Matrix norm compatible with Euclidean norm that is tighter than Frobenius

matricesmatrix-normsreference-request

Define the matrix-norm

$\|M\|=\left(\sum_{j_1,j_2=1}^n\left|\sum_{i=1}^nM_{ij_1}M_{ij_2}^*\right|^2\right)^{1/4}$

This is smaller than the Frobenius norm and it compatible with the vector 2-norm.

Q: Does this norm have a common denomination/usage?

Let me briefly recap the proofs of the assertions made above:

1) Simply take the quartic root of
$$\|M\|^4=\sum_{j_1,j_2=1}^n\left|\sum_{i=1}^nM_{ij_1}M_{ij_2}^*\right|^2\leq \sum_{i=1}^n\left[\sum_{j=1}^n|M_{ij}|^2\right]\left[\sum_{k=1}^n|M_{ik}|^2\right] \overset{C.S.}{\leq}\left(\left(\sum_{i=1}^n\left[\sum_{j=1}^n|M_{ij}|^2\right]\right)^2\left(\sum_{i=1}^n\left[\sum_{k=1}^n|M_{ik}|^2\right]\right)^2\right)^{1/2}\leq \left(\left[\sum_{i,j=1}^n|M_{ij}|^2\right]^2\left[\sum_{i,k=1}^n|M_{ik}|^2\right]^2\right)^{1/2}=\left[\sum_{i,j=1}^n|M_{ij}|^2\right]^2=\|M\|_F^4$$

2) Consider that for any $v \in \mathbb{C}^n$
$$\|Mv\|_2^2=\sum_{i=1}^n\left|\sum_{j=1}^n M_{ij}v_j\right|^2 = \sum_{i,j_1,j_2=1}^nM_{ij_1}M_{ij_2}^*v_{j_1}v_{j_2}^*=\sum_{j_1=1}^nv_{j_1}\sum_{i,j_2=1}^nM_{ij_1}M_{ij_2}^*v_{j_2}^*\\
\leq
\|v\|_2\left(\sum_{j_1=1}^n\left|\sum_{i,j_2=1}^nM_{ij_1}M_{ij_2}^*v_{j_2}^*\right|^2\right)^{1/2}=\|v\|_2\left(\sum_{j_1=1}^n\left|\sum_{j_2=1}^nv_{j_2}^*\sum_{i=1}^nM_{ij_1}M_{ij_2}^*\right|^2\right)^{1/2}\\
\leq \|v\|_2\left(\sum_{j_1=1}^n\|v\|_2^2\sum_{j_2=1}^n\left|\sum_{i=1}^nM_{ij_1}M_{ij_2}^*\right|^2\right)^{1/2}=\|v\|_2^2\left(\sum_{j_1,j_2=1}^n\left|\sum_{i=1}^nM_{ij_1}M_{ij_2}^*\right|^2\right)^{1/2}\\=\|v\|_2^2\|M\|^2$$

Best Answer

Not sure if it has a name in the literature, but this is just $\|M^\ast M\|_F^{1/2}=\left(\sum_{i=1}^n\sigma_i(M)^4\right)^{1/4}$, the $4$-norm of the singular values of $M$. In contrast, the Frobenius norm $\|M\|_F=\sqrt{\operatorname{tr}(M^\ast M)}=\left(\sum_{i=1}^n\sigma_i(M)^2\right)^{1/2}$ is the $2$-norm of the singular values.

Related Question