English
Related papers

Related papers: Studying Two Dimensional Systems With the Density …

200 papers

We introduce a picture to analyze the density matrix renormalization group (DMRG) numerical method from a quantum information perspective. This leads us to introduce some modifications for problems with periodic boundary conditions in which…

Strongly Correlated Electrons · Physics 2007-05-23 F. Verstraete , D. Porras , J. I. Cirac

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 discuss the development of an angular-momentum-conserving variant of the Density Matrix Renormalization Group (DMRG) method for use in large-scale shell-model calculations of atomic nuclei and report a first application of the method to…

Nuclear Theory · Physics 2009-02-09 B. Thakur , S. Pittel , N. Sandulescu

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

We generalize the spectral sum rule preserving density matrix numerical renormalization group (DM-NRG) method in such a way that it can make use of an arbitrary number of not necessarily Abelian, local symmetries present in the quantum…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 A. I. Toth , C. P. Moca , O. Legeza , G. Zarand

White's density matrix renormalization group ({DMRG}) method has been applied to the one-dimensional Ising model in a transverse field ({ITF}), in order to study the accuracy of the numerical algorithm. Due to the exact solubility of the…

Strongly Correlated Electrons · Physics 2009-10-31 Ors Legeza , Gabor Fath

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 implement an efficient strong-disorder renormalization-group (SDRG) procedure to study disordered tight-binding models in any dimension and on the Erdos-Renyi random graphs, which represent an appropriate infinite dimensional limit. Our…

Strongly Correlated Electrons · Physics 2017-08-02 Hossein Javan Mard , Jose A. Hoyos , Eduardo Miranda , Vladimir Dobrosavljevic

The tensor-network renormalization group (TNRG) is an accurate numerical real-space renormalization group method for studying phase transitions in both quantum and classical systems. Continuous phase transitions, as an important class of…

Statistical Mechanics · Physics 2026-03-27 Xinliang Lyu

We extend the density matrix renormalization group method to exploit Parity, $C_2$ (rotation by $\pi$) and electron-hole symmtries of model Hamiltonians. We demonstrate the power of this method by obtaining the lowest energy states in all…

Condensed Matter · Physics 2007-05-23 S. Ramasesha , Swapan K. Pati , H. R. Krishnamurthy , Z. Shuai , J. L. Bredas

We propose a new fast numerical renormalization group method,the corner transfer matrix renormalization group (CTMRG) method, which is based on a unified scheme of Baxter's corner transfer matrix method and White's density matrix…

Condensed Matter · Physics 2009-10-28 T. Nishino , K. Okunishi

In some cases the state of a quantum system with a large number of subsystems can be approximated efficiently by the density matrix renormalization group, which makes use of redundancies in the description of the state. Here we show that…

Strongly Correlated Electrons · Physics 2009-02-03 Michael J. Hartmann , Javier Prior , Stephen R. Clark , Martin B. Plenio

In this paper a mode of using the Dynamic Renormalization Group (DRG) method is suggested in order to cope with inconsistent results obtained when applying it to a continuous family of one-dimensional nonlocal models. The key observation is…

Statistical Mechanics · Physics 2020-10-05 E. Katzav

Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techniques have yielded record-breaking results on a diverse set…

Machine Learning · Statistics 2014-10-16 Pankaj Mehta , David J. Schwab

We present a time-step targetting scheme to simulate real-time dynamics efficiently using the density matrix renormalization group (DMRG). The algorithm works on ladders and systems with interactions beyond nearest neighbors, in contrast to…

Strongly Correlated Electrons · Physics 2007-05-23 Adrian E. Feiguin , Steven R. White

We adapt White's density matrix renormalisation group (DMRG) to the direct study of critical phenomena. We use the DMRG to generate transformations in the space of coupling constants. We postulate that a study of density matrix eigenvalues…

Condensed Matter · Physics 2007-05-23 R. J. Bursill , F. Gode

In this paper we describe how the density matrix renormalization group (DMRG) can be used for quantum chemical calculations for molecules, as an alternative to traditional methods, such as configuration interaction or coupled cluster…

Condensed Matter · Physics 2009-10-31 Steven R. White , Richard L. Martin

We present a numerical implementation of the density matrix renormalization group (DMRG) using the discrete variable representation (DVR) basis set. One main advantage of using the local DVR basis sets is that the computations of…

Quantum Physics · Physics 2024-11-13 Bing Gu

Density matrix renormalization group (DMRG) is one of the most powerful numerical methods available for many-body systems. In this work, we develop a perturbation theory of DMRG (PT-DMRG) to largely increase its accuracy in an extremely…

Strongly Correlated Electrons · Physics 2017-03-01 Emanuele Tirrito , Shi-Ju Ran , Andrew J. Ferris , Ian P. McCulloch , Maciej Lewenstein

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima
‹ Prev 1 4 5 6 7 8 10 Next ›