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Strongly correlated layered 2D systems are of central importance in condensed matter physics, but their numerical study is very challenging. Motivated by the enormous successes of tensor networks for 1D and 2D systems, we develop an…

Strongly Correlated Electrons · Physics 2023-04-05 Patrick C. G. Vlaar , Philippe Corboz

Simulation of quantum systems is challenging due to the exponential size of the state space. Tensor networks provide a systematically improvable approximation for quantum states. 2D tensor networks such as Projected Entangled Pair States…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-04 Yuchen Pang , Tianyi Hao , Annika Dugad , Yiqing Zhou , Edgar Solomonik

Infinite projected entangled-pair states (iPEPS) provide a powerful tool for studying strongly correlated systems directly in the thermodynamic limit. A core component of the algorithm is the approximate contraction of the iPEPS, where the…

Strongly Correlated Electrons · Physics 2026-05-12 Yining Zhang , Qi Yang , Philippe Corboz

The approximate contraction of a Projected Entangled Pair States (PEPS) tensor network is a fundamental ingredient of any PEPS algorithm, required for the optimization of the tensors in ground state search or time evolution, as well as for…

Quantum Physics · Physics 2014-04-08 Michael Lubasch , J. Ignacio Cirac , Mari-Carmen Bañuls

Projected Entangled Pair States (PEPS) are a promising ansatz for the study of strongly correlated quantum many-body systems in two dimensions. But due to their high computational cost, developing and improving PEPS algorithms is necessary…

Quantum Physics · Physics 2014-09-05 Michael Lubasch , J. Ignacio Cirac , Mari-Carmen Bañuls

An accurate calculation of the properties of quantum many-body systems is one of the most important yet intricate challenges of modern physics and computer science. In recent years, the tensor network ansatz has established itself as one of…

Quantum Physics · Physics 2020-01-08 Jonas Haferkamp , Dominik Hangleiter , Jens Eisert , Marek Gluza

Calculation of observables with three-dimensional projected entangled pair states is generally hard, as it requires a contraction of complex multi-layer tensor networks. We utilize the multi-layer structure of these tensor networks to…

Strongly Correlated Electrons · Physics 2024-08-21 Illia Lukin , Andrii Sotnikov

An extension of the projected entangled-pair states (PEPS) algorithm to infinite systems, known as the iPEPS algorithm, was recently proposed to compute the ground state of quantum systems on an infinite two-dimensional lattice. Here we…

Strongly Correlated Electrons · Physics 2013-05-29 Roman Orus , Guifre Vidal

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)…

Projected Entangled Pair States (PEPS) are a class of quantum many-body states that generalize Matrix Product States for one-dimensional systems to higher dimensions. In recent years, PEPS have advanced understanding of strongly correlated…

Strongly Correlated Electrons · Physics 2025-01-13 Siddhartha Patra , Sukhbinder Singh , Román Orús

We present an improved version of the algorithm contracting and optimizing finite projected entangled pair states (fPEPS) in conjunction with projected entangled pair operators (PEPOs). Our work has two components to it. First, we explain…

Strongly Correlated Electrons · Physics 2025-11-04 Markus Scheb

The infinite projected entangled pair states (iPEPS) technique [J. Jordan {\it et al.}, Phys. Rev. Lett. {\bf 101}, 250602 (2008)] has been widely used in the recent years to assess the properties of two-dimensional quantum systems, working…

Strongly Correlated Electrons · Physics 2019-08-23 Juraj Hasik , Federico Becca

A typical quantum state obeying the area law for entanglement on an infinite 2D lattice can be represented by a tensor network ansatz -- known as an infinite projected entangled pair state (iPEPS) -- with a finite bond dimension $D$. Its…

Strongly Correlated Electrons · Physics 2018-07-11 Piotr Czarnik , Jacek Dziarmaga

Tensor networks capture large classes of ground states of phases of quantum matter faithfully and efficiently. Their manipulation and contraction has remained a challenge over the years, however. For most of the history, ground state…

Strongly Correlated Electrons · Physics 2024-09-11 Jan Naumann , Erik Lennart Weerda , Matteo Rizzi , Jens Eisert , Philipp Schmoll

Being able to describe accurately the dynamics and steady-states of driven and/or dissipative but quantum correlated lattice models is of fundamental importance in many areas of science: from quantum information to biology. An efficient…

Quantum Physics · Physics 2021-05-19 Conor Mc Keever , Marzena H. Szymańska

The infinite Projected Entangled-Pair State (iPEPS) algorithm is one of the most efficient techniques for studying the ground-state properties of two-dimensional quantum lattice Hamiltonians in the thermodynamic limit. Here, we show how the…

Strongly Correlated Electrons · Physics 2018-04-04 Saeed S. Jahromi , Roman Orus , Mehdi Kargarian , Abdollah Langari

We present a general graph-based Projected Entangled-Pair State (gPEPS) algorithm to approximate ground states of nearest-neighbor local Hamiltonians on any lattice or graph of infinite size. By introducing the structural-matrix which…

Strongly Correlated Electrons · Physics 2019-05-08 Saeed S. Jahromi , Roman Orus

Projected entangled-pair states (PEPS) have become a powerful tool for studying quantum many-body systems in the condensed matter and quantum materials context, particularly with advances in variational energy optimization methods. A key…

Strongly Correlated Electrons · Physics 2025-06-10 Jan Naumann , Erik Lennart Weerda , Jens Eisert , Matteo Rizzi , Philipp Schmoll

We propose a pair of approximations that allows the leading order computational cost of contracting an infinite projected entangled-pair state (iPEPS) to be reduced from $\mathcal{O}(\chi^3D^6)$ to $\mathcal{O}(\chi^3D^3)$ when using a…

Quantum Physics · Physics 2023-06-16 Wangwei Lan , Glen Evenbly

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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