72 research outputs found

    A new look at the Lanczos algorithm for solving symmetric systems of linear equations

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    AbstractSimple versions of the conjugate gradient algorithm and the Lanczos method are discussed, and some merits of the latter are described. A variant of Lanczos is proposed which maintains robust linear independence of the Lanczos vectors by keeping them in secondary storage and occasionally making use of them. The main applications are to problems in which (1) the cost of the matrix-vector product dominates other costs, (2) there is a sequence of right hand sides to be processed, and (3) the eigenvalue distribution of A is not too favorable

    A note on the error analysis of classical Gram-Schmidt

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    An error analysis result is given for classical Gram--Schmidt factorization of a full rank matrix AA into A=QRA=QR where QQ is left orthogonal (has orthonormal columns) and RR is upper triangular. The work presented here shows that the computed RR satisfies \normal{R}=\normal{A}+E where EE is an appropriately small backward error, but only if the diagonals of RR are computed in a manner similar to Cholesky factorization of the normal equations matrix. A similar result is stated in [Giraud at al, Numer. Math. 101(1):87--100,2005]. However, for that result to hold, the diagonals of RR must be computed in the manner recommended in this work.Comment: 12 pages This v2. v1 (from 2006) has not the biliographical reference set (at all). This is the only modification between v1 and v2. If you want to quote this paper, please quote the version published in Numerische Mathemati

    The Asymptotics of Wilkinson's Iteration: Loss of Cubic Convergence

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    One of the most widely used methods for eigenvalue computation is the QRQR iteration with Wilkinson's shift: here the shift ss is the eigenvalue of the bottom 2×22\times 2 principal minor closest to the corner entry. It has been a long-standing conjecture that the rate of convergence of the algorithm is cubic. In contrast, we show that there exist matrices for which the rate of convergence is strictly quadratic. More precisely, let TXT_X be the 3×33 \times 3 matrix having only two nonzero entries (TX)12=(TX)21=1(T_X)_{12} = (T_X)_{21} = 1 and let TLT_L be the set of real, symmetric tridiagonal matrices with the same spectrum as TXT_X. There exists a neighborhood UTLU \subset T_L of TXT_X which is invariant under Wilkinson's shift strategy with the following properties. For T0UT_0 \in U, the sequence of iterates (Tk)(T_k) exhibits either strictly quadratic or strictly cubic convergence to zero of the entry (Tk)23(T_k)_{23}. In fact, quadratic convergence occurs exactly when limTk=TX\lim T_k = T_X. Let XX be the union of such quadratically convergent sequences (Tk)(T_k): the set XX has Hausdorff dimension 1 and is a union of disjoint arcs XσX^\sigma meeting at TXT_X, where σ\sigma ranges over a Cantor set.Comment: 20 pages, 8 figures. Some passages rewritten for clarit

    Mott-Hubbard insulators for systems with orbital degeneracy

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    We study how the electron hopping reduces the Mott-Hubbard band gap in the limit of a large Coulomb interaction U and as a function of the orbital degeneracy N. The results support the conclusion that the hopping contribution grows as roughly \sqrt{N}W, where W is the one-particle band width, but in certain models a crossover to a \sim NW behavior is found for a sufficiently large N.Comment: 7 pages, revtex, 6 figures more information at http://www.mpi-stuttgart.mpg.de/dokumente/andersen/fullerene

    Wave functions and properties of massive states in three-dimensional supersymmetric Yang-Mills theory

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    We apply supersymmetric discrete light-cone quantization (SDLCQ) to the study of supersymmetric Yang-Mills theory on R x S^1 x S^1. One of the compact directions is chosen to be light-like and the other to be space-like. Since the SDLCQ regularization explicitly preserves supersymmetry, this theory is totally finite, and thus we can solve for bound-state wave functions and masses numerically without renormalizing. We present an overview of all the massive states of this theory, and we see that the spectrum divides into two distinct and disjoint sectors. In one sector the SDLCQ approximation is only valid up to intermediate coupling. There we find a well defined and well behaved set of states, and we present a detailed analysis of these states and their properties. In the other sector, which contains a completely different set of states, we present a much more limited analysis for strong coupling only. We find that, while these state have a well defined spectrum, their masses grow with the transverse momentum cutoff. We present an overview of these states and their properties.Comment: RevTeX, 25 pages, 16 figure

    Spectra of "Real-World" Graphs: Beyond the Semi-Circle Law

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    Many natural and social systems develop complex networks, that are usually modelled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semi-circle law is known to describe the spectral density of uncorrelated random graphs, much less is known about the eigenvalues of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more than a few thousand nodes is prohibitively time and memory consuming. Making use of recent advances in algorithms for spectral characterization, here we develop new methods to determine the eigenvalues of networks comparable in size to real systems, obtaining several surprising results on the spectra of adjacency matrices corresponding to models of real-world graphs. We find that when the number of links grows as the number of nodes, the spectral density of uncorrelated random graphs does not converge to the semi-circle law. Furthermore, the spectral densities of real-world graphs have specific features depending on the details of the corresponding models. In particular, scale-free graphs develop a triangle-like spectral density with a power law tail, while small-world graphs have a complex spectral density function consisting of several sharp peaks. These and further results indicate that the spectra of correlated graphs represent a practical tool for graph classification and can provide useful insight into the relevant structural properties of real networks.Comment: 14 pages, 9 figures (corrected typos, added references) accepted for Phys. Rev.

    User-friendly tail bounds for sums of random matrices

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    This paper presents new probability inequalities for sums of independent, random, self-adjoint matrices. These results place simple and easily verifiable hypotheses on the summands, and they deliver strong conclusions about the large-deviation behavior of the maximum eigenvalue of the sum. Tail bounds for the norm of a sum of random rectangular matrices follow as an immediate corollary. The proof techniques also yield some information about matrix-valued martingales. In other words, this paper provides noncommutative generalizations of the classical bounds associated with the names Azuma, Bennett, Bernstein, Chernoff, Hoeffding, and McDiarmid. The matrix inequalities promise the same diversity of application, ease of use, and strength of conclusion that have made the scalar inequalities so valuable.Comment: Current paper is the version of record. The material on Freedman's inequality has been moved to a separate note; other martingale bounds are described in Caltech ACM Report 2011-0

    Two-sided Grassmann-Rayleigh quotient iteration

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    The two-sided Rayleigh quotient iteration proposed by Ostrowski computes a pair of corresponding left-right eigenvectors of a matrix CC. We propose a Grassmannian version of this iteration, i.e., its iterates are pairs of pp-dimensional subspaces instead of one-dimensional subspaces in the classical case. The new iteration generically converges locally cubically to the pairs of left-right pp-dimensional invariant subspaces of CC. Moreover, Grassmannian versions of the Rayleigh quotient iteration are given for the generalized Hermitian eigenproblem, the Hamiltonian eigenproblem and the skew-Hamiltonian eigenproblem.Comment: The text is identical to a manuscript that was submitted for publication on 19 April 200
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