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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

The renormalization of higher-dimensional operators in quantum field theory is essential for phenomenological analyses in particle physics, and plays a significant role in the study of critical phenomena. We present a framework for…

High Energy Physics - Phenomenology · Physics 2025-12-10 Guilherme Guedes , Jasper Roosmale Nepveu

The renormalization method based on the Taylor expansion for asymptotic analysis of differential equations is generalized to difference equations. The proposed renormalization method is based on the Newton-Maclaurin expansion. Several basic…

Classical Analysis and ODEs · Mathematics 2017-07-27 Cheng-shi Liu

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

The statistical mechanics characterization of a finite subsystem embedded in an infinite system is a fundamental question of quantum physics. Nevertheless, a full closed form { for all required entropic measures} does not exist in the…

Quantum Physics · Physics 2022-03-23 Eldad Bettelheim , Aditya Banerjee , Martin B. Plenio , Susana F. Huelga

Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the…

Computational Physics · Physics 2015-05-20 C. N. Gilbreth , Y. Alhassid

Explicit expressions, for efficient application in engineering practice, are derived for generalized displacements and stresses in simply supported multi-layered wide plates and beams subjected to steady-state thermal and mechanical…

Materials Science · Physics 2015-03-16 M. Pelassa , R. Massabo

This work presents a novel physics-informed deep learning based super-resolution framework to reconstruct high-resolution deformation fields from low-resolution counterparts, obtained from coarse mesh simulations or experiments. We leverage…

Machine Learning · Computer Science 2022-11-24 Rajat Arora

A method is described to probe high-scale physics in lower-energy experiments by employing sum rules in terms of renormalisation group invariants. The method is worked out in detail for the study of supersymmetry-breaking mechanisms in the…

High Energy Physics - Phenomenology · Physics 2012-11-06 Jamil Hetzel , Wim Beenakker

This article deals with the adaptive and approximative computation of the Lam\'e equations. The equations of linear elasticity are considered as boundary integral equations and solved in the setting of the boundary element method (BEM).…

Numerical Analysis · Mathematics 2022-05-11 Maximilian Bauer , Mario Bebendorf

A renormalization group (RG) analysis of the superconductive instability of an anisotropic fermionic system is developed at a finite temperature. The method appears a natural generalization of Shankar's approach to interacting fermions and…

Condensed Matter · Physics 2009-10-28 Fabio Siringo , Giuseppe G. N. Angilella , Renato Pucci

We develop the strong coupling quantum thermodynamics based on the solution of the exact master equation. We find that both the Hamiltonian and the temperature must be renormalized due to the system-reservoir couplings. With the…

Quantum Physics · Physics 2020-10-06 Wei-Ming Huang , Wei-Min Zhang

This Dissertation presents results of a thorough study of ultracold bosonic and fermionic gases in three-dimensional and quasi-one-dimensional systems. Although the analyses are carried out within various theoretical frameworks…

Quantum Gases · Physics 2014-12-16 G. E. Astrakharchik

Recently, deep learning has emerged as a promising tool for statistical downscaling, the set of methods for generating high-resolution climate fields from coarse low-resolution variables. Nevertheless, their ability to generalize to climate…

Machine Learning · Computer Science 2023-05-03 Jose González-Abad , Jorge Baño-Medina

The process of renormalization to eliminate divergences arising in quantum field theory is not uniquely defined; one can always perform a finite renormalization, rendering finite perturbative results ambiguous. The consequences of making…

High Energy Physics - Phenomenology · Physics 2019-01-24 D. G. C. McKeon , Chenguang Zhao

The Bayesian uncertainty quantification technique has become well established in turbulence modeling over the past few years. However, it is computationally expensive to construct a globally accurate surrogate model for Bayesian inference…

Data Analysis, Statistics and Probability · Physics 2022-03-16 Fanzhi Zeng , Wei Zhang , Jinping Li , Tianxin Zhang , Chao Yan

Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and…

Computational Engineering, Finance, and Science · Computer Science 2017-05-09 Timo Heister , Juliane Dannberg , Rene Gassmöller , Wolfgang Bangerth

We present a new exact renormalization approach for quantum lattice models leading to long-range interactions. The renormalization scheme is based on wavelets with an infinite support in such a way that the excitation spectrum at the fixed…

High Energy Physics - Theory · Physics 2019-09-04 Pascal Fries , Ignacio Reyes , Johanna Erdmenger , Haye Hinrichsen

Presented are several example quantum computing representations of quantum systems with a relativistic energy relation. Basic unitary representations of free Dirac particles and BCS superconductivity are given. Then, these are combined into…

Quantum Physics · Physics 2013-07-16 Jeffrey Yepez

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu