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Related papers: Exact diagonalization: the Bose-Hubbard model as a…

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The graph Laplacian, a typical representation of a network, is an important matrix that can tell us much about the network structure. In particular its eigenpairs (eigenvalues and eigenvectors) incubate precious topological information…

Numerical Analysis · Mathematics 2013-11-08 Luca Bergamaschi , Enrico Bozzo , Massimo Franceschet

We propose a new non-perturbative technique for calculating the field-theory S-matrix directly from the eigenstates of the Hamiltonian. Our method involves a discretized momentum space and a momentum cutoff, thereby truncating the Hilbert…

High Energy Physics - Phenomenology · Physics 2017-10-10 Neil Christensen

A new procedure is constructed by means of APS in APLAN language. The procedure solves the initial-value problem for linear differential equations of order $k$ with polynomial coefficients and regular singularity in the initialization point…

Numerical Analysis · Mathematics 2007-05-23 P. N. Denisenko

Correlated quantum many-body phenomena in lattice models have been identified as a set of physically interesting problems that cannot be solved classically. Analog quantum simulators, in photonics and microwave superconducting circuits,…

Quantum Physics · Physics 2023-10-24 Abhi Saxena , Erfan Abbasgholinejad , Arka Majumdar , Rahul Trivedi

We develop a variational method to obtain many-body ground states of the Bose-Hubbard model using feedforward artificial neural networks. A fully-connected network with a single hidden layer works better than a fully-connected network with…

Disordered Systems and Neural Networks · Physics 2018-01-17 Hiroki Saito , Masaya Kato

The Fermi-Hubbard model is of fundamental importance in condensed-matter physics, yet is extremely challenging to solve numerically. Finding the ground state of the Hubbard model using variational methods has been predicted to be one of the…

Quantum Physics · Physics 2021-01-04 Chris Cade , Lana Mineh , Ashley Montanaro , Stasja Stanisic

We introduce a unitary matrix-product operator (UMPO) based variational method that approximately finds all the eigenstates of fully many-body localized (fMBL) one-dimensional Hamiltonians. The computational cost of the variational…

Strongly Correlated Electrons · Physics 2016-08-03 Frank Pollmann , Vedika Khemani , J. Ignacio Cirac , S. L. Sondhi

The discretization approximation method commonly used to simulate the dynamics of quantum system coupled to the environment in continuum often suffers from the periodically partial recovery of initial state because of the effect of finite…

Quantum Physics · Physics 2025-05-07 H. T. Cui , Y. A. Yan , M. Qin , X. X. Yi

This paper proposes a Newton-type method to solve numerically the eigenproblem of several diagonalizable matrices, which pairwise commute. A classical result states that these matrices are simultaneously diagonalizable. From a suitable…

Numerical Analysis · Mathematics 2022-11-07 Rima Khouja , Bernard Mourrain , Jean-Claude Yakoubsohn

We calculate explicitly the Bethe vectors states by the algebraic Bethe ansatz method with the $gl(2)$-invariant $R$-matrix for the two-site Bose-Hubbard model. Using a binomial expansion of the n-th power of a sum of two operators we get…

Mathematical Physics · Physics 2015-05-21 Gilberto Santos , Changrim Ahn , Angela Foerster , Itzhak Roditi

Bernstein polynomials, long a staple of approximation theory and computational geometry, have also increasingly become of interest in finite element methods. Many fundamental problems in interpolation and approximation give rise to…

Numerical Analysis · Mathematics 2019-07-15 Larray Allen , Robert C. Kirby

One of the most used approaches in simulating materials is the tight-binding approximation. When using this method in a material simulation, it is necessary to compute the eigenvalues and eigenvectors of the Hamiltonian describing the…

Numerical Analysis · Computer Science 2009-10-29 Matthias Petschow , Edoardo Di Napoli , Paolo Bientinesi

Density Matrix Exponentiation is a technique for simulating Hamiltonian dynamics when the Hamiltonian to be simulated is available as a quantum state. In this paper, we present a natural analogue to this technique, for simulating Markovian…

Quantum Physics · Physics 2023-09-06 Dhrumil Patel , Mark M. Wilde

Gradient methods are frequently used in large scale image deblurring problems since they avoid the onerous computation of the Hessian matrix of the objective function. Second order information is typically sought by a clever choice of the…

Numerical Analysis · Mathematics 2015-11-19 Federica Porta , Marco Prato , Luca Zanni

A method is proposed to improve the accuracy of approximate techniques for strongly correlated electrons that use reduced Hilbert spaces. As a first step, the method involves a change of basis that incorporates exactly part of the short…

Statistical Mechanics · Physics 2009-10-30 E. Dagotto , G. B. Martins , J. Riera , A. L. Malvezzi , C. Gazza

We investigate ground state properties of a quasi-one-dimensional electron-lattice coupled model for quarter-filled molecular conductors. The effective one-dimensional extended Hubbard model coupled to adiabatic lattice degree of freedom is…

Strongly Correlated Electrons · Physics 2009-04-23 Yuichi Otsuka , Hitoshi Seo , Yukitoshi Motome , Takeo Kato

A model Hamiltonian is proposed in order to understand the localization-delocalization transition in a quantum dot, where there are two gate voltages: top and side. Considering energetically favorable degrees of freedom only, we achieve a…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Myung-Hoon Chung

A Bose-Hubbard model on a dynamical lattice was introduced in previous work as a spin system analogue of emergent geometry and gravity. Graphs with regions of high connectivity in the lattice were identified as candidate analogues of…

High Energy Physics - Theory · Physics 2015-05-30 Francesco Caravelli , Alioscia Hamma , Fotini Markopoulou , Arnau Riera

We propose a general framework that leads to one-dimensional XX and Hubbard models in full generality, based on the decomposition of an arbitrary vector space (possibly infinite dimensional) into a direct sum of two subspaces, the two…

Mathematical Physics · Physics 2015-05-13 G. Feverati , L. Frappat , E. Ragoucy

A new iterative method for solving large scale symmetric nonlinear eigenvalue problems is presented. We firstly derive an infinite dimensional symmetric linearization of the nonlinear eigenvalue problem, then we apply the indefinite Lanczos…

Numerical Analysis · Mathematics 2019-10-11 Giampaolo Mele