Rigidity of the structured singular value and applications
Sourav Pal, Nitin Tomar

TL;DR
This paper investigates the rigidity properties of the structured singular value $_E$, characterizes when it coincides with classical norms, and explores its applications to specific matrix subspaces and domains.
Contribution
It proves a rigidity theorem for $_E$ on scalar multiples of the identity and diagonal matrices, and characterizes subspaces where $_E$ equals the operator norm.
Findings
$_E$ equals $_F$ only if $E=F$ for scalar multiples of identity and diagonal matrices.
There exists a subspace of symmetric matrices where $_E$ equals the operator norm.
No subspace of $M_2( C)$ has $_E$ equal to the numerical radius.
Abstract
The structured singular value for a linear subspace of is defined by \[ \mu_E(A)=1 / \inf\{\|X\| \ : \ X \in E, \ \det(I_n-AX)=0 \} \quad (A \in M_n(\mathbb{C})), \] and if there is no with . It is well-known that coincides with the spectral radius when and when , for all . Also, for any linear subspace satisfying , we have . We prove that if and is any linear subspace of containing , then if and only if . We prove the exact same rigidity theorem for the linear subspace consisting of the diagonal matrices of order . On the contrary, when…
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