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Inspired by the superblock method of White, we introduce a simple modification of the standard Renormalization Group (RG) technique for the study of quantum lattice systems. Our method which takes into account the effect of Boundary…

Statistical Mechanics · Physics 2009-10-28 A. Langari , V. Karimipour

Adaptive quantum circuits enhance flexibility and efficiency over traditional static circuits by dynamically adjusting their structure and parameters in real-time based on intermediate measurement outcomes. This paper introduces a novel…

Quantum Physics · Physics 2025-04-15 Waldemir Cambiucci , Regina Melo Silveira , Wilson Vicente Ruggiero

A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A…

Strongly Correlated Electrons · Physics 2010-04-20 Julian Rincon , D. J. Garcia , K. Hallberg

The family of Green's function methods based on the $GW$ approximation has gained popularity in the electronic structure theory thanks to its accuracy in weakly correlated systems combined with its cost-effectiveness. Despite this,…

Chemical Physics · Physics 2023-08-31 Antoine Marie , Pierre-François Loos

We present a new tensor network algorithm for calculating the partition function of interacting quantum field theories in 2 dimensions. It is based on the Tensor Renormalization Group (TRG) protocol, adapted to operate entirely at the level…

Quantum Physics · Physics 2021-11-24 Manuel Campos , German Sierra , Esperanza Lopez

In correlated electron materials, the application of many-body techniques for the study of interaction effects or unconventional superconductivity often requires the formulation of an effective low-energy model that contains only the…

Strongly Correlated Electrons · Physics 2013-05-30 Carsten Honerkamp

We present a technique designed for parallelizing large rigid body simulations, capable of exploiting multiple CPU cores within a computer and across a network. Our approach can be applied to simulate both unilateral and bilateral…

Graphics · Computer Science 2024-03-27 Manas Kale , Paul G. Kry

The nonrelativistic reduction of the self-consistent covariant density functional theory is realized for the first time with the similarity renormalization group (SRG) method. The reduced nonrelativistic Hamiltonian and densities are…

Nuclear Theory · Physics 2020-08-19 Z. X. Ren , P. W. Zhao

According to the available publications, the field theoretical renormalization group (RG) approach in the two-dimensional case gives the critical exponents that differ from the known exact values. This fact was attempted to explain by the…

Statistical Mechanics · Physics 2009-11-13 A. A. Pogorelov , I. M. Suslov

At low energies, the microscopic characteristics and changes of physical systems as viewed at different distance scales are described by universal scale invariant properties investigated by the Renormalization Group (RG) apparatus, an…

General Physics · Physics 2018-04-03 Eric Howard

We present a detailed discussion of a novel dynamical renormalization group scheme: the Dynamically Driven Renormalization Group (DDRG). This is a general renormalization method developed for dynamical systems with non-equilibrium critical…

Condensed Matter · Physics 2009-10-28 Alessandro Vespignani , Stefano Zapperi , Vittorio Loreto

The renormalization of the effective field theories (EFTs) in many-body systems is the most pressing and challenging problem in modern nuclear ab initio calculation. For general non-relativistic EFTs, we prove that the renormalization group…

Nuclear Theory · Physics 2023-08-29 Bing-Nan Lu , Bao-Ge Deng

We demonstrate how to devise a Matsubara-formalism-based one-loop approximation to the flow of the functional renormalization group (FRG) that reproduces identically the leading-logarithmic parquet approximation. This construction of a…

Strongly Correlated Electrons · Physics 2024-03-25 Jan Diekmann , Severin G. Jakobs

We present a renormalization group (RG) approach to explain universal features of extreme statistics, applied here to independent, identically distributed variables. The outlines of the theory have been described in a previous Letter, the…

Statistical Mechanics · Physics 2015-05-18 G. Gyorgyi , N. R. Moloney , K. Ozogany , Z. Racz , M. Droz

The Density Matrix Renormalization Group (DMRG) algorithm is a powerful tool for solving eigenvalue problems to model quantum systems. DMRG relies on tensor contractions and dense linear algebra to compute properties of condensed matter…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Ryan Levy , Edgar Solomonik , Bryan K. Clark

A hybrid approach to nonequilibrium dynamics of quantum impurity systems is presented. The numerical renormalization group serves as a means to generate a suitable low-energy Hamiltonian, allowing for an accurate evaluation of the real-time…

Strongly Correlated Electrons · Physics 2013-03-20 Fabian Guettge , Frithjof B. Anders , Ulrich Schollwoeck , Eitan Eidelstein , Avraham Schiller

We present a comprehensive review of the In-Medium Similarity Renormalization Group (IM-SRG), a novel ab inito method for nuclei. The IM-SRG employs a continuous unitary transformation of the many-body Hamiltonian to decouple the ground…

Nuclear Theory · Physics 2016-03-15 H. Hergert , S. K. Bogner , T. D. Morris , A. Schwenk , K. Tsukiyama

In the past two decades, the density matrix renormalization group (DMRG) has emerged as an innovative new method in quantum chemistry relying on a theoretical framework very different from that of traditional electronic structure…

Computational Physics · Physics 2020-02-18 Alberto Baiardi , Markus Reiher

The recently developed tensor renormalization-group (TRG) method provides a highly precise technique for deriving thermodynamic and critical properties of lattice Hamiltonians. The TRG is a local coarse-graining transformation, with the…

Statistical Mechanics · Physics 2008-02-18 Michael Hinczewski , A. Nihat Berker

The tensor-network renormalization group (TNRG) is an accurate numerical real-space renormalization group method for studying phase transitions in both quantum and classical systems. Continuous phase transitions, as an important class of…

Statistical Mechanics · Physics 2026-03-27 Xinliang Lyu
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