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In the mathematical field of linear algebra and convex analysis, the numerical range or field of values of a complex ''n'' × ''n'' matrix ''A'' is the set : where x * denotes the conjugate transpose of the vector x. In engineering, numerical ranges are used as a rough estimate of eigenvalues of ''A''. Recently, generalizations of numerical range are used to study quantum computing. A related concept is the numerical radius, which is the largest absolute value of the numbers in the numerical range, i.e. : ''r''(''A'') is a norm. ''r''(''A'')=||''A''||, where ||''A''|| is the operator norm of ''A''. ==Properties== # The numerical range is the range of the Rayleigh quotient. # (Hausdorff–Toeplitz theorem) The numerical range is convex and compact. # for all square matrix ''A'' and complex numbers α and β. Here ''I'' is the identity matrix. # is a subset of the closed right half-plane if and only if is positive semidefinite. # The numerical range is the only function on the set of square matrices that satisfies (2), (3) and (4). # (Sub-additive) . # contains all the eigenvalues of ''A''. # The numerical range of a 2×2 matrix is an elliptical disk. # is a real line segment (β ) if and only if ''A'' is a Hermitian matrix with its smallest and the largest eigenvalues being α and β # If ''A'' is a normal matrix then is the convex hull of its eigenvalues. # If α is a sharp point on the boundary of , then α is a normal eigenvalue of ''A''. # is a norm on the space of ''n''×''n'' matrices. # 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「numerical range」の詳細全文を読む スポンサード リンク
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