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This lecture provides an introduction to the renormalisation group as applied to scattering of two nonrelativistic particles. As well as forming a framework for constructing effective theories of few-nucleon systems, these ideas also…

High Energy Physics - Phenomenology · Physics 2007-09-20 Michael C. Birse

Discrete amorphous materials are best described in terms of arbitrary networks which can be embedded in three dimensional space. Investigating the thermodynamic equilibrium as well as non-equilibrium behavior of such materials around second…

Statistical Mechanics · Physics 2013-12-10 Eser Aygun , Ayse Erzan

We study the renormalization group flow of higher derivative gravity, utilizing the functional renormalization group equation for the average action. Employing a recently proposed algorithm, termed the universal renormalization group…

High Energy Physics - Theory · Physics 2012-02-29 F. Saueressig , K. Groh , S. Rechenberger , O. Zanusso

In this talk methods for a rigorous control of the renormalization group (RG) flow of field theories are discussed. The RG equations involve the flow of an infinite number of local partition functions. By the method of exact beta-function…

High Energy Physics - Theory · Physics 2009-10-28 A. Pordt

The renormalization group method has been adapted to the analysis of the long-time behavior of non-linear partial differential equation and has demonstrated its power in the study of critical phenomena of gravitational collapse. In the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Osamu Iguchi , Akio Hosoya , Tatsuhiko Koike

We review the renormalization group method applied to non-equilibrium dynamics by tracing the way how the hydrodynamic equations can be derived as reduced dynamics of the Boltzmann equation as a typical example.

High Energy Physics - Phenomenology · Physics 2007-05-23 Teiji Kunihiro

Random noncommutative geometry can be seen as a Euclidean path-integral approach to the quantization of the theory defined by the Spectral Action in noncommutative geometry (NCG). With the aim of investigating phase transitions in random…

Mathematical Physics · Physics 2021-08-10 Carlos I. Perez-Sanchez

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 possible usefulness of the renormalization group method in Nuclear Physics is pointed out in this talk in the context of the nuclear multifragmentation. The presentation is rather superficial and sketchy, to indicate the main lines…

Nuclear Theory · Physics 2007-05-23 J. Polonyi

We present a simple proof of the all-order exponentiation of soft logarithmic corrections to hard processes in perturbative QCD. Our argument is based on proving that all large logs in the soft limit can be expressed in terms of a single…

High Energy Physics - Phenomenology · Physics 2010-04-05 Stefano Forte , Giovanni Ridolfi

In the modeling of complex biological systems, the use of power-law models (such as S-systems and GMA systems) often provides a remarkable accuracy over several orders of magnitude in concentrations, an unusually broad range not fully…

Biological Physics · Physics 2019-11-22 Benito Hernández-Bermejo

Various normalization layers have been proposed to help the training of neural networks. Group Normalization (GN) is one of the effective and attractive studies that achieved significant performances in the visual recognition task. Despite…

Computer Vision and Pattern Recognition · Computer Science 2022-07-06 Agus Gunawan , Xu Yin , Kang Zhang

We describe the generalization of Wilson's Numerical Renormalization Group method to quantum impurity models with a bosonic bath, providing a general non-perturbative approach to bosonic impurity models which can access exponentially small…

Statistical Mechanics · Physics 2007-05-23 Ralf Bulla , Ning-Hua Tong , Matthias Vojta

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 perturbative renormalization group(RG) equation is applied to resum divergent series of perturbative wave functions of quantum anharmonic oscillator. It is found that the resummed series gives the cumulant of the naive perturbation…

High Energy Physics - Theory · Physics 2009-09-25 Teiji Kunihiro

The renormalization group is a tool that allows one to obtain a reduced description of systems with many degrees of freedom while preserving the relevant features. In the case of quantum systems, in particular, one-dimensional systems…

Quantum Physics · Physics 2009-11-13 Jose Gaite

We consider a symmetric scalar theory with quartic coupling in 4-dimensions and compare the standard 2PI calculation with a modified version which uses a functional renormalization group method. The set of integral differential equations…

High Energy Physics - Phenomenology · Physics 2015-01-14 M. E. Carrington , Wei-Jie Fu , D. Pickering , J. W. Pulver

I show that an application of renormalization group arguments may lead to significant corrections to the vacuum decay rate for phase transitions in flat and curved space-time. It can also give some information regarding its dependence on…

High Energy Physics - Phenomenology · Physics 2008-11-26 D. Metaxas

In these lectures I discuss peculiarities of the critical behaviour of ``non-ideal'' systems as it is explained by the renormalization group approach. Examples considered here include account of the single-ion anisotropy, structural…

Statistical Mechanics · Physics 2007-05-23 Yu. Holovatch

Boolean circuit is a computational graph that consists of the dynamic directed graph structure and static functionality. The commonly used logic optimization and Boolean matching-based transformation can change the behavior of the Boolean…

Machine Learning · Computer Science 2024-11-19 Liwei Ni , Xinquan Li , Biwei Xie , Huawei Li
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