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The quantum many-body problem is an important topic in condensed matter physics. To efficiently solve the problem, several methods have been developped to improve the representation ability of wave-functions. For the Fermi-Hubbard model…

Strongly Correlated Electrons · Physics 2024-06-05 Yu-Tong Zhou , Zheng-Wei Zhou , Xiao Liang

Tensor networks have in recent years emerged as the powerful tools for solving the large-scale optimization problems. One of the most popular tensor network is tensor train (TT) decomposition that acts as the building blocks for the…

Numerical Analysis · Computer Science 2016-06-20 Qibin Zhao , Guoxu Zhou , Shengli Xie , Liqing Zhang , Andrzej Cichocki

A tensor network is a type of decomposition used to express and approximate large arrays of data. A given data-set, quantum state or higher dimensional multi-linear map is factored and approximated by a composition of smaller multi-linear…

Quantum Physics · Physics 2022-07-08 Richik Sengupta , Soumik Adhikary , Ivan Oseledets , Jacob Biamonte

We propose a method of simulating efficiently many-body interacting fermion lattice models in trapped ions, including highly nonlinear interactions in arbitrary spatial dimensions and for arbitrarily distant couplings. We map products of…

Quantum Physics · Physics 2015-05-30 J. Casanova , A. Mezzacapo , L. Lamata , E. Solano

We examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not…

Quantum Physics · Physics 2015-03-17 Jacob D. Biamonte , Stephen R. Clark , Dieter Jaksch

We extend the theory of fast Fourier transforms on finite groups to finite inverse semigroups. We use a general method for constructing the irreducible representations of a finite inverse semigroup to reduce the problem of computing its…

Group Theory · Mathematics 2011-08-02 Martin Malandro

A new approach for the parallel forward modeling of transient electromagnetic (TEM) fields is presented. It is based on a family of uniform-in-time rational approximants to the matrix exponential that share a common denominator independent…

Numerical Analysis · Mathematics 2025-06-16 Ralph-Uwe Börner , Stefan Güttel

How best to think about quantum systems under permutation invariance is a question that has received a great deal of attention in the literature. But very little attention has been paid to taking seriously the proposal that permutation…

Quantum Physics · Physics 2014-09-02 Adam Caulton

We adapt the bialgebra and Hopf relations to expose internal structure in the ground state of a Hamiltonian with $Z_2$ topological order. Its tensor network description allows for exact contraction through simple diagrammatic rewrite rules.…

Quantum Physics · Physics 2011-12-08 S. J. Denny , J. D. Biamonte , D. Jaksch , S. R. Clark

We present a unified framework to describe lattice gauge theories by means of tensor networks: this framework is efficient as it exploits the high amount of local symmetry content native of these systems describing only the gauge invariant…

Quantum Physics · Physics 2014-10-14 Pietro Silvi , Enrique Rico , Tommaso Calarco , Simone Montangero

Quantum simulation of chemical Hamiltonians enables the efficient calculation of chemical properties. Mapping is one of the essential steps in simulating fermionic systems on quantum computers. In this work, a unified framework of…

Quantum Physics · Physics 2022-10-11 Qing-Song Li , Huan-Yu Liu , Qingchun Wang , Yu-Chun Wu , Guo-Ping Guo

The design and application of regression-free tensor network representations for integration is presented. Tensor network methods are demonstrated to outperform Monte Carlo for test problems, and exponential convergence is shown to be…

Numerical Analysis · Mathematics 2022-02-22 Sebastian Cassel

A network representation is useful for describing the structure of a large variety of complex systems. However, most real and engineered systems have multiple subsystems and layers of connectivity, and the data produced by such systems is…

Tensor Networks (TNs) are a computational paradigm used for representing quantum many-body systems. Recent works have shown how TNs can also be applied to perform Machine Learning (ML) tasks, yielding comparable results to standard…

High Energy Physics - Experiment · Physics 2024-09-26 Lorenzo Borella , Alberto Coppi , Jacopo Pazzini , Andrea Stanco , Marco Trenti , Andrea Triossi , Marco Zanetti

We show how to map local fermionic problems onto local spin problems on a lattice in any dimension. The main idea is to introduce auxiliary degrees of freedom, represented by Majorana fermions, which allow us to extend the Jordan-Wigner…

Strongly Correlated Electrons · Physics 2011-02-16 F. Verstraete , J. I. Cirac

Learning workable representations of dynamical systems is becoming an increasingly important problem in a number of application areas. By leveraging recent work connecting deep neural networks to systems of differential equations, we…

Machine Learning · Statistics 2020-03-03 Steindor Saemundsson , Alexander Terenin , Katja Hofmann , Marc Peter Deisenroth

We write down a class of two-dimensional quantum spin-1/2 Hamiltonians whose eigenspectra are exactly solvable via the Jordan-Wigner transformation. The general structure corresponds to a suitable grid composed of XY or XX-Ising spin chains…

Strongly Correlated Electrons · Physics 2025-09-03 Sumiran Pujari

The Jordan-Wigner transformation is known as a powerful tool in condensed matter theory, especially in the theory of low-dimensional quantum spin systems. The aim of this chapter is to review the application of the Jordan-Wigner…

Strongly Correlated Electrons · Physics 2016-11-23 Oleg Derzhko

The purpose of this overview article, which can be viewed as a supplement to our previous review on quantum rings, [S. Viefers {\it et al}, Physica E {\bf 21} (2004), 1-35], is to highlight the differences of boson and fermion systems in…

Mesoscale and Nanoscale Physics · Physics 2012-10-03 M. Manninen , S. Viefers , S. M. Reimann

We report on the calculation of the symmetry resolved entanglement entropies in two-dimensional many-body systems of free bosons and fermions by \emph{dimensional reduction}. When the subsystem is translational invariant in a transverse…

Statistical Mechanics · Physics 2020-08-11 Sara Murciano , Paola Ruggiero , Pasquale Calabrese