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A modified density matrix renormalization group (DMRG) algorithm is applied to the zigzag spin-1/2 chain with frustrated antiferromagnetic exchange $J_1$, $J_2$ between first and second neighbors. The modified algorithm yields accurate…

Strongly Correlated Electrons · Physics 2015-05-18 Manoranjan Kumar , Zoltan G. Soos , Diptiman Sen , S. Ramasesha

We propose that an unsharp measurement-based process to generate genuine multipartite entanglement from an entangled initial state with a fewer number of qubits can be classified in two ways -- biased and unbiased inflation protocols. In…

Quantum Physics · Physics 2022-08-22 Pritam Halder , Ratul Banerjee , Shiladitya Mal , Aditi Sen De

An interpolation error is an integral of the squared error of a regression model over a domain of interest. We consider the interpolation error for the case of misspecified Gaussian process regression: used covariance function differs from…

Statistics Theory · Mathematics 2018-03-28 A. Zaytsev , E. Romanenkova , D. Ermilov

For a class of parametric modal regression models with measurement error, a simulation extrapolation estimation procedure is proposed in this paper for estimating the modal regression coefficients. Large sample properties of the proposed…

Methodology · Statistics 2019-10-04 Jianhong Shi , Yujing Zhang , Ping Yu , Weixing Song

We propose a new combined approach of the exact diagonalization, the renormalization group and the Bethe ansatz for precise estimates of the charge gap $\Delta$ in the one-dimensional extended Hubbard model with the onsite and the…

Strongly Correlated Electrons · Physics 2015-06-25 K. Sano , Y. Ono

To overcome the limitations of the traditional state-averaging approaches in excited state calculations, where one solves for and represents all states between the ground state and excited state of interest, we have investigated a number of…

Strongly Correlated Electrons · Physics 2009-11-13 Jonathan J. Dorando , Johannes Hachmann , Garnet Kin-Lic Chan

We combine the Density Matrix Renormalization Group (DMRG) with Matrix Product State tangent space concepts to construct a variational algorithm for finding ground states of one dimensional quantum lattices in the thermodynamic limit. A…

Quantum Physics · Physics 2019-04-22 V. Zauner-Stauber , L. Vanderstraeten , M. T. Fishman , F. Verstraete , J. Haegeman

We extend the previous study of extracting crystalline symmetry-protected topological invariants to the correlated regime. We construct the interacting Hofstadter model defined on square lattice with the rotation and translation symmetry…

Strongly Correlated Electrons · Physics 2026-01-06 Lu Zhang , Min Long , Yuxuan Zhang , Zi Yang Meng , Xue-Yang Song

We use a density matrix renormalization group method to study quantitatively the phase diagram of a one-dimensional extended Hubbard model at half-filling by investigating the correlation functions and structure factors. We confirm the…

Strongly Correlated Electrons · Physics 2007-05-23 Y. Z. Zhang

An extrapolation method in shell model calculations with deformed basis is presented, which uses a scaling property of energy and energy variance for a series of systematically approximated wave functions to the true one. Such approximated…

Nuclear Theory · Physics 2009-11-10 Takahiro Mizusaki

Learning the closest matrix product state (MPS) representation of a quantum state enables useful tools for quantum machine learning and analysis of complex quantum systems. In this work, we study the problem of learning MPS in the following…

Quantum Physics · Physics 2026-05-21 Chia-Ying Lin , Nai-Hui Chia , Shih-Han Hung

We use the density matrix renormalization group (DMRG) for transfer matrices to numerically calculate impurity corrections to thermodynamic properties. The method is applied to two impurity models in the spin-1/2 chain, namely a weak link…

Strongly Correlated Electrons · Physics 2009-10-31 Stefan Rommer , Sebastian Eggert

We propose a simple modification of the density matrix renormalization group (DMRG) method in order to tackle strongly disordered quantum spin chains. Our proposal, akin to the idea of the adaptive time-dependent DMRG, enables us to reach…

Strongly Correlated Electrons · Physics 2018-11-14 J. C. Xavier , J. A. Hoyos , E. Miranda

I present a density-matrix renormalization-group (DMRG) method for calculating dynamical properties and excited states in low-dimensional lattice quantum many-body systems. The method is based on an exact variational principle for dynamical…

Strongly Correlated Electrons · Physics 2009-11-07 Eric Jeckelmann

The magnetic susceptibility of the quarter-filled one-dimensional extended Hubbard model is calculated using the density-matrix renormalization group technique. It is found that in the charge gap regime of the model ($U> 4t $ and $V > 2t$),…

Strongly Correlated Electrons · Physics 2007-05-23 S. Moukouri

To facilitate the numerical analysis of particle methods, we derive truncation error estimates for the approximate operators in a generalized particle method. Here, a generalized particle method is defined as a meshfree numerical method…

Numerical Analysis · Mathematics 2019-07-09 Yusuke Imoto

We introduce a Lagrangian formulation of the Density Matrix Renormalization Group (DMRG). We present Lagrangians which when minimised yield the optimal DMRG wavefunction in a variational sense, both within the general matrix product ansatz,…

Strongly Correlated Electrons · Physics 2008-04-11 Garnet Kin-Lic Chan

Accurate determinations of the MS-bar b-quark mass $m_b(m_b)$ from $\sigma(e^+e^-\to{\rm hadrons})$ experimental data currently contain three comparable sources of uncertainty; the experimental uncertainty from moments of this…

High Energy Physics - Phenomenology · Physics 2009-11-10 M. R. Ahmady , V. Elias , A. Squires , T. G. Steele , Ailin Zhang

The Density Matrix Renormalization Group (DMRG) method with periodic boundary conditions is introduced for two dimensional classical spin models. It is shown that this method is more suitable for derivation of the properties of infinite 2D…

Statistical Mechanics · Physics 2009-10-31 Andrej Gendiar , Anton Surda

Diffusion probabilistic models (DPMs), while effective in generating high-quality samples, often suffer from high computational costs due to their iterative sampling process. To address this, we propose an enhanced ODE-based sampling method…

Machine Learning · Computer Science 2025-04-03 Jinyoung Choi , Junoh Kang , Bohyung Han