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In numerical analysis, Wilkinson's polynomial is a specific polynomial which was used by James H. Wilkinson in 1963 to illustrate a difficulty when finding the root of a polynomial: the location of the roots can be very sensitive to perturbations in the coefficients of the polynomial. The polynomial is : Sometimes, the term ''Wilkinson's polynomial'' is also used to refer to some other polynomials appearing in Wilkinson's discussion. ==Background== Wilkinson's polynomial arose in the study of algorithms for finding the roots of a polynomial : It is a natural question in numerical analysis to ask whether the problem of finding the roots of ''p'' from the coefficients ''c''''i'' is well-conditioned. That is, we hope that a small change in the coefficients will lead to a small change in the roots. Unfortunately, this is not the case here. The problem is ill-conditioned when the polynomial has a multiple root. For instance, the polynomial ''x''2 has a double root at ''x'' = 0. However, the polynomial ''x''2−ε (a perturbation of size ε) has roots at ±√ε, which is much bigger than ε when ε is small. It is therefore natural to expect that ill-conditioning also occurs when the polynomial has zeros which are very close. However, the problem may also be extremely ill-conditioned for polynomials with well-separated zeros. Wilkinson used the polynomial ''w''(''x'') to illustrate this point (Wilkinson 1963). In 1984, he described the personal impact of this discovery: :''Speaking for myself I regard it as the most traumatic experience in my career as a numerical analyst.''〔 〕 Wilkinson's polynomial is often used to illustrate the undesirability of naively computing eigenvalues of a matrix by first calculating the coefficients of the matrix's characteristic polynomial and then finding its roots, since using the coefficients as an intermediate step may introduce an extreme ill-conditioning even if the original problem was well conditioned. 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Wilkinson's polynomial」の詳細全文を読む スポンサード リンク
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