# Numerical range

In the mathematical field of linear algebra and convex analysis, the numerical range or field of values of a complex ${\displaystyle n\times n}$ matrix A is the set

${\displaystyle W(A)=\left\{{\frac {\mathbf {x} ^{*}A\mathbf {x} }{\mathbf {x} ^{*}\mathbf {x} }}\mid \mathbf {x} \in \mathbb {C} ^{n},\ \mathbf {x} \not =0\right\}}$

where ${\displaystyle \mathbf {x} ^{*}}$ denotes the conjugate transpose of the vector ${\displaystyle \mathbf {x} }$. The numerical range includes, in particular, the diagonal entries of the matrix (obtained by choosing x equal to the unit vectors along the coordinate axes) and the eigenvalues of the matrix (obtained by choosing x equal to the eigenvectors).

In engineering, numerical ranges are used as a rough estimate of eigenvalues of A. Recently, generalizations of the 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.

${\displaystyle r(A)=\sup\{|\lambda |:\lambda \in W(A)\}=\sup _{\|x\|=1}|\langle Ax,x\rangle |.}$

## Properties

1. The numerical range is the range of the Rayleigh quotient.
2. (Hausdorff–Toeplitz theorem) The numerical range is convex and compact.
3. ${\displaystyle W(\alpha A+\beta I)=\alpha W(A)+\{\beta \}}$ for all square matrix ${\displaystyle A}$ and complex numbers ${\displaystyle \alpha }$ and ${\displaystyle \beta }$. Here ${\displaystyle I}$ is the identity matrix.
4. ${\displaystyle W(A)}$ is a subset of the closed right half-plane if and only if ${\displaystyle A+A^{*}}$ is positive semidefinite.
5. The numerical range ${\displaystyle W(\cdot )}$ is the only function on the set of square matrices that satisfies (2), (3) and (4).
6. (Sub-additive) ${\displaystyle W(A+B)\subseteq W(A)+W(B)}$, where the sum on the right-hand side denotes a sumset.
7. ${\displaystyle W(A)}$ contains all the eigenvalues of ${\displaystyle A}$.
8. The numerical range of a ${\displaystyle 2\times 2}$ matrix is a filled ellipse.
9. ${\displaystyle W(A)}$ is a real line segment ${\displaystyle [\alpha ,\beta ]}$ if and only if ${\displaystyle A}$ is a Hermitian matrix with its smallest and the largest eigenvalues being ${\displaystyle \alpha }$ and ${\displaystyle \beta }$.
10. If ${\displaystyle A}$ is a normal matrix then ${\displaystyle W(A)}$ is the convex hull of its eigenvalues.
11. If ${\displaystyle \alpha }$ is a sharp point on the boundary of ${\displaystyle W(A)}$, then ${\displaystyle \alpha }$ is a normal eigenvalue of ${\displaystyle A}$.
12. ${\displaystyle r(\cdot )}$ is a norm on the space of ${\displaystyle n\times n}$ matrices.
13. ${\displaystyle r(A)\leq \|A\|\leq 2r(A)}$, where ${\displaystyle \|\cdot \|}$ denotes the operator norm.[1][2][3][4]
14. ${\displaystyle r(A^{n})\leq r(A)^{n}}$

## Bibliography

• Choi, M.D.; Kribs, D.W.; Życzkowski (2006), "Quantum error correcting codes from the compression formalism", Rep. Math. Phys., 58 (1): 77–91, arXiv:quant-ph/0511101, Bibcode:2006RpMP...58...77C, doi:10.1016/S0034-4877(06)80041-8, S2CID 119427312.
• Dirr, G.; Helmkel, U.; Kleinsteuber, M.; Schulte-Herbrüggen, Th. (2006), "A new type of C-numerical range arising in quantum computing", Proc. Appl. Math. Mech., 6: 711–712, doi:10.1002/pamm.200610336.
• Bonsall, F.F.; Duncan, J. (1971), Numerical Ranges of Operators on Normed Spaces and of Elements of Normed Algebras, Cambridge University Press, ISBN 978-0-521-07988-4.
• Bonsall, F.F.; Duncan, J. (1971), Numerical Ranges II, Cambridge University Press, ISBN 978-0-521-20227-5.
• Horn, Roger A.; Johnson, Charles R. (1991), Topics in Matrix Analysis, Cambridge University Press, Chapter 1, ISBN 978-0-521-46713-1.
• Horn, Roger A.; Johnson, Charles R. (1990), Matrix Analysis, Cambridge University Press, Ch. 5.7, ex. 21, ISBN 0-521-30586-1
• Li, C.K. (1996), "A simple proof of the elliptical range theorem", Proc. Am. Math. Soc., 124 (7): 1985, doi:10.1090/S0002-9939-96-03307-2.
• Keeler, Dennis S.; Rodman, Leiba; Spitkovsky, Ilya M. (1997), "The numerical range of 3 × 3 matrices", Linear Algebra and Its Applications, 252 (1–3): 115, doi:10.1016/0024-3795(95)00674-5.
• "Functional Characterizations of the Field of Values and the Convex Hull of the Spectrum", Charles R. Johnson, Proceedings of the American Mathematical Society, 61(2):201-204, Dec 1976.

## References

1. ^
2. ^
3. ^
4. ^ Hilary Priestley. "B4b hilbert spaces: extended synopses 9. Spectral theory" (PDF). In fact, ‖T‖ = max(−mT , MT) = wT. This fails for non-self-adjoint operators, but wT ≤ ‖T‖ ≤ 2wT in the complex case.