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A simplified version of White's Density Matrix Renormalization Group (DMRG) algorithm has been used to find the ground state of the free particle on a tight-binding lattice. We generalize this algorithm to treat the tight-binding particle…

Strongly Correlated Electrons · Physics 2009-10-31 M. A. Martin-Delgado , G. Sierra , R. M. Noack

We introduce the Nuclear Electronic All-Particle Density Matrix Renormalization Group (NEAP-DMRG) method for solving the time-independent Schr\"odinger equation simultaneously for electrons and other quantum species. In contrast to already…

Chemical Physics · Physics 2020-05-29 Andrea Muolo , Alberto Baiardi , Robin Feldmann , Markus Reiher

An efficiency of the Tucker decomposition of amplitude tensors within the single-reference relativistic coupled cluster method with single and double excitations (RCCSD) was studied in a series of benchmark calculations for (AuCl)$_n$…

Computational Physics · Physics 2025-07-29 Alexander V. Oleynichenko , Artem S. Rumiantsev , Andrei Zaitsevskii , Ephraim Eliav

We generalized the recently introduced new impurity solver based on the diagrammatic expansion around the atomic limit and Quantum Monte Carlo summation of the diagrams. We present generalization to the cluster of impurities, which is at…

Strongly Correlated Electrons · Physics 2009-11-11 Kristjan Haule

Quantum computational chemistry has emerged as an important application of quantum computing. Hybrid quantum-classical computing methods, such as variational quantum eigensolvers (VQE), have been designed as promising solutions to quantum…

We implement and apply time-dependent density matrix renormalization group (TD-DMRG) algorithms at zero and finite temperature to compute the linear absorption and fluorescence spectra of molecular aggregates. Our implementation is within a…

Chemical Physics · Physics 2019-07-30 Jiajun Ren , Zhigang Shuai , Garnet Kin-Lic Chan

The Density Matrix Renormalization Group (DMRG) was introduced by Steven White in 1992 as a method for accurately describing the properties of one-dimensional quantum lattices. The method, as originally introduced, was based on the…

Mesoscale and Nanoscale Physics · Physics 2011-05-12 Jorge Dukelsky , Stuart Pittel

The cluster-in-molecule (CIM) local correlation approach with an accurate distant pair correlation energy correction is presented. For large systems, the inclusion of distant pair correlation energies is essential for the accurate…

Chemical Physics · Physics 2020-08-06 Zhigang Ni , Yang Guo , Frank Neese , Wei Li , Shuhua Li

We report the implementation of 4-component spinor relativistic equation-of-motion coupledcluster method within the single- and double- excitation approximation to calculate ionization potential (EOM-CCSD) of molecules. We have applied this…

Chemical Physics · Physics 2015-02-25 Himadri Pathak , Sudip Sasmal , Malaya K. Nayak , Nayana Vaval , Sourav Pal

We address general-shaped clustering problems under very weak parametric assumptions with a two-step hybrid robust clustering algorithm based on trimmed k-means and hierarchical agglomeration. The algorithm has low computational complexity…

Methodology · Statistics 2022-01-19 Luca Insolia , Domenico Perrotta

Light clusters are included in the equation of state of nuclear matter within the relativistic mean field theory. The effect of the cluster-meson coupling constants on the dissolution density is discussed. Theoretical and experimental…

Nuclear Theory · Physics 2012-06-04 Márcio Ferreira , Constança Providência

In this work we describe the rank-reduced variant of the equation-of-motion coupled cluster theory with complete inclusion of single, double, and triple excitations. The advantage of the proposed formalism in comparison with the canonical…

Chemical Physics · Physics 2026-05-15 Piotr Michalak , Michał Lesiuk

We describe the use of the Density Matrix Renormalization Group method as a means of approximately solving large-scale nuclear shell-model problems. We focus on an angular-momentum-conserving variant of the method and report test results…

Nuclear Theory · Physics 2011-05-12 S. Pittel , N. Sandulescu

Except for small molecules, it is impossible to solve many electrons systems without imposing severe approximations. If the configuration interaction approaches (CI) or Coupled Clusters techniques \cite{FuldeBook} are applicable for…

Strongly Correlated Electrons · Physics 2009-11-11 J. P. Julien , Johann Bouchet

We aim to describe the cluster states of nuclear systems starting with a realistic interaction, which is a challenge of modern nuclear theories. Here, the short-range correlation of realistic interaction is treated by employing the damping…

Nuclear Theory · Physics 2020-03-20 Naoyuki Itagaki , Tokuro Fukui , Akihiro Tohsaki

Dense relativistic matter has attracted a lot of attention over many decades now, with a focus on an understanding of the phase structure and thermodynamics of dense strong-interaction matter. The analysis of dense strong-interaction matter…

High Energy Physics - Phenomenology · Physics 2021-11-17 Jens Braun , Timon Dörnfeld , Benedikt Schallmo , Sebastian Töpfel

In strongly correlated systems, numerical algorithms taking parity quantum numbers into account are used not only for accelerating computation by reducing the Hilbert space but also for particular manipulations such as the Level…

Strongly Correlated Electrons · Physics 2016-02-04 Yu-Chin Tzeng

Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: the density matrix renormalization group (DMRG), Boltzmann…

Quantum Physics · Physics 2024-04-18 Daming Li

The direct ring coupled-cluster doubles (drCCD)-based random phase approximation (RPA) has provided an attractive framework for the development and application of RPA-related methods. However, a potential unphysical solution issue recently…

Chemical Physics · Physics 2025-08-18 Ruiheng Song , Xiliang Gong , Hong-Zhou Ye

This paper explores the problem of clustering ensemble, which aims to combine multiple base clusterings to produce better performance than that of the individual one. The existing clustering ensemble methods generally construct a…

Machine Learning · Computer Science 2020-12-17 Yuheng Jia , Hui Liu , Junhui Hou , Qingfu Zhang
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