454 research outputs found

    Cylindrical Algebraic Sub-Decompositions

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    Cylindrical algebraic decompositions (CADs) are a key tool in real algebraic geometry, used primarily for eliminating quantifiers over the reals and studying semi-algebraic sets. In this paper we introduce cylindrical algebraic sub-decompositions (sub-CADs), which are subsets of CADs containing all the information needed to specify a solution for a given problem. We define two new types of sub-CAD: variety sub-CADs which are those cells in a CAD lying on a designated variety; and layered sub-CADs which have only those cells of dimension higher than a specified value. We present algorithms to produce these and describe how the two approaches may be combined with each other and the recent theory of truth-table invariant CAD. We give a complexity analysis showing that these techniques can offer substantial theoretical savings, which is supported by experimentation using an implementation in Maple.Comment: 26 page

    Using the distribution of cells by dimension in a cylindrical algebraic decomposition

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    We investigate the distribution of cells by dimension in cylindrical algebraic decompositions (CADs). We find that they follow a standard distribution which seems largely independent of the underlying problem or CAD algorithm used. Rather, the distribution is inherent to the cylindrical structure and determined mostly by the number of variables. This insight is then combined with an algorithm that produces only full-dimensional cells to give an accurate method of predicting the number of cells in a complete CAD. Since constructing only full-dimensional cells is relatively inexpensive (involving no costly algebraic number calculations) this leads to heuristics for helping with various questions of problem formulation for CAD, such as choosing an optimal variable ordering. Our experiments demonstrate that this approach can be highly effective.Comment: 8 page

    Computing the Rank and a Small Nullspace Basis of a Polynomial Matrix

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    We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n x n matrix of degree d over a field K we give a rank and nullspace algorithm using about the same number of operations as for multiplying two matrices of dimension n and degree d. If the latter multiplication is done in MM(n,d)=softO(n^omega d) operations, with omega the exponent of matrix multiplication over K, then the algorithm uses softO(MM(n,d)) operations in K. The softO notation indicates some missing logarithmic factors. The method is randomized with Las Vegas certification. We achieve our results in part through a combination of matrix Hensel high-order lifting and matrix minimal fraction reconstruction, and through the computation of minimal or small degree vectors in the nullspace seen as a K[x]-moduleComment: Research Report LIP RR2005-03, January 200

    Numerical Algebraic Geometry: A New Perspective on String and Gauge Theories

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    The interplay rich between algebraic geometry and string and gauge theories has recently been immensely aided by advances in computational algebra. However, these symbolic (Gr\"{o}bner) methods are severely limited by algorithmic issues such as exponential space complexity and being highly sequential. In this paper, we introduce a novel paradigm of numerical algebraic geometry which in a plethora of situations overcomes these short-comings. Its so-called 'embarrassing parallelizability' allows us to solve many problems and extract physical information which elude the symbolic methods. We describe the method and then use it to solve various problems arising from physics which could not be otherwise solved.Comment: 36 page

    Structural synthesis of a stiffened cylinder

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    Structural synthesis of cylindrical shell reinforced with rectangular cross section stiffener

    Algorithmic Contributions to the Theory of Regular Chains

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    Regular chains, introduced about twenty years ago, have emerged as one of the major tools for solving polynomial systems symbolically. In this thesis, we focus on different algorithmic aspects of the theory of regular chains, from theoretical questions to high- performance implementation issues. The inclusion test for saturated ideals is a fundamental problem in this theory. By studying the primitivity of regular chains, we show that a regular chain generates its saturated ideal if and only if it is primitive. As a result, a family of inclusion tests can be detected very efficiently. The algorithm to compute the regular GCDs of two polynomials modulo a regular chain is one of the key routines in the various triangular decomposition algorithms. By revisiting relations between subresultants and GCDs, we proposed a novel bottom-up algorithm for this task, which improves the previous algorithm in a significant manner and creates opportunities for parallel execution. This thesis also discusses the accelerations towards fast Fourier transform (FFT) over finite fields and FFT based subresultant chain constructions in the context of massively parallel GPU architectures, which speedup our algorithms by several orders of magnitude

    Time-Domain Minimization of Voltage and Current Total Harmonic Distortion for a Single-Phase Multilevel Inverter with a Staircase Modulation

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    This paper presents the optimization technique for minimizing the voltage and current total harmonic distortion (THD) in a single-phase multilevel inverter controlled by staircase modulation. The previously reported research generally considered the optimal THD problem in the frequency domain, taking into account a limited harmonic number. The novelty of the suggested approach is that voltage and current minimal THD problems are being formulated in the time domain as constrained optimization ones, making it possible to determine the optimal switching angles. In this way, all switching harmonics can be considered. The target function expression becomes very compact and existing efficient solvers for this kind of optimization problems can find a solution in negligible processor time. Current THD is understood as voltage frequency weighted THD that assumes pure inductive load—this approximation is practically accurate for inductively dominant RL-loads. In this study, the optimal switching angles and respective minimal THD values were obtained for different inverter level counts and overall fundamental voltage magnitude (modulation index) dynamic range. Developments are easily modified to cover multilevel inverter grid-connected applications. The results have been verified by experimental tests
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