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We numerically determine subleading scaling terms in the ground-state entanglement entropy of several two-dimensional (2D) gapless systems, including a Heisenberg model with N\'eel order, a free Dirac fermion in the {\pi}-flux phase, and…

Strongly Correlated Electrons · Physics 2012-04-25 Hyejin Ju , Ann B. Kallin , Paul Fendley , Matthew B. Hastings , Roger G. Melko

Let $H$ be a frustration-free Hamiltonian describing a 2D grid of qudits with local interactions, a unique ground state, and local spectral gap lower bounded by a positive constant. For any bipartition defined by a vertical cut of length…

Quantum Physics · Physics 2022-06-28 Anurag Anshu , Itai Arad , David Gosset

We present experimentally and numerically accessible quantities that can be used to differentiate among various families of random entangled states. To this end, we analyze the entanglement properties of bipartite reduced states of a…

Inspired by holographic codes and tensor-network decoders, we introduce tensor-network stabilizer codes which come with a natural tensor-network decoder. These codes can correspond to any geometry, but, as a special case, we generalize…

Quantum Physics · Physics 2021-07-28 Terry Farrelly , Robert J. Harris , Nathan A. McMahon , Thomas M. Stace

Entanglement is one of the physical properties of quantum systems responsible for the computational hardness of simulating quantum systems. But while the runtime of specific algorithms, notably tensor network algorithms, explicitly depends…

Tensor networks are a powerful tool for many-body ground states with limited entanglement. These methods can nonetheless fail for certain time-dependent processes - such as quantum transport or quenches - where entanglement growth is linear…

Strongly Correlated Electrons · Physics 2020-05-20 Gabriela Wojtowicz , Justin E. Elenewski , Marek M. Rams , Michael Zwolak

In quantum spin chains at criticality, two types of scaling for the entanglement entropy exist: one comes from conformal field theory (CFT), and the other is for entanglement support of matrix product state (MPS) approximation. They…

Statistical Mechanics · Physics 2011-09-02 Hiroaki Matsueda

This article reviews the quantum entanglement in Valence-Bond-Solid (VBS) states defined on a lattice or a graph. The subject is presented in a self-contained and pedagogical way. The VBS state was first introduced in the celebrated paper…

Quantum Physics · Physics 2015-03-13 Vladimir E. Korepin , Ying Xu

In the tensor-network framework, the expectation values of two-dimensional quantum states are evaluated by contracting a double-layer tensor network constructed from initial and final tensor-network states. The computational cost of…

Strongly Correlated Electrons · Physics 2017-07-24 Z. Y. Xie , H. J. Liao , R. Z. Huang , H. D. Xie , J. Chen , Z. Y. Liu , T. Xiang

Tensor networks impose a notion of geometry on the entanglement of a quantum system. In some cases, this geometry is found to reproduce key properties of holographic dualities, and subsequently much work has focused on using tensor networks…

Strongly Correlated Electrons · Physics 2017-10-04 Katharine Hyatt , James R. Garrison , Bela Bauer

We have developed an efficient tensor network algorithm for spin ladders, which generates ground-state wave functions for infinite-size quantum spin ladders. The algorithm is able to efficiently compute the ground-state fidelity per lattice…

Statistical Mechanics · Physics 2011-05-17 Sheng-Hao Li , Yao-Heng Su , Yan-Wei Dai , Huan-Qiang Zhou

In tensor networks, a geometric operation of pushing a bond cut surface toward a minimal surface corresponds to entanglement distillation. Cutting bonds defines a reduced transition matrix on the bond cut surface and the associated quantum…

High Energy Physics - Theory · Physics 2022-10-17 Takato Mori , Hidetaka Manabe , Hiroaki Matsueda

In a $d$-dimensional topological insulator of order $d$, there are zero energy states on its corners which have close relationship with its entanglement behaviors. We studied the bipartite entanglement spectra for different subsystem shapes…

Mesoscale and Nanoscale Physics · Physics 2019-07-04 Qiang Wang , Da Wang , Qiang-Hua Wang

A rigorous analysis is presented for the entanglement spectrum of quantum many-body states possessing a higher-form group-representation symmetry generated by topological Wilson loops, which is generally non-invertible. A general framework…

Quantum Physics · Physics 2025-10-22 Haruki Yagi , Zongping Gong

We perform an exact diagonalization study of the topological order in topological flat band models through calculating entanglement entropy and spectra of low energy states. We identify multiple independent minimal entangled states, which…

Strongly Correlated Electrons · Physics 2013-08-20 W. Zhu , D. N. Sheng , F. D. M. Haldane

In this work, we investigate the effects of $\text{T}\bar{\text{T}}$ and root-$\text{T}\bar{\text{T}}$ deformations on reflected and entanglement entropy in the context of both pure and mixed state entanglement measures. Utilizing a mixed…

High Energy Physics - Theory · Physics 2026-01-16 Saikat Biswas

Quantum systems with short range interactions are known to respect an area law for the entanglement entropy: the von Neumann entropy $S$ associated to a bipartition scales with the boundary $p$ between the two parts. Here we study the case…

Quantum Physics · Physics 2010-02-03 Alioscia Hamma , Daniel A. Lidar , Simone Severini

We begin by deriving bounds for the entanglement of a spin with an (adjacent and non-adjacent) interval of spins in an arbitrary pure Finitely Correlated States (FCS). The bounds we derive become exact in the case where one considers the…

Quantum Physics · Physics 2008-07-31 Spyridon Michalakis

The theory of entanglement provides a fundamentally new language for describing interactions and correlations in many body systems. Its vocabulary consists of qubits and entangled pairs, and the syntax is provided by tensor networks. We…

Quantum Physics · Physics 2021-12-20 Ignacio Cirac , David Perez-Garcia , Norbert Schuch , Frank Verstraete

Deep neural networks (DNNs) have delivered a remarkable performance in many tasks of computer vision. However, over-parameterized representations of popular architectures dramatically increase their computational complexity and storage…

Computer Vision and Pattern Recognition · Computer Science 2022-05-31 Chang Nie , Huan Wang , Lu Zhao