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In this work, we present the first implementation of the transcorrelated electronic Hamiltonian in an optimization procedure for matrix product states by the density matrix renormalization group (DMRG) algorithm. In the transcorrelation…

Chemical Physics · Physics 2022-08-30 Alberto Baiardi , Michał Lesiuk , Markus Reiher

Within the Functional Renormalisation Group (FRG) approach, we present a fluid-dynamical approach to solving flow equations for models living in a multi-dimensional field space. To this end, the underlying exact flow equation of the…

Statistical Mechanics · Physics 2024-12-23 Niklas Zorbach , Adrian Koenigstein , Jens Braun

On a finite momentum grid with N integration points and weights the Similarity Renormalization Group (SRG) with a given generator G unitarily evolves an initial interaction with a cutoff on energy differences. This steadily drives the…

Nuclear Theory · Physics 2014-04-22 E. Ruiz Arriola , S. Szpigel , V. S. Timoteo

The paper describes an explicit variational modification of the standard RSRG method and its application to quantum spin lattice systems. The modified approach is applied to exactly solvable ITF, XX and isotropic Heisenberg models. Better…

Strongly Correlated Electrons · Physics 2014-07-02 A. S. Serov , G. V. Koval

We consider the application of the two-loop functional renormalization-group (fRG) approach to study the low-dimensional Hubbard model. This approach accounts for both, the universal and non-universal contributions to the RG flow. While the…

Strongly Correlated Electrons · Physics 2009-09-01 A. A. Katanin

The density matrix renormalization group (DMRG) is applied to some one-dimensional reaction-diffusion models in the vicinity of and at their critical point. The stochastic time evolution for these models is given in terms of a non-symmetric…

Statistical Mechanics · Physics 2011-10-11 Enrico Carlon , Malte Henkel , Ulrich Schollwoeck

Stochastic variance reduced gradient (SVRG) is a popular variance reduction technique for accelerating stochastic gradient descent (SGD). We provide a first analysis of the method for solving a class of linear inverse problems in the lens…

Numerical Analysis · Mathematics 2022-01-19 Bangti Jin , Zehui Zhou , Jun Zou

We study transport properties of quantum impurity systems using the functional renormalization group. The latter is an RG-based diagrammatic tool to treat Coulomb interactions in a fast and flexible way. Prior applications, which employed a…

Strongly Correlated Electrons · Physics 2010-09-21 C. Karrasch

The non-perturbative {\it ab initio} calculations of infinite nuclear matter using In-Medium Similarity Renormalization Group (IMSRG) method is developed in this work, which enables calculations with chiral two and three-nucleon forces at…

Nuclear Theory · Physics 2025-02-27 Xin Zhen , Rongzhe Hu , Haoyu Shang , Jiawei Chen , Junchen Pei , Furong Xu

A simple class of unitary renormalization group transformations that force hamiltonians towards a band-diagonal form produce few-body interactions in which low- and high-energy states are decoupled, which can greatly simplify many-body…

Nuclear Theory · Physics 2008-11-26 S. K. Bogner , R. J. Furnstahl , R. J. Perry

The renormalization group (RG) method is one of the singular perturbation methods which is used in search for asymptotic behavior of solutions of differential equations. In this article, time-independent vector fields and time (almost)…

Dynamical Systems · Mathematics 2015-05-14 Hayato Chiba

A new framework for exploiting information about the renormalization group (RG) behavior of gravity in a dynamical context is discussed. The Einstein-Hilbert action is RG-improved by replacing Newton's constant and the cosmological constant…

High Energy Physics - Theory · Physics 2007-05-23 M. Reuter , H. Weyer

We first examine how T-matrix equivalence drives the flow of similarity renormalization group (SRG) evolved potential matrix elements to a universal form, with the ultimate goal of gaining insight into universality for three-nucleon forces.…

Nuclear Theory · Physics 2015-03-02 Brian Dainton

The recently proposed combination of the valence-space in-medium similarity renormalization group (VS-IMSRG) with the density matrix renormalization group (DMRG) offers a scalable and flexible many-body approach for strongly correlated…

Nuclear Theory · Physics 2024-08-12 A. Tichai , K. Kapás , T. Miyagi , M. A. Werner , Ö. Legeza , A. Schwenk , G. Zarand

We summarize our recent results on the large N renormalization group (RG) approach to matrix models for discretized two-dimensional quantum gravity. We derive exact RG equations by solving the reparametrization identities, which reduce…

High Energy Physics - Theory · Physics 2007-05-23 S. Higuchi , C. Itoi , S. Nishigaki , N. Sakai

We present a general frame to extend functional renormalization group (fRG) based computational schemes by using an exactly solvable interacting reference problem as starting point for the RG flow. The systematic expansion around this…

Strongly Correlated Electrons · Physics 2015-02-11 Nils Wentzell , Ciro Taranto , Andrey A. Katanin , Alessandro Toschi , Sabine Andergassen

The Magnus expansion is an efficient alternative to solving similarity renormalization group (SRG) flow equations with high-order, memory-intensive ordinary differential equation solvers. The numerical simplifications it offers for operator…

Nuclear Theory · Physics 2020-09-23 A. J. Tropiano , S. K. Bogner , R. J. Furnstahl

The pseudofermion functional renormalization group (pffRG) is a computational method for determining zero-temperature phase diagrams of frustrated quantum magnets. In a recent methodological advance, the commonly employed Katanin truncation…

Strongly Correlated Electrons · Physics 2022-07-04 Marc K. Ritter , Dominik Kiese , Tobias Müller , Fabian B. Kugler , Ronny Thomale , Simon Trebst , Jan von Delft

The density matrix renormalization group (DMRG) algorithm is a cornerstone computational method for studying quantum many-body systems, renowned for its accuracy and adaptability. Despite DMRG's broad applicability across fields such as…

Computational Physics · Physics 2026-03-24 Per Sehlstedt , Jan Brandejs , Paolo Bientinesi , Lars Karlsson

We train machine learning algorithms to infer the entanglement structure of disordered long-range interacting quantum spin chains by learning from the strong disorder renormalisation group (SDRG) method. The system consists of…

Disordered Systems and Neural Networks · Physics 2026-03-06 A. Ustyuzhanin , J. Vahedi , S. Kettemann