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Computing the zeros of a Fourier series or a Chebyshev series or general orthogonal polynomial series with parity symmetries

机译:计算具有奇偶校验对称性的Fourier级数或Chebyshev级数或一般正交多项式级数的零

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In recent years, good algorithms have been developed for finding the zeros of trigonometric polynomials and of ordinary polynomials when written in the form of a truncated Chebyshev polynomial or Legendre polynomial series. In each case, the roots can be found from the eigenvalues of a generalized Frobenius companion matrix whose elements are trivial functions of the Fourier coefficients or Chebyshev coefficients. However, the QR method for computing the companion matrix eigenvalues has a cost that grows proportionally to N~3 where N is the polynomial degree. (By exploiting the special structure of the companion matrices, the cost can be reduced to O (N~2), but only for large N.) Here, we show that if the polynomial has definite parity, such as a trigonometric polynomial composed only of cosines or a polynomial that is a sum only of Chebyshev polynomials of odd degree, one can exploit these symmetries to halve the size of the problem. This reduces costs in the companion matrix method by a factor ranging between four and eight. For trigonometric polynomials, we give transformations that dramatically reduce costs even if the roots are found by an algorithm other than the companion matrix procedure. We further give reductions for trigonometric polynomials with double parity symmetries which save a factor of sixteen to a factor of sixty-four in the companion matrix algorithm. Special functions such as spherical harmonics, Mathieu functions, prolate spheroidal wavefunctions and Hough functions, all represented by truncated Fourier series with double parity, are a rich source of applications.
机译:近年来,已经开发出了很好的算法,以截断的切比雪夫多项式或勒让德多项式的形式编写时,可以找到三角多项式和普通多项式的零。在每种情况下,都可以从广义Frobenius伴随矩阵的特征值中找到根,该矩阵的元素是傅里叶系数或Chebyshev系数的平凡函数。然而,用于计算伴随矩阵特征值的QR方法的成本成比例地增加到N〜3,其中N是多项式。 (通过利用伴随矩阵的特殊结构,可以将成本降低到O(N〜2),但仅对于大N即可。)在这里,我们表明,如果多项式具有确定的奇偶性,例如仅由三项式组成的三角多项式如果余弦或多项式仅是奇数切比雪夫多项式之和,则可以利用这些对称性将问题的大小减半。这将伴随矩阵方法的成本降低了四到八倍。对于三角多项式,我们给出了可以大大降低成本的变换,即使通过除伴随矩阵过程以外的其他算法找到了根也是如此。我们进一步给出了具有双重奇偶校验对称性的三角多项式的约简,在伴随矩阵算法中将其节省了16倍至64倍。特殊功能(如球谐函数,Mathieu函数,扁长球面波函数和Hough函数)均以具有双重奇偶性的截断傅立叶级数表示,这些都是丰富的应用程序。

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