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This is a lecture note on the renormalization group theory for field theory models based on the dimensional regularization method. We discuss the renormalization group approach to fundamental field theoretic models in low dimensions. We…

Statistical Mechanics · Physics 2018-04-10 Takashi Yanagisawa

Quantum and tensor network simulations have emerged as prominent sign-problem free approaches to lattice gauge theories. Unlike conventional Markov chain Monte Carlo methods, they are based on the Hamiltonian formulation. In this talk, we…

High Energy Physics - Lattice · Physics 2021-12-01 Angus Kan , Lena Funcke , Stefan Kühn , Luca Dellantonio , Jinglei Zhang , Jan F. Haase , Christine A. Muschik , Karl Jansen

We consider the sign problem for classical spin models at complex $\beta =1/g_0^2$ on $L\times L$ lattices. We show that the tensor renormalization group method allows reliable calculations for larger Im$\beta$ than the reweighting Monte…

High Energy Physics - Lattice · Physics 2014-01-15 Alan Denbleyker , Yuzhi Liu , Y. Meurice , M. P. Qin , T. Xiang , Z. Y. Xie , J. F. Yu , Haiyuan Zou

Monte Carlo sampling techniques have been proposed as a strategy to reduce the computational cost of contractions in tensor network approaches to solving many-body systems. Here we put forward a variational Monte Carlo approach for the…

Strongly Correlated Electrons · Physics 2012-05-01 Andrew J. Ferris , Guifre Vidal

Ab-initio calculations of real-time evolution for lattice gauge theory have very interesting potential applications but present challenging computational aspects. We show that tensor renormalization group methods developed in the context of…

High Energy Physics - Lattice · Physics 2024-01-15 Michael Hite , Yannick Meurice

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 describe a new method to compute renormalized coupling constants in a Monte Carlo renormalization group calculation. The method can be used for a general class of models, e.g., lattice spin or gauge models. The basic idea is to simulate…

High Energy Physics - Lattice · Physics 2009-10-22 M. Hasenbusch , K. Pinn , C. Wieczerkowski

We develop a formalism for performing real space renormalization group transformations of the "decimation type" using perturbation theory. The type of transformations beyond $d=1$ is nontrivial even for free theories. We check the formalism…

Condensed Matter · Physics 2016-08-31 V. Kushnir , B. Rosenstein

We demonstrate a tensor renormalization group (TRG) calculation for a two-dimensional Lorentzian model of quantum Regge calculus (QRC). This model is expressed in terms of a tensor network by discretizing the continuous edge lengths of…

High Energy Physics - Theory · Physics 2022-11-24 Yoshiyasu Ito , Daisuke Kadoh , Yuki Sato

We introduce a scheme to perform Monte Carlo Renormalization Group with the coupling constants of the system Hamiltonian encoded in a tensor network. With this scheme we compute the tangent space to the manifold of the critical Hamiltonians…

Statistical Mechanics · Physics 2020-10-07 Yantao Wu

We investigate the phase diagram, and the nature of the phase transitions, of three-dimensional monopole-free CP(N-1) models, characterized by a global U(N) symmetry and a U(1) gauge symmetry, and the absence of monopoles. We present…

Statistical Mechanics · Physics 2020-07-01 Andrea Pelissetto , Ettore Vicari

We develop the functional renormalization group formalism for a tensorial group field theory with closure constraint, in the case of an Abelian just renormalizable model with quartic interactions. The method allows us to obtain a closed but…

High Energy Physics - Theory · Physics 2016-05-10 Dario Benedetti , Vincent Lahoche

We develop coarse-graining tensor renormalization group algorithms to compute physical properties of two-dimensional lattice models on finite periodic lattices. Two different coarse-graining strategies, one based on the tensor…

Strongly Correlated Electrons · Physics 2016-07-12 Hui-Hai Zhao , Zhi-Yuan Xie , Tao Xiang , Masatoshi Imada

We report recent progress on the application of the tensor renormalization group (TRG) to quantum field theories pursued by the Tsukuba group. We explain how to treat the scalar, fermion, and gauge theories with the TRG method presenting…

High Energy Physics - Lattice · Physics 2022-09-21 Shinichiro Akiyama , Yoshinobu Kuramashi , Yusuke Yoshimura

The tensor-entanglement renormalization group approach is applied to Hamiltonians that realize a class of topologically ordered states -- string-net condensed states. We analyze phase transitions between phases with and without string-net…

Strongly Correlated Electrons · Physics 2009-03-08 Zheng-Cheng Gu , Michael Levin , Xiao-Gang Wen

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

Tensor linear regression is an important and useful tool for analyzing tensor data. To deal with high dimensionality, CANDECOMP/PARAFAC (CP) low-rank constraints are often imposed on the coefficient tensor parameter in the (penalized)…

Machine Learning · Statistics 2024-04-02 Ya Zhou , Raymond K. W. Wong , Kejun He

In general, perturbative expansions of observables in powers of the coupling constant in quantum field theories are asymptotic series. In many cases it is possible to apply resummation techniques to assign a unique finite value to an…

High Energy Physics - Lattice · Physics 2018-11-08 Matthias Puhr , Falk Bruckmann

The transverse-field Ising model on the Sierpi\'nski fractal, which is characterized by the fractal dimension $\log_2^{~} 3 \approx 1.585$, is studied by a tensor-network method, the Higher-Order Tensor Renormalization Group. We analyze the…

Statistical Mechanics · Physics 2018-12-19 Roman Krcmar , Jozef Genzor , Yoju Lee , Hana Čenčariková , Tomotoshi Nishino , Andrej Gendiar

Apparently convergent contributions of resummed perturbative series at the next-to-leading order of the 1/N expansion in the O(N) model are reanalyzed in terms of renormalizability. Compared to our earlier article [G. Fejos et al., Phys.…

High Energy Physics - Phenomenology · Physics 2015-06-19 G. Fejos , A. Patkos , Zs. Szep