English
Related papers

Related papers: Renormalization group approach to the P versus NP …

200 papers

We show that the Renormalization Group formalism allows to compute with accuracy the zero temperature correlation functions and particle densities of quantum systems.

Quantum Physics · Physics 2009-11-06 Pierre Gosselin , Herve Mohrbach

Based on the Renormalization Group method, a reduction of non integrable multi-dimensional hamiltonian systems has been performed. The evolution equations for the slowly varying part of the angle-averaged phase space density, and for the…

Accelerator Physics · Physics 2008-11-26 Stephan I. Tzenov

We apply the functional renormalization group theory to the dynamics of first-order phase transitions and show that a potential with all odd-order terms can describe spinodal decomposition phenomena. We derive a momentum-dependent dynamic…

Statistical Mechanics · Physics 2011-11-09 Yantao Li , Fan Zhong

The renormalization group (RG) is a powerful theoretical framework developed to consistently transform the description of configurations of systems with many degrees of freedom, along with the associated model parameters and coupling…

Statistical Mechanics · Physics 2026-04-20 Andrea Gabrielli , Diego Garlaschelli , Subodh P. Patil , M. Ángeles Serrano

The complexity class NP of decision problems that can be solved nondeterministically in polynomial time is of great theoretical and practical importance where the notion of polynomial-time reductions between NP-problems is a key concept for…

Computational Complexity · Computer Science 2022-12-23 Hans-Jörg Kreowski , Sabine Kuske , Aaron Lye , Aljoscha Windhorst

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

Renormalization group method is applied to the study of vibrational energy transfer in protein molecule. An effective Lagrangian and associated equations of motion to describe the resonant energy transfer are analyzed in terms of the…

Biological Physics · Physics 2022-10-13 Shigenori Tanaka

This paper is the fifth in a series devoted to the development of a rigorous renormalisation group method applicable to lattice field theories containing boson and/or fermion fields, and comprises the core of the method. In the…

Mathematical Physics · Physics 2015-06-19 David C. Brydges , Gordon Slade

Functional renormalisation group approach is applied to a system of kaons with finite chemical potential. A set of approximate flow equations for the effective couplings is derived and solved. At high scale the system is found to be at the…

Nuclear Theory · Physics 2017-06-07 Boris Krippa

A so-called Renormalization Group (RG) analysis is performed in order to shed some light on why the density of prime numbers in $\Bbb N^*$ decreases like the single power of the inverse neperian logarithm.

Mathematical Physics · Physics 2007-05-23 A. Peterman

We show how the renormalons emerge from the renormalization group equation with a priori no reference to any Feynman diagrams. The proof is rather given by recasting the renormalization group equation as a resurgent equation studied in the…

High Energy Physics - Theory · Physics 2020-03-17 Jahmall Bersini , Alessio Maiezza , Juan Carlos Vasquez

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

Approximately 10 years ago, the method of renormalization-group symmetries entered the field of boundary value problems of classical mathematical physics, stemming from the concepts of functional self-similarity and of the Bogoliubov…

Mathematical Physics · Physics 2009-08-11 V. F. Kovalev , D. V. Shirkov

Functional conjugation methods are used to analyze the global structure of various renormalization group trajectories, and to gain insight into the interplay between continuous and discrete rescaling. With minimal assumptions, the methods…

High Energy Physics - Theory · Physics 2011-03-21 Thomas L. Curtright , Cosmas K. Zachos

The functional renormalisation group is employed to study the non-linear regime of late-time cosmic structure formation. This framework naturally allows for non-perturbative approximation schemes, usually guided by underlying symmetries or…

Cosmology and Nongalactic Astrophysics · Physics 2022-01-10 Alaric Erschfeld , Stefan Floerchinger

Two approaches to renormalization-group improvement are examined: the substitution of the solutions of running couplings, masses and fields into perturbatively computed quantities is compared with the systematic sum of all the leading log…

High Energy Physics - Theory · Physics 2008-11-26 F. A. Chishtie , V. Elias , R. B. Mann , D. G. C. McKeon , T. G. Steele

Renormalization group in the internal space consists of the gradual change of the coupling constants. Functional evolution equations corresponding to the change of the mass or the coupling constant are presented in the framework of a scalar…

High Energy Physics - Theory · Physics 2009-11-10 J. Polonyi , K. Sailer

General prescriptions of differential renormalization are presented. It is shown that renormalization group functions are straightforwardly expressed through some constants that naturally arise within this approach. The status of the action…

High Energy Physics - Theory · Physics 2009-10-28 V. A. Smirnov

We construct a general renormalization group transformation on quantum states, independent of any Hamiltonian dynamics of the system. We illustrate this procedure for translational invariant matrix product states in one dimension and show…

Quantum Physics · Physics 2009-11-10 F. Verstraete , J. I. Cirac , J. I. Latorre , E. Rico , M. M. Wolf

We introduce a factor analysis model that summarizes the dependencies between observed variable groups, instead of dependencies between individual variables as standard factor analysis does. A group may correspond to one view of the same…

Machine Learning · Statistics 2014-11-19 Seppo Virtanen , Arto Klami , Suleiman A. Khan , Samuel Kaski