Results 11 to 20 of about 3,357,696 (317)
The distinguishable cluster approximation [PDF]
The Journal of Chemical Physics, 2013 A new method that accurately describes strongly correlated states and captures dynamical correlation is presented. It is derived as a modification of coupled-cluster theory with single and double excitations (CCSD) through consideration of particle ...
D. Kats, F. Manby
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Extended Variational Cluster Approximation
, 2005 The variational cluster approximation (VCA) proposed by M. Potthoff {\it et al.} [Phys. Rev. Lett. {\bf 91}, 206402 (2003)] is extended to electron or spin systems with nonlocal interactions.
K. Held, Ning-Hua Tong, Th. A. Maier
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Dynamical Cluster Approximation Employing FLEX as a Cluster Solver [PDF]
Physical Review B, 2002 We employ the Dynamical Cluster Approximation (DCA) in conjunction with the Fluctuation Exchange Approximation (FLEX) to study the Hubbard model. The DCA is a technique to systematically restore the momentum conservation at the internal vertices of ...
A. Georges +20 more
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Approximate Kernel Clustering [PDF]
2008 49th Annual IEEE Symposium on Foundations of Computer Science, 2008 In the kernel clustering problem we are given a large $n\times n$ positive semi-definite matrix $A=(a_{ij})$ with $\sum_{i,j=1}^na_{ij}=0$ and a small $k\times k$ positive semi-definite matrix $B=(b_{ij})$. The goal is to find a partition $S_1,...,S_k$ of $\{1,...
Khot, Subhash, Naor, Assaf
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Approximate Clustering without the Approximation [PDF]
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009 Approximation algorithms for clustering points in metric spaces is a flourishing area of research, with much research effort spent on getting a better understanding of the approximation guarantees possible for many objective functions such as k-median, k-means, and min-sum clustering.
Maria-Florina Balcan +2 more
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Adaptive cluster approximation for reduced density-matrix functional theory [PDF]
Physical review B, 2016 A method, called the adaptive cluster approximation (ACA), for single-impurity Anderson models is proposed. It is based on reduced density-matrix functional theory, where the one-particle reduced density matrix is used as the basic variable. The adaptive
Robert Schade, P. Blochl
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Simulating thermal density operators with cluster expansions and tensor networks
SciPost Physics, 2023 We provide an efficient approximation for the exponential of a local operator in quantum spin systems using tensor-network representations of a cluster expansion. We benchmark this cluster tensor network operator (cluster TNO) for one-dimensional systems,
Bram Vanhecke, David Devoogdt, Frank Verstraete, Laurens Vanderstraeten
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A Model of Pixel and Superpixel Clustering for Object Detection
Journal of Imaging, 2022 The paper presents a model of structured objects in a grayscale or color image, described by means of optimal piecewise constant image approximations, which are characterized by the minimum possible approximation errors for a given number of pixel ...
Vadim A. Nenashev +2 more
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Generalized multiband typical medium dynamical cluster approximation: Application to (Ga,Mn)N [PDF]
, 2016 We generalize the multiband typical medium dynamical cluster approximation and the formalism introduced by Blackman, Esterling, and Berk so that it can deal with localization in multiband disordered systems with both diagonal and off-diagonal disorder ...
Yi Zhang +9 more
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Statistics for approximate gene clusters [PDF]
BMC Bioinformatics, 2013 Genes occurring co-localized in multiple genomes can be strong indicators for either functional constraints on the genome organization or remnant ancestral gene order. The computational detection of these patterns, which are usually referred to as gene clusters, has become increasingly sensitive over the past decade.
Jahn, Katharina +3 more
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