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Let $A, B$ be square matrices over $\Bbb C$. Prove that matrices $AB$ and $BA$ have the same characteristic polynomial.


I know it's a famous problem and found various answers. However, I am at my first year of math degree and my knowledge is very limited.

I have never seen matrix which the entires of the matrix is matrices themselves. We never spoke in the class about limits of matrices (those the sort of solutions I saw online).

So, this question is kind of "challenge" for us to prove with our basic linear algebra knowledge. If any one knows a solution (complicated as it may be as long as it dosent require more than the basic knowledge) it would help a lot. thank you very much

Matt Samuel
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FreeZe
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  • Have you considered a proof along these lines, then? – Ben Grossmann Apr 13 '20 at 13:11
  • Also, note that a matrix "which the entries of the matrix is matrices themselves" is called a block matrix. – Ben Grossmann Apr 13 '20 at 13:12
  • This proof is a very nice one that doesn't use any advanced linear algebra knowledge, but requires some explanation. – Ben Grossmann Apr 13 '20 at 13:17
  • @Omnomnomnom i saw this proof. one thing i do not understand: obviously the challenging part is proving the statement for singular matrices. so detA=0 (otherwise it would be easy) so how can we assume that detA=/= 0 ? – FreeZe Apr 13 '20 at 13:19
  • That's exactly where taking a "limit of matrices" is useful, which is something I was taking for granted at first. In any case, I'm working on explaining that last proof in detail. – Ben Grossmann Apr 13 '20 at 13:21
  • @Omnomnomnom thanks! the problem with the "limit of matrices" proof, is that i cant explain with my limited tools why the function that maps matrices to its polynomial is continious – FreeZe Apr 13 '20 at 13:25
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    As far as that explanation goes: the function that takes $A$ to $\det(A - x I)$ is a combination of the functions $A - xI$ followed by the determinant function, and the composition of continuous functions is continuous. Showing that those functions are individually continuous is easy, but ultimately requires that you say what exactly you mean by "continuous". – Ben Grossmann Apr 13 '20 at 13:28

3 Answers3

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Here is a classical solution.

Step 1 If $B$ is invertible.

Then \begin{align}P_{AB}(x)&= \det(xI-AB)\\&=\det(xB^{-1}B-AB)\\&= \det(xB^{-1}-A) \det(B)\\&=\det(B) \det(xB^{-1}-A)\\& = \det(xI-BA)\end{align}

Step 2 The general case.Let $B$ be arbitrary.

We want to show that $$\det(\lambda I-AB)=\det(\lambda I -BA)$$ for all $\lambda$.

Fix an arbitrary $\lambda$. Define $$P(x)= \det(\lambda I-A(B-xI))-\det(\lambda I -(B-xI)A)$$ This is a polynomial in $x$ of degree at most $n$. Moreover, by Step 1, we have $P(x)=0$ for all $x$ which are not eigenvalues of $B$. Therefore, $P$ has infinitely many roots and hence $$P=0$$

In particular $P(0)=0$ which shows the claim.

N. S.
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I provide here a detailed (and to some extent elementary) explanation of this proof. Note that we assume the (fairly elementary) fact that for square matrices $A,B$, we have $\det(AB) = \det(A)\det(B)$.

With that, we proceed as follows. Let $n$ be the size of the matrices $A$ and $B$.

$\det(A)$ is a polynomial on the entries of $A$. For example, when $A$ is $2 \times 2$, we have $$ \det A = a_{11}a_{22} - a_{12}a_{21}. $$ The above expression for $\det(A)$ is a "polynomial" in that it requires only addition and multiplication.

Note: In general, a similar expression can be attained with the Leibniz expansion of the determinant. Just as the polynomial $f(x,y) = x^2 - 2y^2 + xy$ is a polynomial on two variables, so is the determinant of $A$ a polynoimal on $n^2$ variables.

Similarly, $p_1 = \det(xI - AB)$ and $p_2 = \det(x I - BA)$ are polynomials on the entries $a_{ij}$ of $A$, the entries $b_{ij}$ of $B$, and $x$. Our goal is to show that $p_1 = p_2$. The key to the proof is the following: $$ \begin{align} \det(A)\cdot p_1 &= \det(xI - AB)\det(A) = \det([xI - AB]A) = \det(xA - ABA) \\ & = \det(A[x I - BA]) = \det(A) \det(x I - BA) = \det(A)\cdot p_2. \end{align} $$ Now, it suffices to show that the following is true.

Claim: Suppose that $p_1,p_2,q$ are non-zero polynomials on $m$ variables such that $$ q(x_1,\dots,x_m)p_1(x_1,\dots,x_m) = q(x_1,\dots,x_m)p_2(x_1,\dots,x_m). $$ Then it must hold that $p_1 = p_2$.

Proof: Let $p = p_1 - p_2$. It is equivalent to show that if $q\cdot p = 0$, then $p = 0$. In other words, it suffices to show that $\Bbb C[x_1,\dots,x_m]$ is an integral domain, as is done on this post.

Ben Grossmann
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  • I'm struggling to find a version of the proof of the claim that doesn't either appeal to abstract algebra or get bogged down in notation. Maybe something can be done by taking advantage of the fact that we're working over $\Bbb C$. – Ben Grossmann Apr 13 '20 at 13:59
  • if we are working over C. dosent it mean that detA. det(xI-AB) and det(xI-BA) are polynomilas with 1 variable x ? if the answer is yes, there must be a simple way to prove that for polynomials over C: if p1p2=p1p3 then p2=p3 – FreeZe Apr 13 '20 at 14:37
  • @I If you only consider the expression to be a function of the variable $x$, then you have a polynomial over the one variable $x$. However, the point of this proof is that I'm considering the expressions to be polynomials over the entries of $A$ and $B$ as well – Ben Grossmann Apr 13 '20 at 14:38
  • @I If you don't consider the expression to be a polynomial over the entries of $A$, then the case of $\det(A) = 0$ is still problematic – Ben Grossmann Apr 13 '20 at 14:40
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    @I I would say that that N.S's approach is the better one for you to take. – Ben Grossmann Apr 13 '20 at 14:41
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Here's a simple proof that assumes OP knows how to telescope a finite geometric series and take a limit of a (complex) scalar sequence.

main idea is observing:
$\text{trace}\Big(\big(AB\big)^k\Big)=\text{trace}\Big(\big(BA\big)^k\Big)$ for $k \in\{1,2,3,...\}$

and the below proves that if traces of two $\text{n x n}$ complex matrices match for all powers of $k$, then the two matrices have the same eigenvalues. (With a lot more work the below can be developed into Newton's Identities though that seemed outside the scope.)

with $AB$ having distinct eigenvalues $\lambda_{AB}=\{\lambda_1, \lambda_2, ..., \lambda_d\}$ and $BA$ having distinct eigenvalues $\lambda_{BA}=\{\gamma_1, \gamma_2, ..., \gamma_r\}$. Between the two sets, there is a maximum modulus eigenvalue denoted $\sigma$. And for purposes of ordering, in each case the ordering is from smallest modulus to largest.

$x \in \mathbb C, \big \vert x\big \vert \gt \sigma$
i.e. $x$ may be any value on the complex plane outside the circle with radius $\sigma$ (that is centered at the origin)

$\sum_{k=1}^d\alpha_k\frac{1-(\frac{\lambda_k}{x})^m}{1-\frac{\lambda_k}{x}} =n + \sum_{k=1}^{m-1} \text{trace}\Big(\big(\frac{1}{x}AB\big)^k\Big) =n + \sum_{k=1}^{m-1} \text{trace}\Big(\big(\frac{1}{x}BA\big)^k\Big)=\sum_{j=1}^r\beta_j\frac{1-(\frac{\gamma_j}{x})^m}{1-\frac{\gamma_j}{x}}$

where $\alpha_k$ and $\beta_j$ are positive integers, i.e. denoting the algebraic multiplicities of the eigenvalues. Taking limits as $m\to \infty$

$\sum_{k=1}^d\alpha_k\frac{1}{1-\frac{\lambda_k}{x}}= \sum_{j=1}^r\beta_j\frac{1}{1-\frac{\gamma_j}{x}}$
suppose WLOG that $\vert \lambda_d\vert =\sigma$ and multiply each side by $(1-\frac{\lambda_d}{x})$

$LHS=(1-\frac{\lambda_d}{x})\sum_{k=1}^d\alpha_k\frac{1}{1-\frac{\lambda_k}{x}}= (1-\frac{\lambda_d}{x})\sum_{j=1}^r\beta_j\frac{1}{1-\frac{\gamma_j}{x}}=RHS$

take a limit as $x\to \lambda_d$ e.g. sequentially $x_t = (1 +\frac{1}{t})\lambda_d$

$0\lt \alpha_d= \lim_{x\to \lambda_d}\sum_{j=1}^r\beta_j(1-\frac{\lambda_d}{x})\frac{1}{1-\frac{\gamma_j}{x}}$
but $\lim_{x\to \lambda_d}(1-\frac{\lambda_d}{x})\frac{1}{1-\frac{\gamma_j}{x}}= 1$ iff $\gamma_j = \lambda_d$ and 0 otherwise.
Thus there is a maximum modulus eigenvalue in common with the same algebraic multiplicities and the labeling (other than for modulus purposes) is arbitrary so assume WLOG that $\gamma_r = \lambda_d$. Thus $\beta_r = \alpha_d$. Now recurse on the strictly smaller subproblem

$LHS=\sum_{k=1}^{d-1}\alpha_k\frac{1}{1-\frac{\lambda_k}{x}}= \sum_{j=1}^{r-1}\beta_j\frac{1}{1-\frac{\gamma_j}{x}}=RHS$

user8675309
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