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Efficient methods to access the entanglement of a quantum many-body state, where the complexity generally scales exponentially with the system size $N$, have long a concern. Here we propose the Schmidt tensor network state (Schmidt TNS)…

Quantum Physics · Physics 2023-07-18 Peng-Fei Zhou , Ying Lu , Jia-Hao Wang , Shi-Ju Ran

Tensor networks, such as matrix product states (MPS) and tree tensor network states (TTNS), are powerful ans\"atze for simulating quantum dynamics. While both ans\"atze are theoretically exact in the limit of large bond dimensions, [J.…

Chemical Physics · Physics 2025-12-15 Weitang Li , Jiajun Ren , Jun Yan

This is a set of notes on some unrelated topics in mathematical physics, at varying levels of detail. First, I consider certain questions relating to the decay of correlation functions in matrix product states, in particular those generated…

Quantum Physics · Physics 2014-04-17 M. B. Hastings

Projected entangled pair states (PEPS) on finite two-dimensional lattices are a natural ansatz for representing ground states of local many-body Hamiltonians, as they inherently satisfy the boundary law of entanglement entropy. In this…

Strongly Correlated Electrons · Physics 2025-05-14 Daniel Alcalde Puente , Erik Lennart Weerda , Konrad Schröder , Matteo Rizzi

We study entanglement and other correlation properties of random states in high-dimensional bipartite systems. These correlations are quantified by parameters that are subject to the "concentration of measure" phenomenon, meaning that on a…

Quantum Physics · Physics 2007-05-23 Patrick Hayden , Debbie W. Leung , Andreas Winter

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

This paper introduces a Heisenberg picture approach to Matrix Product States (MPS), offering a rigorous yet intuitive framework to explore their structure and classification. MPS efficiently represent ground states of quantum many-body…

Mathematical Physics · Physics 2025-03-11 Abdessatar Souissi , Amenallah Andolsi

Tensor network states, and in particular projected entangled pair states (PEPS), suggest an innovative approach for the study of lattice gauge theories, both from a pure theoretic point of view, and as a tool for the analysis of the recent…

Quantum Physics · Physics 2016-04-12 Erez Zohar , Michele Burrello

A natural way to generalise tensor network variational classes to quantum field systems is via a continuous tensor contraction. This approach is first illustrated for the class of quantum field states known as continuous matrix-product…

Quantum Physics · Physics 2015-08-04 David Jennings , Christoph Brockt , Jutho Haegeman , Tobias J. Osborne , Frank Verstraete

Doubts have been raised on the representation of chiral spin liquids exhibiting topological order in terms of projected entangled pair states (PEPSs). Here, starting from a simple spin-1/2 chiral frustrated Heisenberg model, we show that a…

Strongly Correlated Electrons · Physics 2022-11-18 Juraj Hasik , Maarten Van Damme , Didier Poilblanc , Laurens Vanderstraeten

In continuous quantum field theories, the entanglement entropy of a subsystem with sharp corners on its boundary exhibits a universal corner-dependent contribution. We study this contribution through the lens of lattice discretization, and…

Quantum Physics · Physics 2026-05-29 Noa Feldman , Moshe Goldstein

Tensor networks are a powerful modeling framework developed for computational many-body physics, which have only recently been applied within machine learning. In this work we utilize a uniform matrix product state (u-MPS) model for…

Machine Learning · Computer Science 2021-04-26 Jacob Miller , Guillaume Rabusseau , John Terilla

We consider Projected Entangled Pair State (PEPS) models with a global $\mathbb Z_N$ symmetry, which are constructed from $\mathbb Z_N$-symmetric tensors and are thus $\mathbb Z_N$-invariant wavefunctions, and study the occurence of…

Statistical Mechanics · Physics 2017-08-15 Manuel Rispler , Kasper Duivenvoorden , Norbert Schuch

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 present a matrix product state (MPS) algorithm to approximate ground states of translationally invariant systems with periodic boundary conditions. For a fixed value of the bond dimension D of the MPS, we discuss how to minimize the…

Quantum Physics · Physics 2011-03-21 B. Pirvu , F. Verstraete , G. Vidal

Correlator product states (CPS) are a powerful and very broad class of states for quantum lattice systems whose amplitudes can be sampled exactly and efficiently. They work by gluing together states of overlapping clusters of sites on the…

Quantum Physics · Physics 2018-03-16 Stephen R. Clark

Two-dimensional Projected Entangled Pair States (PEPS) provide a unique framework giving access to detailed entanglement features of correlated (spin or electronic) systems. For a bi-partitioned quantum system, it has been argued that the…

Strongly Correlated Electrons · Physics 2015-06-22 Didier Poilblanc

We investigate the use of matrix product states (MPS) to approximate ground states of critical quantum spin chains with periodic boundary conditions (PBC). We identify two regimes in the (N,D) parameter plane, where N is the size of the…

Statistical Mechanics · Physics 2013-02-08 B. Pirvu , G. Vidal , F. Verstraete , L. Tagliacozzo

We introduce a new paradigm for scaling simulations with projected entangled-pair states (PEPS) for critical strongly-correlated systems, allowing for reliable extrapolations of PEPS data with relatively small bond dimensions $D$. The key…

Quantum Physics · Physics 2022-11-23 Bram Vanhecke , Juraj Hasik , Frank Verstraete , Laurens Vanderstraeten

Tensor network states provide successful descriptions of strongly correlated quantum systems with applications ranging from condensed matter physics to cosmology. Any family of tensor network states possesses an underlying entanglement…

Quantum Physics · Physics 2020-09-30 Matthias Christandl , Angelo Lucia , Péter Vrana , Albert H. Werner