Searches for New Heavy Resonances in Final States with Leptons and Photons in ATLAS and CMS

Searches for resonances in final states with leptons and photons have always been a powerful tool for discovery in high energy physics. We present here the latest results from the ATLAS and CMS experiments, based on up to 36.1 fb$^{-1}$ of 13 TeV proton-proton collisions produced at the Large Hadron Collider. Detailed results on single lepton, dilepton, diphoton and Z$\gamma$ resonances are included

Rare decays at LHCb

The results on rare decay processes obtained by the LHCb experiment using 1.0 fb^(-1) of pp collisions collected in 2011 at a centre-of-mass energy of sqrt(s)=7 TeV are presented. Branching fractions, angular distributions, CP and isospin asymmetries are investigated to search for new physics effects.Comment: Proceedings of the XI LISHEP conference, 17-24 March 2013, Rio de Janeiro, Brazil (4 pages, 13 figures

QCD Dual

We uncover a novel solution of the 't Hooft anomaly matching conditions for QCD. Interestingly in the perturbative regime the new gauge theory, if interpreted as a possible QCD dual, predicts the critical number of flavors above which QCD in the nonperturbative regime, develops an infrared stable fixed point. Remarkably this value is identical to the maximum bound predicted in the nonpertubative regime via the all-orders conjectured beta function for nonsupersymmetric gauge theories.Comment: RevTeX, 13 pages. Added discussion on operator matching and flavor decoupling. Version to match the published on

The kinematical Hilbert space of Loop Quantum Gravity from BF theories

In this work, it is demonstrated how the kinematical Hilbert space of Loop Quantum Gravity (LQG) can be inferred from the configuration space of BF theories via the imposition of the Hamiltonian constraints. In particular, it is outlined how the projection to the representations associated with Ashtekar-Barbero connections provides the correct procedure to implement second-class constraints and the corresponding nontrivial induced symplectic structure. Then, the reduction to SU(2) invariant intertwiners is analyzed and the properties of LQG states under Lorentz transformations is discussed.Comment: 13 page

Representations of braid groups and construction of projective surfaces

Braid groups are an important and flexible tool used in several areas of science, such as Knot Theory (Alexander's theorem), Mathematical Physics (Yang-Baxter's equation) and Algebraic Geometry (monodromy invariants). In this note we will focus on their algebraic-geometric aspects, explaining how the representation theory of higher genus braid groups can be used to produce interesting examples of projective surfaces defined over the field of complex numbers.Comment: Note written for the Proceedings of the Conference "Group 32 - The 32nd International Colloquium on Group Theoretical Methods in Physics", held on Czech Technical University (Prague) on July 9-13, 201

Magnetic and radar sensing for multimodal remote health monitoring

With the increased life expectancy and rise in health conditions related to aging, there is a need for new technologies that can routinely monitor vulnerable people, identify their daily pattern of activities and any anomaly or critical events such as falls. This paper aims to evaluate magnetic and radar sensors as suitable technologies for remote health monitoring purpose, both individually and fusing their information. After experiments and collecting data from 20 volunteers, numerical features has been extracted in both time and frequency domains. In order to analyse and verify the validation of fusion method for different classifiers, a Support Vector Machine with a quadratic kernel, and an Artificial Neural Network with one and multiple hidden layers have been implemented. Furthermore, for both classifiers, feature selection has been performed to obtain salient features. Using this technique along with fusion, both classifiers can detect 10 different activities with an accuracy rate of approximately 96%. In cases where the user is unknown to the classifier, an accuracy of approximately 92% is maintained