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numerical range : ウィキペディア英語版
numerical range
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
:W(A) = \left\}} \mid \mathbf\in\mathbb^n,\ x\not=0\right\}
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) = \sup \ = \sup_ |\langle Ax, x \rangle|.
''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.
# W(\alpha A+\beta I)=\alpha W(A)+\ for all square matrix ''A'' and complex numbers α and β. Here ''I'' is the identity matrix.
# W(A) is a subset of the closed right half-plane if and only if A+A^
* is positive semidefinite.
# The numerical range W(\cdot) is the only function on the set of square matrices that satisfies (2), (3) and (4).
# (Sub-additive) W(A+B)\subseteq W(A)+W(B).
# W(A) contains all the eigenvalues of ''A''.
# The numerical range of a 2×2 matrix is an elliptical disk.
# W(A) 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 W(A) is the convex hull of its eigenvalues.
# If α is a sharp point on the boundary of W(A), then α is a normal eigenvalue of ''A''.
# r(\cdot) is a norm on the space of ''n''×''n'' matrices.
# r(A^n) \le r(A)^n

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



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