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I realize that when a matrix is symmetric, then it must have all real eigenvalues. However, I am doing research on matrices for my own pleasure and I cannot find a mathematical proof or explanation when a matrix will have all real eigenvalues except for when it is symmetric. I am dealing with matrices such as A below and I want to know what is it about A and its characteristic polynomial that gives it real eigenvalues (0, 0, -2)? Similarly, what is it about matrix B that gives it only one real eigenvalue (0) and the other two complex? enter image description here

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5 Answers 5

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There are so-called $\mathcal{PT}$-symmetric matrices which may have purely real eigenvalues. A square matrix $M$ is called $\mathcal{PT}$-symmetric iff it satisfies the property: $$ [\mathcal{PT},M] = 0 \Leftrightarrow \mathcal{P}M = M^*\mathcal{P} $$ where $\mathcal{P}$ is and $\mathcal{T}\equiv*$ is the complex conjugation operator. Further $[\mathcal{P},\mathcal{T}]=0$ and $\mathcal{P}^2=1$, $\mathcal{T}^2=1$ $\Rightarrow (\mathcal{PT})^2=1$. A $\mathcal{PT}$-symmetric matrix is said to have 'unbroken' $\mathcal{PT}$ symmetry iff any eigenvector of $M$ is also an eigenvector of $\mathcal{PT}$.

Claim: If $M$ has unbroken $\mathcal{PT}$ symmetry, this implies that $M$ has real eigenvalues.

Proof: First note that the eigenvalues of $\mathcal{PT}$ are non-zero since the combination is an involution: $\mathcal{PT} u = \mu u \Rightarrow \mathcal{PT}^2 u = u = \mu^*\mu u \Rightarrow |\mu|=1$.

Now let $Mv = \lambda v \Rightarrow \mathcal{PT}Mv = \mathcal{PT} \lambda v$. Thus since the combination $\mathcal{PT}$ is an anti-linear operator and $M$ commutes with $\mathcal{PT}$: $\mathcal{PT} M v = \lambda^*\mathcal{PT}v\Rightarrow \lambda \mu = \lambda^*\mu$. Since we've shown that $\mu\neq0$, this implies $\lambda^* = \lambda$. QED

More on $\mathcal{PT}$-symmetry and related concepts in this article: The English in there isn't perfect but the content looks good.

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Here is one example of sufficient conditions.

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Posting just a link as an answer is rather fragile; links tend to become stale some day. At least you could try to lift from the paper the statement of the conditions you refer to. – Marc van Leeuwen Apr 9 '14 at 6:16

Do you know of companion matrices? See the Wikipedia link here:

They are made-to-order matrices which will have the polynomial you want as its characteristic polynomial. They are far from symmetric matrices. Now start with a polynomial having your favorite real numbers as its roots, and construct the Companion matrix for that polynomial.

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I don't think the question is about how to construct matrices with real eigenvalues, but on how to recognise them. Construction is simple: just take any real triangular matrix and conjugate it by any real invertible matrix (moreover all examples can be obtained in this way). – Marc van Leeuwen Apr 9 '14 at 6:19
Ok, I see the distinction in the question which my answer does not address. – P Vanchinathan Apr 9 '14 at 6:35

Another approach is to construct a triangular matrix with pre-determined diagonal entries; they will be the eigenvalues, and the matrix is not symmetric.

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A necessary and sufficient condition for a matrix$~A$ to have only real eigenvalues (that is, not have any non-real complex eigenvalues) is the existence of a polynomial $P$ that splits into linear factors over the real numbers and such that $P[A]=0$. If such a polynomial exists at all, one can take the characteristic polynomial for$~A$ (but not necessarily the minimal polynomial) as$~P$. This gives a trivially valid, but fairly hard to check condition. Without using eigenvectors, it is actually not so obvious why the characteristic polynomial of a symmetric matrix should always allow such a factorisation. But I don't think one can do much better to completely characterise the case of real-only eigenvalues.

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