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The eigenvalue structure of the quantum transfer matrix is known to encode essential information about the elementary excitations. Here we study transfer matrices of quantum states in a topological phase using the tensor network formalism.…

Strongly Correlated Electrons · Physics 2016-07-26 Jutho Haegeman , Valentin Zauner , Norbert Schuch , Frank Verstraete

We construct a tensor network representation of the partition function for the massless Schwinger model on a two dimensional lattice using staggered fermions. The tensor network representation allows us to include a topological term. Using…

High Energy Physics - Lattice · Physics 2020-06-24 Nouman Butt , Simon Catterall , Yannick Meurice , Judah Unmuth-Yockey

One of the challenging problems in the condensed matter physics is to understand the quantum many-body systems, especially, their physical mechanisms behind. Since there are only a few complete analytical solutions of these systems, several…

Statistical Mechanics · Physics 2020-03-27 Jozef Genzor , Tomotoshi Nishino , Andrej Gendiar

We consider the two-dimensional uniformly frustrated XY model in the limit of small frustration, which is equivalent to an XY system, for instance a Josephson junction array, in a weak uniform magnetic field applied along a direction…

Statistical Mechanics · Physics 2009-11-13 Vincenzo Alba , Andrea Pelissetto , Ettore Vicari

We construct a general wave function with the topological order by introducing the $\mathbb{Z}_{2}$ gauge degrees of freedom, characterizing both the toric code state and double semion state. Via calculating the correlation length defined…

Strongly Correlated Electrons · Physics 2018-10-17 Wen-Tao Xu , Guang-Ming Zhang

Landau theory's implicit assumption that microscopic details cannot affect the system's phases has been challenged only recently in systems such as antiferromagnetic quantum spin chains with periodic boundary conditions, where topological…

We present a nonperturbative tensor-network approach to the excitation spectra of superconducting circuits based on Josephson junction arrays. These arrays provide the large lumped inductances required for qubit designs, yet their…

Quantum Physics · Physics 2025-10-13 Emilio Rui , Joachim Cohen , Alexandru Petrescu

By using extensive tensor network calculations, we map out the phase diagram of the frustrated $J_1$-$J_2$ Ising model on the square lattice. In particular, we focus on the cases with controversy in the phase diagram, especially the stripe…

Statistical Mechanics · Physics 2021-08-19 Hong Li , Li-Ping Yang

It is shown that the phase diagram of the two-dimensional generalized fully-frustrated XY model on a square lattice contains a crossing of the chirality transition and the Kosterlitz-Thouless (KT) transition, as well as a stable phase…

Superconductivity · Physics 2008-01-22 Petter Minnhagen , Beom Jun Kim , Sebastian Bernhardsson , Gerardo Cristofano

We study the quantum phase transition of the one-dimensional phase model in the presence of dissipative frustration, provided by an interaction of the system with the environment through two non-commuting operators. Such a model can be…

Statistical Mechanics · Physics 2018-04-25 Dominik Maile , Sabine Andergassen , Wolfgang Belzig , Gianluca Rastelli

We introduce a method for extracting meaningful entanglement measures of tensor network states in general dimensions. Current methods require the explicit reconstruction of the density matrix, which is highly demanding, or the contraction…

Strongly Correlated Electrons · Physics 2022-07-28 Noa Feldman , Augustine Kshetrimayum , Jens Eisert , Moshe Goldstein

We use the recently developed tensor network algorithm based on infinite projected entangled pair states (iPEPS) to study the phase diagram of frustrated antiferromagnetic J1-J2 Heisenberg model on a checkerboard lattice. The simulation…

Strongly Correlated Electrons · Physics 2012-05-01 Yang-hao Chan , Yong-jian Han , Luming Duan

We describe the use of tensor networks to numerically determine wave functions of interacting two-dimensional fermionic models in the continuum limit. We use two different tensor network states: one based on the numerical continuum limit of…

Strongly Correlated Electrons · Physics 2021-04-28 Reza Haghshenas , Zhi-Hao Cui , Garnet Kin-Lic Chan

The recent progress in the optimization of two-dimensional tensor networks [H.-J. Liao, J.-G. Liu, L. Wang, and T. Xiang, Phys. Rev. X ${\bf 9}$, 031041 (2019)] based on automatic differentiation opened the way towards precise and fast…

Strongly Correlated Electrons · Physics 2021-02-16 Juraj Hasik , Didier Poilblanc , Federico Becca

An efficient algorithm is constructed for contracting two-dimensional tensor networks under periodic boundary conditions. The central ingredient is a novel renormalization step that scales linearly with system size, i.e. from $L \to L+1$.…

Strongly Correlated Electrons · Physics 2025-04-17 Gleb Fedorovich , Lukas Devos , Jutho Haegeman , Laurens Vanderstraeten , Frank Verstraete , Atsushi Ueda

Tensor network states constitute an important variational set of quantum states for numerical studies of strongly correlated systems in condensed-matter physics, as well as in mathematical physics. This is specifically true for finitely…

Quantum Physics · Physics 2014-11-27 M. Kliesch , D. Gross , J. Eisert

We investigate the finite-temperature phase diagram of the classical $J_1$-$J_2$ XY model on a square lattice using a tensor network approach designed for frustrated spin systems. This model, characterized by competing nearest-neighbor and…

Strongly Correlated Electrons · Physics 2024-12-30 Feng-Feng Song , Hanggai Nuomin , Naoki Kawashima

Berezinskii-Kosterlitz-Thouless transition of the classical XY model is re-investigated, combining the Tensor Network Renormalization (TNR) and the Level Spectroscopy method based on the finite-size scaling of the Conformal Field Theory. By…

Statistical Mechanics · Physics 2022-07-25 Atsushi Ueda , Masaki Oshikawa

Tensor completion is a natural higher-order generalization of matrix completion where the goal is to recover a low-rank tensor from sparse observations of its entries. Existing algorithms are either heuristic without provable guarantees,…

Data Structures and Algorithms · Computer Science 2023-07-14 Allen Liu , Ankur Moitra

Tensor network techniques are becoming increasingly popular tools to solve partial differential equations within the so-called quantics representation. Their popularity stems from the fact that their spatial resolution depends only…

Quantum Physics · Physics 2026-04-13 Jheng-Wei Li , Nicolas Jolly , Xavier Waintal