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Related papers: Tensor-product representations for string-net cond…

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In recent years, interest in expressing the success of neural networks to the quantum computing has increased significantly. Tensor network theory has become increasingly popular and widely used to simulate strongly entangled correlated…

Quantum Physics · Physics 2019-05-07 Amandeep Singh Bhatia , Mandeep Kaur Saggi , Ajay Kumar , Sushma Jain

Particle systems admit a variety of tensor product structures (TPSs) depending on the algebra of observables chosen for analysis. Global symmetry transformations and dynamical transformations may be resolved into local unitary operators…

Quantum Physics · Physics 2009-11-13 N. L. Harshman , S. Wickramasekara

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

Tensor network states are used to approximate ground states of local Hamiltonians on a lattice in D spatial dimensions. Different types of tensor network states can be seen to generate different geometries. Matrix product states (MPS) in…

Quantum Physics · Physics 2012-03-02 G. Evenbly , G. Vidal

We obtain an exact matrix-product-state (MPS) representation of a large series of fractional quantum Hall (FQH) states in various geometries of genus 0. The states in question include all paired k=2 Jack polynomials, such as the Moore-Read…

Strongly Correlated Electrons · Physics 2013-06-03 B. Estienne , Z. Papic , N. Regnault , B. A. Bernevig

We formalize and generalize the concept of a topological state-sum construction using the language of tensor networks. We give examples for constructions that are possibly more general than all state-sum constructions in the literature that…

Strongly Correlated Electrons · Physics 2019-09-09 Andreas Bauer

These lecture notes provide a brief overview of methods of entanglement theory applied to the study of quantum many-body systems, as well as of tensor network states capturing quantum states naturally appearing in condensed-matter systems.

Quantum Physics · Physics 2013-10-07 J. Eisert

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

Canonical forms are central to the analytical understanding of tensor network states, underpinning key results such as the complete classification of one-dimensional symmetry-protected topological phases within the matrix product state…

In this article we present analytical results on the exact tensor network representations and correlation functions of the first examples of 2D ground states with quantum phase transitions between area law and extensive entanglement…

Quantum Physics · Physics 2025-03-26 Olai B. Mykland , Zhao Zhang

We investigate ensembles of Matrix Product States (MPSs) generated by quantum circuit evolution followed by projection onto MPSs with a fixed bond dimension $\chi$. Specifically, we consider ensembles produced by: (i) random sequential…

Quantum Physics · Physics 2025-01-20 Hugo Lóio , Guillaume Cecile , Sarang Gopalakrishnan , Guglielmo Lami , Jacopo De Nardis

Projected entangled pair states (PEPS) offer memory-efficient representations of some quantum many-body states that obey an entanglement area law, and are the basis for classical simulations of ground states in two-dimensional (2d)…

In this study, we introduce a novel family of tensor networks, termed constrained matrix product states (MPS), designed to incorporate exactly arbitrary discrete linear constraints, including inequalities, into sparse block structures.…

Numerical Analysis · Mathematics 2025-07-10 Javier Lopez-Piqueres , Jing Chen

Matrix Product States (MPSs) provide a powerful framework to study and classify gapped quantum phases --symmetry-protected topological (SPT) phases in particular--defined in one dimensional lattices. On the other hand, it is natural to…

Strongly Correlated Electrons · Physics 2017-04-24 Ken Shiozaki , Shinsei Ryu

Understanding the quantum evolution of light in nonlinear media is central to the development of next-generation quantum technologies. Yet modeling these processes remains computationally demanding, as the required resources grow rapidly…

Quantum Physics · Physics 2025-11-25 Nikolay Kapridov , Egor Tiunov , Dmitry Chermoshentsev

The Minimally Entangled Typical Thermal States (METTS) are an ensemble of pure states, equivalent to the Gibbs thermal state, that can be efficiently represented by tensor networks. In this article, we use the Projected Entangled Pair…

Quantum Physics · Physics 2024-01-25 Aritra Sinha , Marek M. Rams , Jacek Dziarmaga

The truncation or compression of the spectrum of Schmidt values is inherent to the matrix product state (MPS) approximation of one-dimensional quantum ground states. We provide a renormalization group picture by interpreting this…

Quantum Physics · Physics 2016-11-23 Matthias Bal , Marek M. Rams , Valentin Zauner , Jutho Haegeman , Frank Verstraete

Quantum entanglement is a particularly useful characterization of topological orders which lack conventional order parameters. In this work, we study the entanglement in topologically ordered states between two arbitrary spatial regions,…

Strongly Correlated Electrons · Physics 2023-08-01 Chao Yin , Shang Liu

It is believed that most (perhaps all) gapped phases of matter can be described at long distances by Topological Quantum Field Theory (TQFT). On the other hand, it has been rigorously established that in 1+1d ground states of gapped…

Strongly Correlated Electrons · Physics 2019-11-05 Anton Kapustin , Alex Turzillo , Minyoung You

Tensor networks, a model that originated from quantum physics, has been gradually generalized as efficient models in machine learning in recent years. However, in order to achieve exact contraction, only tree-like tensor networks such as…

Computer Vision and Pattern Recognition · Computer Science 2021-03-17 Song Cheng , Lei Wang , Pan Zhang
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