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Related papers: Renormalization group on tensor networks

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The quantum renormalization group method is applied to study the quantum criticality and entanglement entropy of the ground state of the Ising chain in the presence of antisymmetric anisotropic couplings and alternating exchange…

Strongly Correlated Electrons · Physics 2012-08-09 Xiang Hao

While renormalization groups are fundamental in physics, renormalization of complex networks remains vague in its conceptual definition and methodology. Here, we propose a novel strategy to renormalize complex networks. Rather than…

Statistical Mechanics · Physics 2024-03-13 Sungwon Jung , Sang Hoon Lee , Jaeyoon Cho

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima

Randomly connected tensor networks (RCTN) are the dynamical systems defined by summing over all the possible networks of tensors. Because of the absence of fixed lattice structure, RCTN is not expected to have renormalization procedures. In…

High Energy Physics - Theory · Physics 2025-04-11 Naoki Sasakura

Renormalization group techniques are widely used in modern physics to describe the low energy relevant aspects of systems involving a large number of degrees of freedom. Those techniques are thus expected to be a powerful tool to address…

High Energy Physics - Theory · Physics 2021-11-19 Vincent Lahoche , Dine Ousmane Samary , Mohamed Tamaazousti

Novel randomness-induced disordered ground states in two-dimensional (2D) quantum spin systems have been attracting much interest. For quantitative analysis of such random quantum spin systems, one of the most promising numerical approaches…

Strongly Correlated Electrons · Physics 2020-11-03 Kouichi Seki , Toshiya Hikihara , Kouichi Okunishi

Tensor renormalization group (TRG) constitutes an important methodology for accurate simulations of strongly correlated lattice models. Facilitated by the automatic differentiation technique widely used in deep learning, we propose a…

Strongly Correlated Electrons · Physics 2020-07-07 Bin-Bin Chen , Yuan Gao , Yi-Bin Guo , Yuzhi Liu , Hui-Hai Zhao , Hai-Jun Liao , Lei Wang , Tao Xiang , Wei Li , Z. Y. Xie

We study the critical behavior and phase diagram of the $d$-dimensional random field O(N) model by means of the nonperturbative functional renormalization group approach presented in the preceding paper. We show that the dimensional…

Statistical Mechanics · Physics 2011-07-20 Matthieu Tissier , Gilles Tarjus

We review White's density matrix renormalisation group method, an increasingly popular method for the solution of low dimensional quantum Hamiltonians. We describe some applications to frustrated spin systems, quantum critical phenomena,…

Condensed Matter · Physics 2008-02-03 G. A. Gehring , R. J. Bursill , T. Xiang

We briefly review general concepts of renormalization in quantum field theory and discuss their application to solutions of integral equations with singular potentials in the few-nucleon sector of the low-energy effective field theory of…

Nuclear Theory · Physics 2020-05-28 E. Epelbaum , A. M. Gasparyan , J. Gegelia , Ulf-G. Meißner , X. -L. Ren

Tensor network methods are taking a central role in modern quantum physics and beyond. They can provide an efficient approximation to certain classes of quantum states, and the associated graphical language makes it easy to describe and…

Quantum Physics · Physics 2017-08-02 Jacob Biamonte , Ville Bergholm

We compute the partition function of a massive free boson in a square lattice using a tensor network algorithm. We introduce a singular value decomposition (SVD) of continuous matrices that leads to very accurate numerical results. It is…

Statistical Mechanics · Physics 2019-11-13 Manuel Campos , German Sierra , Esperanza Lopez

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 renormalization group approach as developed by the author for Fermi liquids is applied to clean Fermi liquids and ballistic quantum dots. In the former case Landau theory is shown to be a fixed point and in the latter the Universal…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 R. Shankar

This article presents a tutorial introduction to a recently developed real-time renormalization group method. It describes nonequilibrium properties of discrete quantum systems coupled linearly to an environment. We illustrate the technique…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Herbert Schoeller

We briefly summarize some recent theoretical developments in perturbative QCD, emphasizing new ideas which have led to widening the domain of applicability of perturbation theory. In particular, it is now possible to calculate efficiently…

High Energy Physics - Phenomenology · Physics 2009-10-30 Stefano Forte

The full-density-matrix numerical renormalization group (NRG) has evolved as a systematic and transparent setting for the cal- culation of thermodynamical quantities at arbitrary temperatures within the NRG framework. It directly evaluates…

Strongly Correlated Electrons · Physics 2013-05-30 Andreas Weichselbaum

We examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not…

Quantum Physics · Physics 2015-03-17 Jacob D. Biamonte , Stephen R. Clark , Dieter Jaksch

The renormalization group (RG) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification in a relatively small set of…

Statistical Mechanics · Physics 2024-09-04 Guido Caldarelli , Andrea Gabrielli , Tommaso Gili , Pablo Villegas

We propose inverse renormalization group transformations within the context of quantum field theory that produce the appropriate critical fixed point structure, give rise to inverse flows in parameter space, and evade the critical slowing…

High Energy Physics - Lattice · Physics 2022-02-25 Dimitrios Bachtis , Gert Aarts , Francesco Di Renzo , Biagio Lucini
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