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The projective construction (the slave-particle approach) has played an very important role in understanding strongly correlated systems, such as the emergence of fermions, anyons, and gauge theory in quantum spin liquids and quantum Hall…

Strongly Correlated Electrons · Physics 2010-04-19 Zheng-Cheng Gu , Frank Verstraete , Xiao-Gang Wen

Making a combined use of bosonization and fermionization techniques, we build nonlocal transformations between dual fermion operators, describing junctions of strongly interacting spinful one-dimensional quantum wires. Our approach allows…

Strongly Correlated Electrons · Physics 2015-09-30 Domenico Giuliano , Andrea Nava

We use the Grassmann tensor renormalization group method to investigate the $N_f=2$ Schwinger model with the staggered fermions in the presence of a $2\pi$ periodic $\theta$ term in a broad range of mass. The method allows us to deal with…

High Energy Physics - Lattice · Physics 2025-11-12 Hayato Kanno , Shinichiro Akiyama , Kotaro Murakami , Shinji Takeda

We develop a new formulation of the functional renormalization group (RG) for interacting fermions. Our approach unifies the purely fermionic formulation based on the Grassmannian functional integral, which has been used in recent years by…

Strongly Correlated Electrons · Physics 2007-05-23 Florian Schuetz , Lorenz Bartosch , Peter Kopietz

We propose a novel parametrization of the four-point vertex function in the one-loop one-particle irreducible renormalization group (RG) scheme for fermions. It is based on a decomposition of the effective two-fermion interaction into…

Strongly Correlated Electrons · Physics 2009-02-11 Christoph Husemann , Manfred Salmhofer

We propose a new tensor renormalization group algorithm, Anisotropic Tensor Renormalization Group (ATRG), for lattice models in arbitrary dimensions. The proposed method shares the same versatility with the Higher-Order Tensor…

Statistical Mechanics · Physics 2020-09-02 Daiki Adachi , Tsuyoshi Okubo , Synge Todo

We study the two-dimensional square lattice Ising ferromagnet and antiferromagnet with a magnetic field by using tensor network method. Focusing on the role of guage fixing, we present the partition function in terms of a tensor network.…

Statistical Mechanics · Physics 2025-01-03 Myung-Hoon Chung

The Ising model with ferromagnetic couplings on the Hanoi networks is analyzed with an exact renormalization group. In particular, the fixed-points are determined and the renormalization-group flow for certain initial conditions is…

Disordered Systems and Neural Networks · Physics 2015-03-17 S. Boettcher , C. T. Brunson

By combining the Grassmann algebra with multi-scale entanglement renormalization ansatz (MERA), we introduce a new unbiased and effective numerical method for simulating 2D strongly correlated electronic systems. The new GMERA method…

Strongly Correlated Electrons · Physics 2015-06-12 Jie Lou , Yan Chen

We propose a modified form of a tensor renormalization group algorithm for evaluating partition functions of classical statistical mechanical models on 2D lattices. This algorithm coarse-grains only the rows and columns of the lattice…

Quantum Physics · Physics 2019-12-18 Wangwei Lan , Glen Evenbly

The Wilsonian exact renormalization group gives a natural framework in which ultraviolet and infrared divergences can be treated separately. In massless QED we introduce, as the only mass parameter, a renormalization scale $\L_R > 0$. We…

High Energy Physics - Theory · Physics 2009-10-30 M. Pernici , M. Raciti , F. Riva

Isometric tensor networks in two dimensions enable efficient and accurate study of quantum many-body states, yet the effect of the isometric restriction on the represented quantum states is not fully understood. We address this question in…

We propose a hybrid stochastic method for the tensor renormalization group (TRG) approach. TRG is known as a powerful tool to study the many-body systems and quantum field theory on the lattice. It is based on a low-rank approximation of…

High Energy Physics - Lattice · Physics 2021-10-25 Hiroshi Ohki , Erika Arai , Masaaki Tomii

The geometric renormalization technique for complex networks has successfully revealed the multiscale self-similarity of real network topologies and can be applied to generate replicas at different length scales. In this letter, we extend…

Physics and Society · Physics 2023-07-04 Muhua Zheng , Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano

We develop a recently-proposed mapping of the two-dimensional Ising model with random exchange (RBIM), via the transfer matrix, to a network model for a disordered system of non-interacting fermions. The RBIM transforms in this way to a…

Disordered Systems and Neural Networks · Physics 2011-08-05 F. Merz , J. T. Chalker

We introduce a variational algorithm to simulate quantum many-body states based on a tree tensor network ansatz which releases the isometry constraint usually imposed by the real-space renormalization coarse-graining: This additional…

Statistical Mechanics · Physics 2014-10-08 Matthias Gerster , Pietro Silvi , Matteo Rizzi , Rosario Fazio , Tommaso Calarco , Simone Montangero

We develop the tensor renormalization group (TRG) algorithm for statistical systems with open boundaries, which allows us to investigate not only the bulk but also the boundary property, such as the surface magnetization. We demonstrate…

Statistical Mechanics · Physics 2019-08-02 Shumpei Iino , Satoshi Morita , Naoki Kawashima

Tensor renormalization group, originally devised as a numerical technique, is emerging as a rigorous analytical framework for studying lattice models in statistical physics. Here we introduce a new renormalization map - the 2x1 map - which…

Statistical Mechanics · Physics 2025-06-05 Nikolay Ebel , Tom Kennedy , Slava Rychkov

We apply the Grassmann tensor renormalization group (GTRG) to the one-flavor lattice Gross-Neveu model in the presence of chemical potential. We compute the fermion number density and its susceptibility and confirm the validity of GTRG for…

High Energy Physics - Lattice · Physics 2015-04-01 Shinji Takeda , Yusuke Yoshimura

We propose a new renormalization scheme of tensor networks made only of third order tensors. The isometry used for coarse-graining the network can be prepared at an $O(D^6)$ computational cost in any $d$ dimension ($d \ge 2$), where $D$ is…

High Energy Physics - Lattice · Physics 2019-12-06 Daisuke Kadoh , Katsumasa Nakayama