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We propose a simple connection between matrix quantum mechanics and tensor networks. This allows us to imbue tensor networks with some interesting additional structure. The geometry of the graph describing the tensor network state is…

High Energy Physics - Theory · Physics 2024-07-25 Alexander Frenkel

The phase diagram of a novel two-dimensional frustrated Ising model with both anti-ferromagnetic and ferromagnetic couplings is studied using Tensor-Network Renormalization-Group techniques. This model can be seen as two anti-ferromagnetic…

Statistical Mechanics · Physics 2025-02-19 Christophe Chatelain

We study the topological entanglement entropy and scalar chirality of a topologically ordered skyrmion formed in a two-dimensional triangular lattice. Scalar chirality remains a smooth function of the magnetic field in both helical and…

Strongly Correlated Electrons · Physics 2023-11-08 Vipin Vijayan , L. Chotorlishvili , A. Ernst , S. S. P. Parkin , M. I. Katsnelson , S. K. Mishra

We study the complexity of approximately contracting translation-invariant tensor networks. The computational cost of row-by-row tensor network contraction, which defines a discrete time evolution governed by a fixed transfer matrix, is…

Quantum Physics · Physics 2026-05-06 Yi-Cheng Wang , Samuel J. Garratt , Ehud Altman

We define a class of tensor network states for spin systems where the individual tensors are functionals of fields. The construction is based on the path integral representation of correlators of operators in quantum field theory. These…

Statistical Mechanics · Physics 2021-04-20 Anne E. B. Nielsen , Benedikt Herwerth , J. Ignacio Cirac , Germán Sierra

We prove the existence of a finite temperature Z_{2} phase transition for the topological charge ordering within the Fully Frustrated XY Model. Our method enables a proof of the topological charge confinement within the conventional XY…

Statistical Mechanics · Physics 2014-01-07 Zohar Nussinov

We establish an intriguing connection between quantum phase transitions and bifurcations in the ground-state fidelity per lattice site, and construct the universal order parameter for quantum Ising model in a transverse magnetic field on an…

Strongly Correlated Electrons · Physics 2011-05-17 Sheng-Hao Li , Hong-Lei Wang , Qian-Qian Shi , Huan-Qiang Zhou

Tensor networks (TNs) have become one of the most essential building blocks for various fields of theoretical physics such as condensed matter theory, statistical mechanics, quantum information, and quantum gravity. This review provides a…

Statistical Mechanics · Physics 2022-05-10 Kouichi Okunishi , Tomotoshi Nishino , Hiroshi Ueda

We consider the effect of positional disorder on a Josephson junction array with an applied magnetic field of f=1/2 flux quantum per unit cell. This is equivalent to the problem of random Gaussian phase shifts in the fully frustrated 2D XY…

Superconductivity · Physics 2009-10-31 Pramod Gupta , S. Teitel

Accurately evaluating configurational integrals for dense solids remains a central and difficult challenge in the statistical mechanics of condensed systems. Here, we present a novel tensor network approach that reformulates the…

We demonstrate the power of 2D tensor networks for obtaining large deviation functions of dynamical observables in a classical nonequilibrium setting. Using these methods, we analyze the previously unstudied dynamical phase behavior of the…

Statistical Mechanics · Physics 2020-10-07 Phillip Helms , Garnet Kin-Lic Chan

Trial wavefunctions that can be represented by summing over locally-coupled degrees of freedom are called tensor network states (TNSs); they have seemed difficult to construct for two-dimensional topological phases that possess protected…

Mesoscale and Nanoscale Physics · Physics 2015-11-25 J. Dubail , N. Read

The one-dimensional extended isotropic XY model (s=1/2) in a transverse field with uniform long-range interactions among the \textit{z} components of the spin is considered. The model is exactly solved by introducing the gaussian and…

Statistical Mechanics · Physics 2009-12-11 F. G. Ribeiro , J. P. de Lima , L. L. Goncalves

Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a…

Statistical Mechanics · Physics 2020-08-12 Javier Lopez-Piqueres , Brayden Ware , Romain Vasseur

We examine the possibility that pertinent impurities in a condensed matter system may help in designing quantum devices with enhanced coherent behaviors. For this purpose, we analyze a field theory model describing Y- shaped superconducting…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 D. Giuliano , P. Sodano

The tensor product representation of quantum states leads to a promising variational approach to study quantum phase and quantum phase transitions, especially topological ordered phases which are impossible to handle with conventional…

Strongly Correlated Electrons · Physics 2013-05-29 Xie Chen , Bei Zeng , Zheng-Cheng Gu , Isaac L. Chuang , Xiao-Gang Wen

Two-dimensional arrays of superconductors separated by normal metallic regions exhibit rich phenomenology and a high degree of controllability. We establish such systems as platforms for topological phases of matter, and in particular…

Mesoscale and Nanoscale Physics · Physics 2024-04-29 Omri Lesser , Ady Stern , Yuval Oreg

We introduce a fully frustrated XY model with nearest neighbor (nn) and next nearest neighbor (nnn) couplings which can be realized in Josephson junction arrays. We study the phase diagram for $0\leq x \leq 1$ ($x$ is the ratio between nnn…

Statistical Mechanics · Physics 2009-10-31 G. Franzese , V. Cataudella , S. E. Korshunov , R. Fazio

We study the bipartite entanglement per bond to determine characteristic features of the phase diagram of various quantum spin models in different spatial dimensions. The bipartite entanglement is obtained from a tensor network…

Quantum Physics · Physics 2016-07-07 B. Braiorr-Orrs , M. Weyrauch , M. V. Rakov

Machine-learning techniques have proved successful in identifying ordered phases of matter. However, it remains an open question how far they can contribute to the understanding of phases without broken symmetry, such as spin liquids. Here…

Strongly Correlated Electrons · Physics 2019-11-19 Jonas Greitemann , Ke Liu , Ludovic D. C. Jaubert , Han Yan , Nic Shannon , Lode Pollet