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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

In recent years, spectral clustering has become a standard method for data analysis used in a broad range of applications. In this paper we propose a new class of algorithms for multiway spectral clustering based on optimization of a…

Machine Learning · Computer Science 2016-05-05 James Voss , Mikhail Belkin , Luis Rademacher

For quantum spin models defined on a two-dimensional lattice, we look for the best numbering of the lattice sites (a layout) that, at fixed bond dimension and other parameters of the density matrix renormalization group (DMRG) algorithm,…

Strongly Correlated Electrons · Physics 2026-03-09 A. Scardicchio

The exact renormalization group (ERG) is a powerful tool for understanding the formal properties of field theories. By adapting generalized ERG schemes to the flow of wavefunctionals, we obtain a large class of continuous unitary networks,…

High Energy Physics - Theory · Physics 2024-01-22 Samuel Goldman , Nima Lashkari , Robert G. Leigh , Mudassir Moosa

The problem considered here is the determination of the hamiltonian of a first quantized nonrelativistic particle by the help of some measurements of the location with a finite resolution. The resulting hamiltonian depends on the resolution…

High Energy Physics - Theory · Physics 2009-10-30 Hanae El Hattab , Janos Polonyi

In this article we apply a recently invented analytical real-space renormalization group formulation which is based on numerical concepts of the density matrix renormalization group. Within a rigorous mathematical framework we construct…

Statistical Mechanics · Physics 2009-10-31 Andreas Degenhard

The density-matrix renormalization group method (DMRG) has established itself over the last decade as the leading method for the simulation of the statics and dynamics of one-dimensional strongly correlated quantum lattice systems. In the…

Strongly Correlated Electrons · Physics 2011-01-04 Ulrich Schollwoeck

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of time-dependent DMRG from the usual situation of hermitian Hamiltonian matrices to…

Compared to common density functionals, ab initio wave function methods can provide greater reliability and accuracy, which could prove useful when modeling adsorbates or defects of otherwise periodic systems. However, the breaking of…

Materials Science · Physics 2020-10-02 Bryan T. G. Lau , Gerald Knizia , Timothy C. Berkelbach

We develop a systematic multi-local expansion of the Polchinski-Wilson exact renormalization group (ERG) equation. Integrating out explicitly the non local interactions, we reduce the ERG equation obeyed by the full interaction functional…

Condensed Matter · Physics 2009-10-31 Pascal Chauve , Pierre Le Doussal

We introduce a hybrid approach to applying the density matrix renormalization group (DMRG) to continuous systems, combining a grid approximation along one direction with a finite Gaussian basis set along the remaining two directions. This…

Chemical Physics · Physics 2017-08-02 E. Miles Stoudenmire , Steven R. White

The instability of embedding spaces across model retraining cycles presents significant challenges to downstream applications using user or item embeddings derived from recommendation systems as input features. This paper introduces a novel…

Information Retrieval · Computer Science 2025-08-12 Kevin Zielnicki , Ko-Jen Hsiao

We describe an efficient quantum embedding framework for realistic ab initio density matrix embedding (DMET) calculations in solids. We discuss in detail the choice of orbitals and mapping to a lattice, treatment of the virtual space and…

Strongly Correlated Electrons · Physics 2020-01-15 Zhi-Hao Cui , Tianyu Zhu , Garnet Kin-Lic Chan

This thesis describes the development of the density matrix embedding theory (DMET) and its applications to lattice strongly correlated electron problems, including a review of DMET theory and algorithms (Ch 2), investigation of finite size…

Strongly Correlated Electrons · Physics 2018-03-29 Bo-Xiao Zheng

We examine the vacuum polarization contribution in the renormalization scheme of QED. Normally, the quadratic divergence term is discarded under the condition that the counter term of the Lagrangian density should be gauge invariant. Here,…

High Energy Physics - Theory · Physics 2009-01-23 T. Fujita , N. Kanda , H. Kato , H. Kubo , Y. Munakata , S. Oshima , K. Tsuda

Although many techniques have been applied to matrix factorization (MF), they may not fully exploit the feature structure. In this paper, we incorporate the grouping effect into MF and propose a novel method called Robust Matrix…

Machine Learning · Computer Science 2021-07-09 Haiyan Jiang , Shuyu Li , Luwei Zhang , Haoyi Xiong , Dejing Dou

An expansion method for perturbation of the zero temperature grand canonical density matrix is introduced. The method achieves quadratically convergent recursions that yield the response of the zero temperature density matrix upon variation…

Materials Science · Physics 2009-11-10 Anders M. N. Niklasson , Matt Challacombe

The density-matrix renormalization group (DMRG) method, which can deal with a large active space composed of tens of orbitals, is nowadays widely used as an efficient addition to traditional complete active space (CAS)-based approaches. In…

Strongly Correlated Electrons · Physics 2016-11-06 Yingjin Ma , Jing Wen , Haibo Ma

We investigate the role of entanglement in quantum phase transitions, and show that the success of the density matrix renormalization group (DMRG) in understanding such phase transitions is due to the way it preserves entanglement under…

Quantum Physics · Physics 2007-05-23 Tobias J. Osborne , Michael A. Nielsen

The characteristic feature of inverse problems is their instability with respect to data perturbations. In order to stabilize the inversion process, regularization methods have to be developed and applied. In this work we introduce and…

Numerical Analysis · Mathematics 2022-08-22 Andrea Ebner , Jürgen Frikel , Dirk Lorenz , Johannes Schwab , Markus Haltmeier
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