496,336 research outputs found
A fast algorithm for LR-2 factorization of Toeplitz matrices
In this paper a new order recursive algorithm for the efficient â1 factorization of Toeplitz matrices is described. The proposed algorithm can be seen as a fast modified Gram-Schmidt method which recursively computes the orthonormal columns i, i = 1,2, âŠ,p, of , as well as the elements of Râ1, of a Toeplitz matrix with dimensions L Ă p. The factor estimation requires 8Lp MADS (multiplications and divisions). Matrix â1 is subsequently estimated using 3p2 MADS. A faster algorithm, based on a mixed and â1 updating scheme, is also derived. It requires 7Lp + 3.5p2 MADS. The algorithm can be efficiently applied to batch least squares FIR filtering and system identification. When determination of the optimal filter is the desired task it can be utilized to compute the least squares filter in an order recursive way. The algorithm operates directly on the experimental data, overcoming the need for covariance estimates. An orthogonalized version of the proposed â1 algorithm is derived. Matlab code implementing the algorithm is also supplied
Computing Periods of Hypersurfaces
We give an algorithm to compute the periods of smooth projective
hypersurfaces of any dimension. This is an improvement over existing algorithms
which could only compute the periods of plane curves. Our algorithm reduces the
evaluation of period integrals to an initial value problem for ordinary
differential equations of Picard-Fuchs type. In this way, the periods can be
computed to extreme-precision in order to study their arithmetic properties.
The initial conditions are obtained by an exact determination of the cohomology
pairing on Fermat hypersurfaces with respect to a natural basis.Comment: 33 pages; Final version. Fixed typos, minor expository changes.
Changed code repository lin
The optimal P3M algorithm for computing electrostatic energies in periodic systems
We optimize Hockney and Eastwood's Particle-Particle Particle-Mesh (P3M)
algorithm to achieve maximal accuracy in the electrostatic energies (instead of
forces) in 3D periodic charged systems. To this end we construct an optimal
influence function that minimizes the RMS errors in the energies. As a
by-product we derive a new real-space cut-off correction term, give a
transparent derivation of the systematic errors in terms of Madelung energies,
and provide an accurate analytical estimate for the RMS error of the energies.
This error estimate is a useful indicator of the accuracy of the computed
energies, and allows an easy and precise determination of the optimal values of
the various parameters in the algorithm (Ewald splitting parameter, mesh size
and charge assignment order).Comment: 31 pages, 3 figure
Dynamic Dominators and Low-High Orders in DAGs
We consider practical algorithms for maintaining the dominator tree and a low-high order in directed acyclic graphs (DAGs) subject to dynamic operations. Let G be a directed graph with a distinguished start vertex s. The dominator tree D of G is a tree rooted at s, such that a vertex v is an ancestor of a vertex w if and only if all paths from s to w in G include v. The dominator tree is a central tool in program optimization and code generation, and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of G is a preorder of D that certifies the correctness of D, and has further applications in connectivity and path-determination problems.
We first provide a practical and carefully engineered version of a recent algorithm [ICALP 2017] for maintaining the dominator tree of a DAG through a sequence of edge deletions. The algorithm runs in O(mn) total time and O(m) space, where n is the number of vertices and m is the number of edges before any deletion. In addition, we present a new algorithm that maintains a low-high order of a DAG under edge deletions within the same bounds. Both results extend to the case of reducible graphs (a class that includes DAGs). Furthermore, we present a fully dynamic algorithm for maintaining the dominator tree of a DAG under an intermixed sequence of edge insertions and deletions. Although it does not maintain the O(mn) worst-case bound of the decremental algorithm, our experiments highlight that the fully dynamic algorithm performs very well in practice. Finally, we study the practical efficiency of all our algorithms by conducting an extensive experimental study on real-world and synthetic graphs
Automatic generation of Feynman rules in the Schroedinger functional
We provide an algorithm to generate vertices for the Schr\"odinger functional
with an abelian background gauge field. The background field has a non-trivial
color structure, therefore we mainly focus on a manipulation of the color
matrix part. We propose how to implement the algorithm especially in python
code. By using python outputs produced by the code, we also show how to write a
numerical expression of vertices in the time-momentum as well as the coordinate
space into a Feynman diagram calculation code. As examples of the applications
of the algorithm, we provide some one-loop results, ratios of the Lambda
parameters between the plaquette gauge action and the improved gauge actions
composed from six-link loops (rectangular, chair and parallelogram), the
determination of the O(a) boundary counter term to this order, and the
perturbative cutoff effects of the step scaling function of the Schroedinger
functional coupling constant.Comment: 34 pages, 4 figure
Using network-flow techniques to solve an optimization problem from surface-physics
The solid-on-solid model provides a commonly used framework for the
description of surfaces. In the last years it has been extended in order to
investigate the effect of defects in the bulk on the roughness of the surface.
The determination of the ground state of this model leads to a combinatorial
problem, which is reduced to an uncapacitated, convex minimum-circulation
problem. We will show that the successive shortest path algorithm solves the
problem in polynomial time.Comment: 8 Pages LaTeX, using Elsevier preprint style (macros included
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