Search for flavour-changing neutral currents tZtZ interactions in pppp collisions at s\sqrt{s}=13 TeV with ATLAS

A search for flavour-changing neutral currents (FCNC) processes in proton-proton ($pp$) collisions at a centre-of-mass energy of 13 TeV with the ATLAS detector at the CERN Large Hadron Collider (LHC) is presented. The analysed data collected during the years of 2015 and 2016 corresponds to an integrated luminosity of 36.1 fb$^{-1}$. A search considering top-quark pair-production events is performed, with one top-quark decaying through the dominant Standard Model (SM) mode $t$ $\to$ $Wb$, and the other through the $t$ $\to$ $qZ$ ($q$=$u$,$c$) FCNC channel. The data are consistent with the SM expectation and the observed and expected upper limits on the branching ratio of $t$ $\to$ $uZ$ and $t$ $\to$ $cZ$ are set at 95% confidence level representing an improvement of about a factor 3 compared with the Run-1 data results from the ATLAS Collaboration.Comment: 5 pages, 4 figures, Top2018 conferenc

Model selection and hypothesis testing for large-scale network models with overlapping groups

The effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods yield diverging descriptions of the same network, making both the comparison and understanding of their results a difficult challenge. A possible solution to this outstanding issue is to shift the focus away from ad hoc methods and move towards more principled approaches based on statistical inference of generative models. As a result, we face instead the more well-defined task of selecting between competing generative processes, which can be done under a unified probabilistic framework. Here, we consider the comparison between a variety of generative models including features such as degree correction, where nodes with arbitrary degrees can belong to the same group, and community overlap, where nodes are allowed to belong to more than one group. Because such model variants possess an increasing number of parameters, they become prone to overfitting. In this work, we present a method of model selection based on the minimum description length criterion and posterior odds ratios that is capable of fully accounting for the increased degrees of freedom of the larger models, and selects the best one according to the statistical evidence available in the data. In applying this method to many empirical unweighted networks from different fields, we observe that community overlap is very often not supported by statistical evidence and is selected as a better model only for a minority of them. On the other hand, we find that degree correction tends to be almost universally favored by the available data, implying that intrinsic node proprieties (as opposed to group properties) are often an essential ingredient of network formation.Comment: 20 pages,7 figures, 1 tabl

On the 1-loop calculations of softly broken fermion-torsion theory in curved space using the Stuckelberg procedure

The soft breaking of gauge or other symmetries is the typical Quantum Field Theory phenomenon. In many cases one can apply the Stuckelberg procedure, which means introducing some additional field (or fields) and restore the gauge symmetry. The original softly broken theory corresponds to a particular choice of the gauge fixing condition. In this paper we use this scheme for performing quantum calculations for fermion-torsion theory, softly broken by the torsion mass in arbitrary curved spacetime.Comment: Talk given at the 7th Alexander Friedmann International Seminar on Gravitation and Cosmology, Joao Pessoa, Brazil, 29 Jun - 5 Jul 2008. 4 pages and one figur