Noncommutative Black Holes and the Singularity Problem

A phase-space noncommutativity in the context of a Kantowski-Sachs cosmological model is considered to study the interior of a Schwarzschild black hole. Due to the divergence of the probability of finding the black hole at the singularity from a canonical noncommutativity, one considers a non-canonical noncommutativity. It is shown that this more involved type of noncommutativity removes the problem of the singularity in a Schwarzschild black hole.Comment: Based on a talk by CB at ERE2010, Granada, Spain, 6th-10th September 201

A class of cubic Rauzy Fractals

In this paper, we study arithmetical and topological properties for a class of Rauzy fractals ${\mathcal R}_a$ given by the polynomial $x^3- ax^2+x-1$ where $a \geq 2$ is an integer. In particular, we prove the number of neighbors of ${\mathcal R}_a$ in the periodic tiling is equal to $8$. We also give explicitly an automaton that generates the boundary of ${\mathcal R}_a$. As a consequence, we prove that ${\mathcal R}_2$ is homeomorphic to a topological disk

A Multivariate Training Technique with Event Reweighting

An event reweighting technique incorporated in multivariate training algorithm has been developed and tested using the Artificial Neural Networks (ANN) and Boosted Decision Trees (BDT). The event reweighting training are compared to that of the conventional equal event weighting based on the ANN and the BDT performance. The comparison is performed in the context of the physics analysis of the ATLAS experiment at the Large Hadron Collider (LHC), which will explore the fundamental nature of matter and the basic forces that shape our universe. We demonstrate that the event reweighting technique provides an unbiased method of multivariate training for event pattern recognition.Comment: 20 pages, 8 figure

Nonparametric models of financial leverage decisions

This paper investigates the properties of nonparametric decision tree models in the analysis of financial leverage decisions. This approach presents two appealing features: the relationship between leverage ratios and the explanatory variables is not predetermined but is derived according to information provided by the data, and the models respect the bounded and fractional nature of leverage ratios. The analysis shows that tree models suggest relationships between explanatory variables and the relative amount of issued debt that parametric models fail to capture. Furthermore, the significant relationships found by tree models are in most cases in accordance with the effects predicted by the pecking-order theory. The results also show that two-part tree models can accommodate better the distinct effects of explanatory variables on the decision to issue debt and on the amount of debt issued by firms that do resort to debt.Capital structure, Fractional regression, Decision trees, Two-part models

Performance of boosted decision trees for combining ATLAS b-tagging methods

This note evaluates the performance of boosted decision trees for combining the information from different ATLAS b-tagging algorithms into a single jet classifier. The rejection of light quarks given by boosted decision trees is estimated using a Monte Carlo simulation of $WH$ and $t\bar{t}$ events. It is shown that this approach yields significant gains in the rejection of light quarks with respect to a tagging algorithm based in 3D impact parameters and reconstructed secondary vertices

Entropic Gravity, Phase-Space Noncommutativity and the Equivalence Principle

We generalize E. Verlinde's entropic gravity reasoning to a phase-space noncommutativity set-up. This allow us to impose a bound on the product of the noncommutative parameters based on the Equivalence Principle. The key feature of our analysis is an effective Planck's constant that naturally arises when accounting for the noncommutative features of the phase-space.Comment: 12 pages. Version to appear at the Classical and Quantum Gravit