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This brief review introduces the reader to tensor network methods, a powerful theoretical and numerical paradigm spawning from condensed matter physics and quantum information science and increasingly exploited in different fields of…

Quantum Physics · Physics 2022-01-24 S. Montangero , E. Rico , P. Silvi

Open quantum systems are central to quantum optics, condensed matter, and chemistry, yet their simulation remains challenging for both classical and near-term quantum hardware. In this work we implement and execute utility-scale quantum…

Quantum Physics · Physics 2026-05-26 Benjamin Tirado , Joana Fraxanet , Adrián Juan-Delgado , Javier Aizpurua , Ruben Esteban

We introduce a simple yet significant improvement to the time-evolving block decimation (TEBD) tensor network algorithm for simulating the time dynamics of strongly correlated one-dimensional (1D) mixed quantum states. The efficiency of 1D…

Quantum Physics · Physics 2026-05-19 Sayak Guha Roy , Kevin Slagle

Information networks are ubiquitous and are ideal for modeling relational data. Networks being sparse and irregular, network embedding algorithms have caught the attention of many researchers, who came up with numerous embeddings algorithms…

Machine Learning · Computer Science 2020-09-25 Junshan Wang , Yilun Jin , Guojie Song , Xiaojun Ma

Tensor network methods have demonstrated their suitability for the study of equilibrium properties of lattice gauge theories, even close to the continuum limit. We use them in an out-of-equilibrium scenario, much less explored so far, by…

High Energy Physics - Lattice · Physics 2025-03-24 Irene Papaefstathiou , Johannes Knolle , Mari Carmen Bañuls

The description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. On the other hand, the time evolution of quantum states is a natural application for quantum computers…

Quantum Physics · Physics 2025-08-20 Ronen Weiss , Alessandro Baroni , Joseph Carlson , Ionel Stetcu

Classical network embeddings create a low dimensional representation of the learned relationships between features across nodes. Such embeddings are important for tasks such as link prediction and node classification. In the current paper,…

Artificial Intelligence · Computer Science 2021-03-15 Chris Connell , Yang Wang

The study of correlation effects in topological phases of matter can benefit from a multidisciplinary approach that combines techniques drawn from condensed matter, high-energy physics and quantum information science. In this work, we…

Strongly Correlated Electrons · Physics 2022-09-19 E. Tirrito , S. Hands , A. Bermudez

We propose an improved approach to carry out the imaginary time evolution of infinite projected entangled-pair states (iPEPS), especially for systems with criticality. A cyclic optimal truncation is introduced to update the tensors along a…

Strongly Correlated Electrons · Physics 2020-09-02 Yi Zheng , Shuo Yang

The projected entangled pair states (PEPS) methods have been proved to be powerful tools to solve the strongly correlated quantum many-body problems in two-dimension. However, due to the high computational scaling with the virtual bond…

Quantum Physics · Physics 2017-05-31 Wen-Yuan Liu , Shao-Jun Dong , Yong-Jian Han , Guang-Can Guo , Lixin He

Low-rank tensor approximation approaches have become an important tool in the scientific computing community. The aim is to enable the simulation and analysis of high-dimensional problems which cannot be solved using conventional methods…

Numerical Analysis · Mathematics 2019-02-26 Patrick Gelß , Stefan Klus , Sebastian Matera , Christof Schütte

We present a fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of systems with long-range interactions that reproduces the dynamics of a standard implementation exactly, i.e., the generated configurations and…

Computational Physics · Physics 2023-07-27 Fabio Müller , Henrik Christiansen , Stefan Schnabel , Wolfhard Janke

In a recent preprint [1] (arXiv:2503.05693), Tindall et al. presented impressive classical simulations of quantum dynamics using tensor networks. Their methods represent a significant improvement in the classical state of the art, and in…

Tensor-network simulations of quantum many-body dynamics are fundamentally limited by entanglement build-up, which leads to exponentially growing computational costs. Furthermore, these classical simulation algorithms are inherently…

Quantum Physics · Physics 2026-04-16 Fredrik Hasselgren , Bálint Koczor

We develop and implement new probabilistic strategy for proving basic results about long time behaviour for interacting diffusion processes on unbounded lattice. The concept of the solution used is rather weak as we construct the process as…

Probability · Mathematics 2016-11-08 Frantisek Zak

Using a map between the Lindbladian evolution of dephasing in free fermions and the time evolution of imaginary-interaction Fermi-Hubbard models in bipartite lattices, we present an efficient classical algorithm to solve the Schr\"{o}dinger…

Quantum Physics · Physics 2026-01-21 Raul A. Santos

In this paper, we consider modelling interaction between a set of variables in the context of time series and high dimension. We suggest two approaches. The first is similar to the neighborhood lasso when the lasso model is replaced by a…

Machine Learning · Statistics 2019-08-05 Kamel Jebreen , Badih Ghattas

Motivated by the experimental realisation of the two-dimensional triangular spin lattice at the National Instate of Standards and Technology in 2012, we developed a new algorithm which allows a time evolution of an MPS with a Hamiltonian…

Strongly Correlated Electrons · Physics 2020-08-27 Tomohiro Hashizume

We study a means of creating multiparticle entanglement of neutral atoms using pairwise controlled dipole-dipole interactions in a three dimensional optical lattice. For tightly trapped atoms the dipolar interaction energy can be much…

Quantum Physics · Physics 2009-10-31 G. K. Brennen , I. H. Deutsch , P. S. Jessen

Simulating many-body quantum systems on a classical computer is difficult due to the large number of degrees of freedom, causing the computational complexity to grow exponentially with system size. Tensor Networks (TN) is a framework that…

Quantum Physics · Physics 2026-03-17 Nir Gutman
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