The CS decomposition is a way to write the singular value decomposition of a matrix with orthonormal columns. More specifically, taking the notation from these notes (pdf alert), consider a $(n_1+n_2)\times p$ matrix $Q$, with
$$Q=\begin{bmatrix}Q_1 \\ Q_2\end{bmatrix},$$
where $Q_1$ has dimensions $n_1\times p$ and $Q_2$ has dimensions $n_2\times p$.
Assume $Q$ has orthonormal columns, that is, $Q_1^\dagger Q_1+Q_2^\dagger Q_2=I$.
Then the CS decomposition essentially tells us that the SVDs of $Q_1$ and $Q_2$ are related. More specifically, there are unitaries $V, U_1, U_2$ such that
\begin{aligned}
U_1^\dagger Q_1 V=\operatorname{diag}(c_1,…,c_p), \\
U_2^\dagger Q_2 V=\operatorname{diag}(s_1,…,s_q),
\end{aligned}
with $c_i^2+s_i^2=1$ (from which the name of the decomposition comes).
As far as I understand, this means that there is a set of orthonormal vectors $\{v_k\}_k$ such that both $\{Q_1 v_k\}_k$ and $\{Q_2 v_k\}$ are orthogonal sets of vectors (with some relations between their norms).
To prove that this is the case, I start by writing down the SVDs of $Q_1$ and $Q_2$, which tell us that there are unitaries $U_1, U_2, V_1, V_2$, and diagonal positive matrices $D_1, D_2$, such that
\begin{aligned}
Q_1= U_1 D_1 V_1^\dagger, \\
Q_2= U_2 D_2 V_2^\dagger.
\end{aligned}
The condition $Q_1^\dagger Q_1+Q_2^\dagger Q_2=I$ then translates into
$$V_1 D_1^2 V_1^\dagger + V_2 D_2^2 V_2^\dagger=I.$$
Denoting with $v^{(i)}_k$ the $k$-th column of $V_i$, and $P^{(i)}_k\equiv v^{(i)}_k v^{(i)*}_k$ the associated projector, this condition can be seen to be equivalent to
$$\sum_k (d^{(1)}_k)^2 P_k^{(1)}+\sum_k (d^{(2)}_k)^2 P_k^{(2)}=I,\tag A$$
where $d^{(i)}_k\equiv (D_i)_{kk}$.
Now, however, I'm a bit stuck into how to proceed from (A). It seems a generalisation of the things proved in this post and links therein, which show that if a sum of projectors gives the identity then the projectors must be orthogonal, but I'm not sure how to prove this in this case.
Best Answer
To get to $(A)$ and proceed from there to show this equation corresponds to $c_i^2 + s_i^2 = 1$, we need to get to $V_1^\dagger = V_2^\dagger$.
To get there consider the "$QR$" decomposition of $Q_2V_1$ matrix. We can write it as: $$ Q_2V_1 = U_2R\\ Q_2 = U_2RV_1^\dagger $$ where $U_2$ is an orthogonal matrix and $R$ is an upper diagonal matrix.
We have $Q_2Q_2^\dagger = I$ ($Q_2$ is full column rank with orthonormal columns). Therefore: $$ (U_2RV_1^\dagger)(VR^\dagger U_2^\dagger) = I \\ U_2 R R^\dagger U_2^\dagger = I \\ R R^\dagger = U_2^\dagger U_2 = I \\ $$
Hence $R$ must be a diagonal matrix, lets call it $D_2$. Rewriting $Q_2$ we get $$ Q_2V_1 = U_2D_2 \\ Q_2 = U_2D_2V_1^\dagger \\ $$ which is same the SVD of $Q_2 = U_2D_2V_2^\dagger$. Therefore $V_2^\dagger = V_1^\dagger$.
Now using the condition $Q_1^\dagger Q_1+Q_2^\dagger Q_2=I$, we get: $$ (V_1D_1^\dagger U_1^\dagger)(U_1D_1V_1^\dagger) + (V_1D_2^\dagger U_2^\dagger)(U_2D_2V_1^\dagger)) = I \\ V_1 D_1^\dagger D_1 V_1^\dagger + V_1 D_2^\dagger D_2 V_1^\dagger = I \\ V_1(D_1^\dagger D_1 + D_2^\dagger D_2)V_1^\dagger = I \\ D_1^\dagger D_1 + D_2^\dagger D_2 = V_1^\dagger V_1 = I \\ \sum_k (d^{(1)}_k)^2 +\sum_k (d^{(2)}_k)^2 = I \\ $$
if $d^{(1)}_i = c_i$ and $d^{(2)}_i = s_i$, then $c_i^2 + s_i^2 = 1$ for $i = 1, 2, .., p$