak Harris-marginal disorder in otherwise strongly interacting quantum critical theories, focusing on systems which have emergent conformal invariance. Using conformal perturbation theory, we argue…

High Energy Physics - Theory · Physics 2022-03-30 Koushik Ganesan , Andrew Lucas , Leo Radzihovsky

It is shown that exact renormalization group (RG) equations (including rescaling and field-renormalization) for respectively the scale-dependent full action $S[\phi,t]$ and the scale-dependent full effective action $\Gamma[\Phi,t]$ --in…

High Energy Physics - Theory · Physics 2014-05-06 C. Bervillier

A brief review of the interaction-round-a-face (IRF) density-matrix renormalization-group (DMRG) method. We have demonstrated the numerical superiority of IRF-DMRG method applied to SU(2) invariant quantum spin chains over the conventional…

Statistical Mechanics · Physics 2009-11-07 Tatsuaki Wada , Tomotoshi Nishino

The running of the non-minimal parameter (\xi) of the interaction of the real scalar field and scalar curvature is explored within the non-perturbative setting of the functional renormalization group (RG). We establish the RG flow in curved…

High Energy Physics - Theory · Physics 2015-05-08 Ilya L. Shapiro , Poliane M. Teixeira , Andreas Wipf

We study the scaling behaviors of the active model B+ using the functional renormalization group (FRG) approach, based on the nonequilibrium effective action formulated via the Martin-Siggia-Rose path-integral formalism. We derive the…

Statistical Mechanics · Physics 2026-01-28 Gergely Fejős , Zsolt Szép , Naoki Yamamoto

Quenched randomness can lead to robust non-equilibrium phases of matter in periodically driven (Floquet) systems. Analyzing transitions between such dynamical phases requires a method capable of treating the twin complexities of disorder…

Disordered Systems and Neural Networks · Physics 2018-11-12 William Berdanier , Michael Kolodrubetz , S. A. Parameswaran , Romain Vasseur

We show explicitly how the exact renormalization group equation of interacting vector models in the large N limit can be mapped into certain higher-spin equations of motion. The equations of motion are generalized to incorporate a…

High Energy Physics - Theory · Physics 2013-07-29 Leopoldo A. Pando Zayas , Cheng Peng

We studied the correlated quasi-one-dimensional systems by one-loop renormalization group techniques in weak coupling. In contrast to conventional g-ology approach, we formulate the theory in terms of bilinear currents and obtain all…

Strongly Correlated Electrons · Physics 2009-11-11 Ming-Shyang Chang , Wei Chen , Hsiu-Hau Lin

The recent inflow of empirical data about the collective behaviour of strongly correlated biological systems has brought field theory and the renormalization group into the biophysical arena. Experiments on bird flocks and insect swarms…

Statistical Mechanics · Physics 2021-09-09 Andrea Cavagna , Luca di Carlo , Irene Giardina , Tomas S. Grigera , Giulia Pisegna , Mattia Scandolo

In this paper, we present a hierarchical path planning framework called SG-RL (subgoal graphs-reinforcement learning), to plan rational paths for agents maneuvering in continuous and uncertain environments. By "rational", we mean (1)…

Artificial Intelligence · Computer Science 2019-04-05 Junjie Zeng , Long Qin , Yue Hu , Cong Hu , Quanjun Yin