This book is a self-contained advanced monograph on inequalities involving the numerical
radius of bounded linear operators acting on complex Hilbert spaces. The study of various …

This study surveys the current status of Quantum Deep Learning Neural Networks. Exciting
breakthroughs may soon bring real quantum neural networks, specifically deep learning …

Numerical range of a Hermitian operator X is defined as the set of all possible expectation
values of this observable among a normalized quantum state. We analyze a modification of …

In quantum mechanics, geometry has been demonstrated as a useful tool for inferring
nonclassical behaviors and exotic properties of quantum systems. One standard approach …

We associate with a k-tuple of hermitian N× N matrices a probability measure on Rk
supported on their joint numerical range: The joint numerical shadow of these matrices …

The totality of normalized density matrices of dimension N forms a convex set in. Working
with the flat geometry induced by the Hilbert–Schmidt distance, we consider images of …

We study operators acting on a tensor product Hilbert space and investigate their product
numerical range, product numerical radius and separable numerical range. Concrete …

We extend the notion of anticoherent spin states to anticoherent subspaces. An anticoherent
subspace of order t is a subspace whose unit vectors are all anticoherent states of order at …

We introduce and initiate the study of a family of higher rank matricial ranges, taking
motivation from hybrid classical and quantum error correction coding theory and its operator …

The restricted numerical range WR (A) of an operator A acting on a D-dimensional Hilbert
space is defined as a set of all possible expectation values of this operator among pure …