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We revisit the critical behavior of classical frustrated systems using the nonperturbative renormalization group (NPRG) equation. Our study is performed within the local potential approximation of this equation to which is added the flow of…

Statistical Mechanics · Physics 2025-01-09 Shunsuke Yabunaka , Bertrand Delamotte

We consider formulations of the functional renormaliztion-group flow for correlated electronic systems, having the dynamical mean-field theory as a starting point. We classify the corresponding renormalization-group schemes into those…

Strongly Correlated Electrons · Physics 2015-08-04 A. A. Katanin

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of time-dependent DMRG from the usual situation of hermitian Hamiltonian matrices to…

We present a theoretical analysis of the properties of low-dimensional quantum antiferromagnets in applied magnetic fields. In a nonlinear sigma model description, we use a spin stiffness analysis, a 1/N expansion, and a renormalization…

Strongly Correlated Electrons · Physics 2017-09-27 B. Normand , Jordan Kyriakidis , Daniel Loss

The Functional Renormalisation Group approach is applied the imbalanced many-fermion systems. The system is found to exhibit the first order phase transition from the superfluid to normal phase when the density (chemical potential) mismatch…

Quantum Gases · Physics 2015-10-20 Boris Krippa

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite…

Mathematical Physics · Physics 2022-02-03 Joshua Feinberg , Roman Riser

We establish the functional Renormalization Group as an exploratory tool to investigate a possible phase transition between a pre-geometric discrete phase and a geometric continuum phase in quantum gravity. In this paper, based on the…

General Relativity and Quantum Cosmology · Physics 2014-12-03 Astrid Eichhorn , Tim Koslowski

Recently a quantum group deformation of EPRL spinfoam model was proposed in arXiv:1012.4216 by one of the authors, and in arXiv:1012.4784 by Fairbairn and Meusburger. It is interesting to study the high spin asymptotics of the quantum group…

General Relativity and Quantum Cosmology · Physics 2011-03-09 You Ding , Muxin Han

In paper I of this two-stage exposition, we introduced finite-range Coulomb gas (FRCG) models, and developed an integral-equation framework for their study. We obtained exact analytical results for $d = 0,1,2 $, where d denotes the range of…

Statistical Mechanics · Physics 2020-03-04 Avanish Kumar , Akhilesh Pandey , Sanjay Puri

We investigate a proposal to address several outstanding shortcomings of the perturbative Standard Model (SM) of particle physics. The appeal of this proposal is that these features are a manifestation of the non-perturbative sector of the…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. D. Bashford

Using the dynamical mean-field theory (DMFT) as a `booster-rocket', the functional renormalization group (fRG) can be upgraded from a weak-coupling method to a powerful computation tool for strongly interacting fermion systems. The strong…

Strongly Correlated Electrons · Physics 2019-03-13 Demetrio Vilardi , Ciro Taranto , Walter Metzner

Density matrix renormalization group (DMRG) is one of the most powerful numerical methods available for many-body systems. In this work, we develop a perturbation theory of DMRG (PT-DMRG) to largely increase its accuracy in an extremely…

Strongly Correlated Electrons · Physics 2017-03-01 Emanuele Tirrito , Shi-Ju Ran , Andrew J. Ferris , Ian P. McCulloch , Maciej Lewenstein

We reformulate the density matrix renormalization group method (DMRG) in terms of a single block, instead of the standard left and right blocks used in the construction of the superblock. This version of the DMRG, which we call the puncture…

Condensed Matter · Physics 2009-10-31 M. A. Martin-Delgado , J. Rodriguez-Laguna , G. Sierra

Describing the emergence of phases of condensed matter is one of the central challenges in physics. For this purpose many numerical and analytical methods have been developed, each with their own strengths and limitations. The functional…

Strongly Correlated Electrons · Physics 2024-04-13 Jonas B. Profe , Dante M. Kennes

The product-wavefunction renormalization group method, which is a novel numerical renormalization group scheme proposed recently,is applied to one-dimensional quantum spin chains in a magnetic field. We draw the zero-temperature…

Statistical Mechanics · Physics 2009-10-30 Yasuhiro Hieida , Kouichi Okunishi , Yasuhiro Akutsu

We present a theory of frustrated, two-dimensional, quantum antiferromagnets in the vicinity of a quantum transition from a non-collinear, magnetically-ordered ground state to a quantum-disordered phase. Using a sigma-model for bosonic,…

Condensed Matter · Physics 2009-10-22 A. V. Chubukov , T. Senthil , S. Sachdev

The favored phase field method (PFM) has encountered challenges in the finite strain fracture modeling of nearly or truly incompressible hyperelastic materials. We identified that the underlying cause lies in the innate contradiction…

Numerical Analysis · Mathematics 2022-05-04 Fucheng Tian , Jun Zeng , Mengnan Zhang , Liangbin Li

The functional renormalization group (FRG) provides a flexible tool to study correlations in low-dimensional electronic systems. In this paper, we present a novel FRG approach to the steady-state of quantum wires out of thermal equilibrium.…

Strongly Correlated Electrons · Physics 2020-12-08 Christian Klöckner , Dante Marvin Kennes , Christoph Karrasch

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamic and…

Strongly Correlated Electrons · Physics 2008-11-26 Karen Hallberg

Data driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning…

Machine Learning · Computer Science 2025-10-01 Erfan Hamdi , Emma Lejeune