I am given a square matrix $A$, and I need to prove that if c is its eigenvalue, then it is also an eigenvalue of its transpose. How should I approach this? Clearly $Av$=$cv$, but I am not sure how to bring transpose into the equation.
If c is an eigenvalue of $A$, is it an eigenvalue of $A^{\mathbf{T}}$?
-
0@Myself: What you want is Jordan canonical form. – 2011-03-04
4 Answers
A simple way would be to look at $\left | A^T-cI \right |$. $\left | A^T-cI \right | = \left| (A-cI)^T \right| = \left| (A-cI) \right|$
EDIT
$\left| B \right|$ denotes the determinant of $B$. First note that for any matrix $B$, $\left| B \right| = \left| B^T \right|$.
(This is true since you get the same determinant if you find the determinant along the row or column.)
$c$ is an eigenvalue of $A$ iff $\left| A - cI\right| = 0$.
Note that $\left| A^T - cI \right| = \left| A^T - cI^T \right| = \left| (A - cI)^T \right| = \left| A - cI\right| = 0$.
Hence, $c$ is an eigenvalue of $A^T$.
-
0Thanks. Going your way, I assume that by || you mean determinant. I am actually not quite clear how to prove that the determinants of those two matrices will be equal to each other (and equal to zero). – 2011-03-04
Another way to look at it is to see that it's equivalent to the following statement: $A$ is regular iff $A^T$ is regular. That follows from the fact that the row rank is equal to the column rank. But I'm not sure how easy it is to show that directly. Anyone?
-
0@Sivaram: By putting $A$ in Jordan form, it suffices to look at a Jordan block. And for a Jordan block, the similarity between itself and its transpose is a mere permutation of basis. – 2011-03-04
Here is another way, that is a bit overboard: Suppose $A:V\rightarrow V$ is a linear operator. Then by definition, $A^t$ is the operator on the dual space $V^*$ given by $\left(A^t(w)\right)(v)=w\left(A(v)\right)$ where $w\in V^*$ and $v\in V$.
Suppose $A$ is invertible and $Ax=\lambda x$. Let $W=\text{span}(x)$ and then decompose $V$ into $V=W\oplus W^c$ where $W^c$ is also invariant under $A$. Let $w$ be any non-zero functional in the annihilator of $W^c$. Then lets look at $A^t(w)$. We have $(A^t(w))(v)=w(A(v))$ for every vector $v$, but it suffices to only consider $v\in W$ or $v\in W^c$. In the previous case, $w(A(v))=w(\lambda v)=\lambda w(v)$, and in the second case $w(A(v))=0$ since $W^c$ is invariant under $A$. Thus $A^t(w)=\lambda w$ so we see the transpose will have the same eigenvalues.
Let $\lambda_1,v_1$ and $\lambda_2,v_2$ be eigenpairs of $A$ and $A^T$ respectively.
$Av_1 = \lambda_1 v_1$
$A^Tv_2 = \lambda_2 v_2$
Therefore,
$v_2^TAv_1 = \lambda_2 v_2^T v_1$
$\lambda_1 v_2^Tv_1 = \lambda_2 v_2^T v_1$
Therefore,
- $v_2^T v_1 = 0$ and $\lambda_1 \neq \lambda_2$.
- $\lambda_1 = \lambda_2$
-
0So what have you shown in the case where $v_2^T v_1=0$? – 2011-03-04