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Building models of Complex Networked Systems (CNS) that can accurately represent reality forms an important research area. To be able to reflect real world systems, the modelling needs to consider not only the intensity of interactions…

Artificial Intelligence · Computer Science 2023-09-26 Jiaqi Wen , Bogdan Gabrys , Katarzyna Musial

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

Hyperbolic superlattices are used for sub-wavelength focusing, cloaking, and optical thermal management. Typically, these superlattices are constructed of layers of noble metals and insulators. Despite these systems displaying excellent…

We present a numerical strategy to efficiently estimate bipartite entanglement measures, and in particular the Entanglement of Formation, for many-body quantum systems on a lattice. Our approach exploits the Tree Tensor Operator tensor…

Quantum Physics · Physics 2022-01-26 Luca Arceci , Pietro Silvi , Simone Montangero

Entanglement and its propagation are central to understanding a multitude of physical properties of quantum systems. Notably, within closed quantum many-body systems, entanglement is believed to yield emergent thermodynamic behavior.…

In the long-standing quest to reconcile gravity with quantum mechanics, profound connections have been unveiled between concepts traditionally pertaining to quantum information theory, such as entanglement, and constitutive features of…

High Energy Physics - Theory · Physics 2022-06-28 Eugenia Colafranceschi , Gerardo Adesso

Resolving unsteady transport phenomena in geometrically complex domains is traditionally constrained by polynomial scaling of computational cost with spatial resolution. While methods based on tensor-network data representations or…

Fluid Dynamics · Physics 2026-02-27 Lukas Gross , Elie Mounzer , David M. Wawrzyniak , Josef M. Winter , Nikolaus A. Adams

We show that a topological quantum computer based on the evaluation of a Witten-Reshetikhin-Turaev TQFT invariant of knots can always be arranged so that the knot diagrams with which one computes are diagrams of hyperbolic knots. The…

Quantum Physics · Physics 2023-05-08 Eric Samperton

The numerical simulation of two-dimensional quantum many-body systems away from equilibrium constitutes a major challenge for all known computational methods. We investigate the utility of Tree Tensor Network (TTN) states to solve the…

Quantum Physics · Physics 2025-05-13 Wladislaw Krinitsin , Niklas Tausendpfund , Markus Heyl , Matteo Rizzi , Markus Schmitt

We study the entanglement properties of the ground state in Kitaev's model. This is a two-dimensional spin system with a torus topology and nontrivial four-body interactions between its spins. For a generic partition $(A,B)$ of the lattice…

Quantum Physics · Physics 2007-05-23 A. Hamma , R. Ionicioiu , P. Zanardi

In this paper we study the effect of non-trivial spatial topology on quantum entanglement by examining the degenerate ground states of a topologically ordered system on torus. Using the string-net (fixed-point) wave-function, we propose a…

Strongly Correlated Electrons · Physics 2016-08-17 Zhu-Xi Luo , Yu-Ting Hu , Yong-Shi Wu

A novel algorithm based on the optimized decimation of tensor networks with super-orthogonalization (ODTNS) that can be applied to simulate efficiently and accurately not only the thermodynamic but also the ground state properties of…

Statistical Mechanics · Physics 2015-06-05 Shi-Ju Ran , Wei Li , Bin Xi , Zhe Zhang , Gang Su

We study the properties of entanglement in two-dimensional topologically ordered phases of matter. Such phases support anyons, quasiparticles with exotic exchange statistics. The emergent nonlocal state spaces of anyonic systems admit a…

Quantum Physics · Physics 2017-10-17 Parsa Bonderson , Christina Knapp , Kaushal Patel

Classification of possible quantum spin liquid (QSL) states of interacting spin-1/2's in two dimensions has been a fascinating topic of condensed matter for decades, resulting in enormous progress in our understanding of low-dimensional…

Strongly Correlated Electrons · Physics 2016-09-28 Hyunyong Lee , Jung Hoon Han

In this paper, we present the construction of tensor network states (TNS) for some of the degenerate ground states of 3D stabilizer codes. We then use the TNS formalism to obtain the entanglement spectrum and entropy of these ground-states…

Strongly Correlated Electrons · Physics 2023-01-23 Huan He , Yunqin Zheng , B. Andrei Bernevig , Nicolas Regnault

The structure of string-net lattice models, relevant as examples of topological phases, leads to a remarkably simple way of expressing their ground states as a tensor network constructed from the basic data of the underlying tensor…

Strongly Correlated Electrons · Physics 2009-03-01 O. Buerschaper , M. Aguado , G. Vidal

Periodic lattices in hyperbolic space are characterized by symmetries beyond Euclidean crystallographic groups, offering a new platform for classical and quantum waves, demonstrating great potentials for a new class of topological…

Mesoscale and Nanoscale Physics · Physics 2022-08-31 Nan Cheng , Francesco Serafin , James McInerney , Zeb Rocklin , Kai Sun , Xiaoming Mao

It has been recently shown how the tensorial nature of real-time path integrals involving the Feynman-Vernon influence functional can be utilized using matrix product states, taking advantage of the finite length of the non-Markovian…

Quantum Physics · Physics 2022-02-04 Amartya Bose

Subsystems of strongly disordered, interacting quantum systems can fail to thermalize because of the phenomenon of many-body localization (MBL). In this article, we explore a tensor network description of the eigenspectra of such systems.…

Disordered Systems and Neural Networks · Physics 2015-07-08 A. Chandran , J. Carrasquilla , I. H. Kim , D. A. Abanin , G. Vidal

Representing data in hyperbolic space can effectively capture latent hierarchical relationships. With the goal of enabling accurate classification of points in hyperbolic space while respecting their hyperbolic geometry, we introduce…

Machine Learning · Computer Science 2018-06-04 Hyunghoon Cho , Benjamin DeMeo , Jian Peng , Bonnie Berger