‎‎‎This paper presents a remarkable formula for spectral distance of a given block normal matrix $G_{D_0} = begin{pmatrix}‎ ‎A & B \‎ ‎C & D_0‎ ‎end{pmatrix} $ to set of block normal matrix $G_{D}$ (as same as $G_{D_0}$ except block $D$ which is replaced by block $D_0$)‎, ‎in which $A in mathbb{C}^{ntimes n}$ is invertible‎, ‎$ B in mathbb{C}^{ntimes m}‎, ‎C in mathbb{C}^{mti...

We argue that deep-inelastic diffractive scaling provides fundamental insight into the QCD Pomeron. The logarithmic scaling violations seen experimentally are in conflict with the scale-invariance of the BFKL Pomeron and with phenomenological two-gluon models. Instead the Pomeron appears as a single gluon at short-distances, indicating the appearance of a Super-Critical phase of Reggeon Field T...

We introduce a new quantum Gromov-Hausdorff distance between C∗-algebraic compact quantum metric spaces. Because it is able to distinguish algebraic structures, this new distance fixes a weakness of Rieffel’s quantum distance. We show that this new quantum distance has properties analogous to the basic properties of the classical Gromov-Hausdorff distance, and we give criteria for when a parame...

Clustering is an important data exploration task. A prominent clustering algorithm is agglomerative hierarchical clustering. Roughly, in each iteration, it merges the closest pair of clusters. It was rst proposed way back in 1951, and since then there have been numerous mod-iications. Some of its good features are: a natural, simple, and non-parametric grouping of similar objects which is capab...