# Determinant of the linear map given by conjugation.

Let $S$ denote the space of skew-symmetric $n\times n$ real matrices, where every element $A\in S$ satisfies $A^T+A = 0$.

Let $M$ denote an orthogonal $n\times n$ matrix, and $L_M$ denotes the linear map $$L_M: A\mapsto MAM^{-1}.$$ What is the determinant of $L_M$ as an endomorphism of $S$?

• I'm not sure that $MAM^{-1}$ is skew-symmetric for skew-symmetric $A$ and general invertible $M$: $(MAM^{-1})^T = (M^{-1})^TA^TM^T = -(M^{-1})^TAM^T$. If $M$ is orthogonal, that is, $M^{-1} = M^T$, then $-(M^{-1})^TAM^T = -MAM^T$, so things work. But I have my doubts when $M$ is not orthogonal. Does it work for $M= M^T$, that is, $M$ symmetric? – Robert Lewis Jul 28 '14 at 18:32
• For $M = M^T$, $(MAM^{-1})^T = (M^{-1})^TA^TM^T = - (M^T)^{-1}AM = -M^{-1}AM$; this doesn't look like it will work for skew-symmetric $A$ and general symmetric $M$! – Robert Lewis Jul 28 '14 at 19:15
• See also math.stackexchange.com/questions/275925/… where the case of conjugation on the whole of $M_n(K)$ is discussed – martini Jul 28 '14 at 19:56
• @RobertLewis You are right. I edited the question. – mez Jul 28 '14 at 20:11

Proposition For any orthogonal $n \times n$ matrix $M$, the conjugation map $L_M: S \to S$, $M \mapsto M A M^{-1}$ has determinant $1$ if $M \in SO(n)$ and/or $n$ is odd, and $-1$ if $M \in O(n) - SO(n)$ and $n$ is even.

Lemma For any orthogonal $n \times n$ matrix $M$, $\Phi: M \mapsto \det L_M$ is a homomorphism $O(n) \to \mathbb{R}^*$, that is, $\Phi$ satisfies:

1. $\Phi(I_n) = 1$,
2. $\Phi(MN) = \Phi(M) \Phi(N)$ for all $M, N \in O(n)$, and
3. $\Phi(M^{-1}) = \Phi(M)^{-1}$ for all $M \in O(n)$.

Proof of Lemma This is immediate, because $\Phi$ is a composition of the determinant representation $GL(S) \to \mathbb{R}^*$ and the adjoint representation $O(n) \to GL(S)$, but for readers who aren't familiar with these ideas, we can verify these claims directly.

1. We have $L_{I_n}(A) = I_n A I_n^{-1} = A$, so $L_{I_n}$ is the identity map on $S$, and thus $\Phi(I_n) = \det L_{I_n} = 1$.
2. By definition, $L_{MN}(A) = (MN)A(MN)^{-1} = M(NAN^{-1})M^{-1} = L_M(L_N(A))$, so $\Phi(MN) = \det L_{MN} = \det (L_M \circ L_n) = \det L_M \det L_N = \Phi(M) \Phi(N)$.
3. (Follows from (1) and (2).) $\square$

Proof of Proposition Since $\Phi$ is continuous and $O(n)$ is compact, the image of $\Phi$ is compact, and hence it is contained in $\{\pm 1\}$. (Suppose not; then there is an element $A$ with $\Phi(A) \not\in \{\pm 1\}$, and by inverting [and using (3)] if necessary we can assume $|\Phi(A)| > 1$. Then, by (2) the image under $\Phi$ of the sequence $(A, A^2, A^3, \ldots)$ is $(\det A, (\det A)^2, (\det A)^3, \ldots)$, which is unbounded, a contradiction with the compactness of the image of $\Phi$.) Since $\Phi$ is continuous with discrete components, it is constant on connected components, and by (1) in the Lemma, $\Phi(M) = \Phi(I_n) = \det L_{I_n} = 1$ for $M$ in the connected component of $I_n$ in $O(n)$, namely $SO(n)$. (Notice how quickly we arrive at this result just using a few easy observations.)

Since $O(n) - SO(n)$ is connected and $\Phi$ is constant on connected components, to compute $\det L_M$ for $M$ in this set, it suffices to compute it for a single element (for each $n$). A simple choice is

$Z := \left(\begin{array}{cc} -1 & 0 \\ 0 & I_n \end{array}\right)$.

We compute $\det L_Z$ directly by computing the matrix representation of $L_Z$ in the basis $(F_{ij})_{i < j}$ of $S$, where $F_{ij}$ is the matrix with $(i, j)$ entry $1$, $(j, i)$ entry $-1$, and all other entries zero, so that

$(F_{ij})_{kl} = \delta_{ik} \delta_{jl} - \delta_{il} \delta_{jk}$.

Then, $L_Z(F_{ij}) = Z F_{ij} Z^{-1}$ has entries

$(L_Z(F_{ij}))_{ab} = \sum_{k, l} Z_{ak} (F_{ij})_{kl} Z_{lb} = Z_{ai} Z_{jb} - Z_{aj} Z_{ib}$,

and by construction this is just the $((a, b), (i, j))$ entry $(L_Z)_{(a, b), (i, j)}$ of the matrix representation of $L_Z$ in the basis $(F_{ij})_{i < j}$. We show that this matrix is in fact diagonal, using that $Z_{11} = -1$, $Z_{aa} = 1$ for $a > 1$, and $Z_{ab} = 0$ for $a \neq b$:

When $a = i = 1$ (so that $b, j > 1$), we have

$(L_Z)_{(1, b), (1, j)} = Z_{11} Z_{jb} - Z_{1j} Z_{1b} = -\delta_{jb}$;

when $i = 1$ and $a > 1$ (or, by symmetry of notation, $a = 1$ and $i > 1$, we have

$(L_Z)_{(a, b), (1, j)} = Z_{a1} Z_{jb} - Z_{aj} Z_{ib} = 0$;

when $a, i > 1$, we have

$(L_Z)_{(a, b), (i, j)} = Z_{ai} Z_{jb} - Z_{aj} Z_{ib} = \delta_{ai} \delta_{jb} - \delta_{aj} \delta_{ib} = \delta_{ai} \delta_{jb}$,

where the last equality comes from the fact that if $\delta_{aj} \neq 0$, then $a = j$, so that $i < j = a < b$, so $\delta_{ib} = 0$, that is the latter term in the second-to-last expression in the previous display is always zero.

In summary, the above computations give us that in the basis $(F_{ij})_{i < j}$, the matrix representation of $L_Z$ is diagonal, the $n - 1$ diagonal entries for the basis elements $F_{1j}$ are $-1$, and the remaining diagonal entries are all $1$. Thus, $\det L_Z = (-1)^{n - 1}$ as claimed. $\square$

• @ Travis, $\det(L_M)$ can be $-1$. For instance, take, for $n=2$, $M=\begin{pmatrix}0&1\\1&0\end{pmatrix}\in O^{-}(2)$. – loup blanc Aug 24 '14 at 10:34
• loup, you're right. The error was that elements in $O^-(n)$ cannot be written as $\exp N$ for any $N \in S$, which is a consequence of the fact that $O(n)$ is not connected. I've added a short argument for handling elements in $O^-(n)$ to the end of the reply, which reduces the problem to computing the answer explicitly just once (for each matrix size anyway). – Travis Aug 24 '14 at 13:12
• @ Travis, I also thought that $\det(L_M)=\det(M)$. Unfortunately, it is false: take, for $n=3$, $M=diag(1,1,-1)$ ; then $L_M=diag(1,-1,-1)$. – loup blanc Aug 24 '14 at 15:35
• Thanks, loup, I didn't check your remark and hedged in my answer accordingly, and included the natural guess. I am somewhat surprised that parity arises in this way, perhaps there is a conceptual explanation for it? – Travis Aug 24 '14 at 15:46
• I've rewritten the solution from the scratch, it's now much cleaner and rather easier. – Travis Aug 25 '14 at 5:57

If we stack the entries of the matrices row by row, then $L_M=M\bigotimes M^{-T}:M_n\rightarrow M_n$ is a Kronecker product. The eigenvalues of $L_M$ are the $(\lambda_j/\lambda_k)_{j,k}$ where $\operatorname{spectrum}(M)=(\lambda_j=\exp(i\theta_j))_j$. Finally $\operatorname{spectrum}(L_M)=(\exp(i(\theta_j-\theta_k))_{j,k}$ and each eigenvalue has modulus $1$.

Here we consider $\phi={L_M}_{|S}$; then $\det(\phi)$ is a product (the result is real) of a part of the eigenvalues of $L_M$. Thus $\det(\phi)=\pm 1$. For example, let $n=2$ ; if $M\in O^+(2)$ then $\det(\phi)=1$ ($\phi(s)=s$) and if $M\in O^-(2)$, then $\det(\phi)=-1$ ($\phi(s)=-s$).

EDIT: on can slightly improve the previous result: ${L_M}^T=M^T\bigotimes M^T$ implies that $L_M{L_M}^T=MM^T\bigotimes MM^T=I_{n^2}$ ; moreover $\det(L_M)=\det(M)^{2n}=1$. Then $L_M\in O^+(n^2)$ and $\phi\in O^+(S)$ or $O^-(S)$.

• What do you mean by $M^{-T}$? – user26857 Aug 23 '14 at 19:25
• @ user26857, $M^{-T}$ is $(M^{-1})^T$. – loup blanc Aug 24 '14 at 1:17