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A numerical approach to ground-state dynamical correlation functions from Density Matrix Renormalization Group (DMRG) is developed. Using sum rules, moments of a dynamic correlation function can be calculated with DMRG, and with the moments…

Condensed Matter · Physics 2016-08-31 Hanbin Pang , H. Akhlaghpour , M. Jarrell

The density matrix renormalization group (DMRG) method has already proved itself as a very efficient and accurate computational method, which can treat large active spaces and capture the major part of strong correlation. Its application on…

Chemical Physics · Physics 2022-10-31 Pavel Beran , Katarzyna Pernal , Fabijan Pavosevic , Libor Veis

We develop a correction to the density matrix used in density matrix renormalization group calculations to take into account the incompleteness of the environment block. The correction allows successful calculations using only a single site…

Strongly Correlated Electrons · Physics 2016-08-31 Steven R. White

Obtaining accurate representations of the eigenstates of an array of coupled superconducting qubits is a crucial step in the design of circuit quantum electrodynamics (QED)-based quantum processors. However, exact diagonalization of the…

We present an efficient implementation of the Density Matrix Renormalization Group (DMRG) algorithm that includes an optimal ordering of the proton and neutron orbitals and an efficient expansion of the active space utilizing various…

Nuclear Theory · Physics 2015-11-18 Ö. Legeza , L. Veis , A. Poves , J. Dukelsky

In decentralized learning, a network of nodes cooperate to minimize an overall objective function that is usually the finite-sum of their local objectives, and incorporates a non-smooth regularization term for the better generalization…

Machine Learning · Computer Science 2022-01-25 Xuanjie Li , Yuedong Xu , Jessie Hui Wang , Xin Wang , John C. S. Lui

We have devised and implemented a local ab initio Density Matrix Renormalization Group (DMRG) algorithm to describe multireference nondynamic correlations in large systems. For long molecules that are extended in one of their spatial…

Strongly Correlated Electrons · Physics 2009-11-11 Johannes Hachmann , Wim Cardoen , Garnet Kin-Lic Chan

Trajectory optimization considers the problem of deciding how to control a dynamical system to move along a trajectory which minimizes some cost function. Differential Dynamic Programming (DDP) is an optimal control method which utilizes a…

Systems and Control · Computer Science 2017-01-10 David D. Fan , Evangelos A. Theodorou

A biorthonormal-block density-matrix renormalization group algorithm is proposed to accurately compute properties of large-scale non-Hermitian many-body systems, in which a renormalized-space partition of the non-Hermitian reduced density…

Strongly Correlated Electrons · Physics 2025-07-08 Peigeng Zhong , Wei Pan , Haiqing Lin , Xiaoqun Wang , Shijie Hu

Finite-temperature transport properties of one-dimensional systems can be studied using the time dependent density matrix renormalization group via the introduction of auxiliary degrees of freedom which purify the thermal statistical…

Strongly Correlated Electrons · Physics 2013-09-09 C. Karrasch , J. H. Bardarson , J. E. Moore

Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be efficient in solving high dimensional problems. Even though…

Artificial Intelligence · Computer Science 2009-12-02 Nicolas A. Barriga , Mauricio Araya-López

Given a Hamiltonian with a continuous symmetry one can generally factorize that symmetry and consider the dynamics on invariant Hilbert Spaces. In Statistical Mechanics this procedure is known as the vertex-IRF map, and in certain cases,…

Statistical Mechanics · Physics 2009-10-28 G. Sierra , T. Nishino

We employ the density matrix renormalization group (DMRG) and the wave function factorization method for the numerical solution of large scale nuclear structure problems. The DMRG exhibits an improved convergence for problems with realistic…

Nuclear Theory · Physics 2007-05-23 T. Papenbrock , D. J. Dean

We review the variational principle in the density matrix renormalization group (DMRG) method, which maximizes an approximate partition function within a restricted degrees of freedom; at zero temperature, DMRG mini- mizes the ground state…

Statistical Mechanics · Physics 2009-10-28 T. Nishino , K. Okunishi

In this paper, We Apply Reinforcement learning (RL) techniques to train a realistic biomechanical model to work with different people and on different walking environments. We benchmarking 3 RL algorithms: Deep Deterministic Policy Gradient…

Artificial Intelligence · Computer Science 2019-01-16 Montaser Mohammedalamen , Waleed D. Khamies , Benjamin Rosman

The physical properties of a quantum many-body system can, in principle, be determined by diagonalizing the respective Hamiltonian, but the dimensions of its matrix representation scale exponentially with the number of degrees of freedom.…

Strongly Correlated Electrons · Physics 2023-09-13 G. Catarina , Bruno Murta

A density-matrix renormalization group (DMRG) method for highly anisotropic two-dimensional systems is presented. The method consists in applying the usual DMRG in two steps. In the first step, a pure one dimensional calculation along the…

Strongly Correlated Electrons · Physics 2009-11-07 S. Moukouri , L. G. Caron

We present the theory of a density matrix renormalization group (DMRG) algorithm which can solve for both the ground and excited states of non-Hermitian transcorrelated Hamiltonians, and show applications in \emph{ab initio} molecular…

We have proposed a density-matrix renormalization group (DMRG) scheme to optimize the one-electron basis states of molecules. It improves significantly the accuracy and efficiency of the DMRG in the study of quantum chemistry or other…

Strongly Correlated Electrons · Physics 2010-10-20 H. -G. Luo , M. -P. Qin , T. Xiang

Planar pushing remains a challenging research topic, where building the dynamic model of the interaction is the core issue. Even an accurate analytical dynamic model is inherently unstable because physics parameters such as inertia and…

Robotics · Computer Science 2020-07-28 Lin Cong , Michael Görner , Philipp Ruppel , Hongzhuo Liang , Norman Hendrich , Jianwei Zhang
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