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Let $A$ be a square complex matrix, $R_i=\sum_{j\ne i}\left|a_{ij}\right|\quad 1\leq i\leq n$ Let's consider the ovals of this kind: $O_{ij}=\left\{z\in\mathbb{C}:\left|z-a_{ii}\right|\left|z-a_{jj}\right|\leq R_iR_j\right\}\quad \forall i\ne j$ Such ovals are called Cassini ovals.
Theorem (A. Brauer): All the eigenvalues of A lie inside the union of these $\frac{n(n-1)}{2}$ ovals of Cassini:$\sigma(A)\subseteq\bigcup_{i\ne j}O_{ij}$
Proof: Let $(\lambda,\mathbf{v})$ be an eigenvalue-eigenvector pair for $A$ and let $v_p,v_q$ be the components of $\mathbf{v}$ with the two maximal absolute values, that is $\left|v_p\right|\geq\left|v_q\right|\geq\left|v_i\right|\quad \forall i\ne p$ (Note that $\left|v_p\right|\ne 0$ otherwise $\mathbf{v}$ should be all-zero, in contrast with eigenvector definition). We can also assume that $\left|v_q\right|$ is not zero, because otherwise $A\mathbf{v}=\lambda\mathbf{v}$ would imply $a_{pp}=\lambda$ which trivially verifies the thesis. Then, since $A\mathbf{v}=\lambda\mathbf{v}$ we have:
$(\lambda-a_{pp})v_p=\sum_{j=1,j\ne p}^n a_{pj}v_j$ and so
$\left|\lambda-a_{pp}\right|\left|v_p\right|=\left|\sum_{j=1,j\ne p}^n a_{pj}v_j\right|\leq\sum_{j=1,j\ne p}^n\left|a_{pj}\right|\left|v_j\right|\leq\sum_{j=1,j\ne p}^n\left|a_{pj}\right|\left|v_q\right|=R_p\left|v_q\right|$ that is
$\left|\lambda-a_{pp}\right|\leq R_p\frac{\left|v_q\right|}{\left|v_p\right|}$
In the same way, we obtain:
$\left|\lambda-a_{qq}\right|\leq R_q\frac{\left|v_p\right|}{\left|v_q\right|}$
Multiplying the two inequalities, the two fractional terms vanish, and we get:
$\left|\lambda-a_{pp}\right|\left|\lambda-a_{qq}\right|\leq R_pR_q$ which is the thesis.$\square$ Remarks:
1) Much like the Levy-Desplanques theorem states a sufficient condition, based on Gerschgorin circles, for non-singularity of a matrix, Brauer's theorem can be employed to state a similar sufficient condition; namely, the following result of Ostrowski holds:
Corollary: Let $A$ be a $n\times n$ complex-valued matrix; if for all $i\ne j$ we have $\left|a_{ii}\right|\left|a_{jj}\right|>R_iR_j$ then $A$ is non singular.
The proof is obvious, since, by Brauer's theorem, the above condition excludes the point $z=0$ from the spectrum of $A$ implying this way $\det(A)\ne 0$
2) Since both Gerschgorin's and Brauer's results rely upon the same $2n$ numbers, namely $\left\{a_{ii}\right\}_{i=1}^n$ and $\left\{R_i\right\}_{i=1}^n$ one may wonder if Brauer's result is stronger than Gerschgorin's one; actually, the answer is positive, as the following inclusion shows:
Corollary: Let $G(A)=\bigcup_{i=1}^n D_i(A)$ and $B(A)=\bigcup_{i\ne j}^n O_{ij}(A)$ be respectively Gershgorin and Brauer eigenvalues inclusion regions ($D_i(A)$ are the Gerschgorin circles and $O_{ij}(A)$ are the Brauer's Cassini ovals); then
$B(A)\subseteq G(A)$
Proof: Let $O_{ij}$ be one of the $n(n-1)/2$ ovals of Cassini for matrix $A$ and be $z\in O_{ij}$ If $R_i=0$ or $R_j=0$ Brauer's theorem imply $z=a_{ii}$ or $z=a_{jj}$ respectively; but since both $a_{ii}$ and $a_{jj}$ belong to their respective Gerschgorin circles, we have $z\in(D_i\cup D_j)$ If both $R_i>0$ and $R_j>0$ then we can write:
$\frac{\left|z-a_{ii}\right|}{R_i}\cdot\frac{\left|z-a_{jj}\right|}{R_j}\leq 1.$ For the left-hand side to be not greater than 1, $\frac{\left|z-a_{ii}\right|}{R_i}$ or $\frac{\left|z-a_{jj}\right|}{R_j}$ must be not greater than 1, which in turn means $z\in D_i$ or $z\in D_j$ that is $z\in(D_i\cup D_j)$ This way, we proved that $O_{ij}\subseteq(D_i\cup D_j)$ now, we have:
$B(A)=\bigcup_{i\ne j}O_{ij}\subseteq\bigcup_{i=1}^n D_i=G(A)$
3) It's obvious from definition that there are infinitely many matrices which generate the same ovals of Cassini: namely, let's define
$\Omega(A)=\left\{M\in\mathbf{C}^{n\times n}: m_{ii}=a_{ii}, R_i(M)=R_i(A)\right\}$ as the set of all matrices which share the same ovals of Cassini as $A$ Then, by Brauer's theorem, we have, for all $M\in\Omega$ matrices, $$ \sigma(M)\subseteq B(A), $$ and therefore, having defined $\sigma(\Omega)=\bigcup_{M\in\Omega}\sigma(M)$ we have $$ \sigma(\Omega)\subseteq B(A). $$
One may then ask how sharp this inclusion is, which, informally speaking, is equivalent to asking how "efficient" is the "use", by Brauer's theorem, of the 2n pieces of information $\left\{a_{ii}\right\}_{i=1}^n$ and $\left\{R_i\right\}_{i=1}^n$ in the construction of inclusion sets (if for example we found the inclusion to be very loose, that is $\sigma(\Omega)$ to be a very little subset of $B(A)$ we could conjecture that the knowledge of the 2n numbers used by Brauer's theorem should have led to a more precise bounding, since the spectra of all matrices which share these numbers lie in a much smaller region). It has been proven that actually $$ \sigma(\Omega)=B(A), $$ thus showing Brauer's ovals are optimal ones under this point of view.
- 1
- S. Gerschgorin, Uber die Abgrenzung der Eigenwerte einer Matrix, Isv. Akad. Nauk USSR Ser. Mat., 7 (1931), pp. 749-754
- 2
- A. Brauer, Limits for the characteristic roots of a matrix II, Duke Math. J. 14 (1947), pp. 21-26
- 3
- R. S. Varga and A. Krautstengl, On Gersgorin-type problems and ovals of Cassini, Electron. Trans. Numer. Anal., 8 (1999), pp. 15-20
- 4
- Richard S. Varga, Gersgorin-type eigenvalue inclusion theorems and their sharpness,Electronic Transactions on Numerical Analysis. Volume 12 (2001), pp. 113-133
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