Abstract: We present updated LHC limits on the minimal universal extra dimensions (MUEDs) model from the Run 2 searches. We scan the parameter space against a number of searches implemented in the public code CheckMATE and derive up-to-date limits on the MUED parameter space from 13TeV searches. The strongest constraints come from a search dedicated to squarks and gluinos with one isolated lepton, jets and missing transverse energy. In the procedure, we take into account initial state radiation and stress its importance in the MUED searches, which is not always appreciated.

Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.

Abstract: We present a study on the possibility of searching for long-lived supersymmetric partners with the MoEDAL experiment at the LHC. MoEDAL is sensitive to highly ionising objects such as magnetic monopoles or massive (meta)stable electrically charged particles. We focus on prospects of directly detecting long-lived sleptons in a phenomenologically realistic model which involves an intermediate neutral long-lived particle in the decay chain. This scenario is not yet excluded by the current data from ATLAS or CMS, and is compatible with astrophysical constraints. Using Monte Carlo simulation, we compare the sensitivities of MoEDAL versus ATLAS in scenarios where MoEDAL could provide discovery reach complementary to ATLAS and CMS, thanks to looser selection criteria combined with the virtual absence of background. It is also interesting to point out that, in such scenarios, in which charged staus are the main long-lived candidates, the relevant mass range for MoEDAL is compatible with a potential role of Supersymmetry in providing an explanation for the anomalous events observed by the ANITA detector.

Abstract: We propose a rigorous and effective way to compare experimental and theoretical histograms, incorporating the different sources of statistical and systematic uncertainties. This is a useful tool to extract as much information as possible from the comparison between experimental data with theoretical simulations, optimizing the chances of identifying New Physics at the LHC. We illustrate this by showing how a search in the CMSSM parameter space, using Bayesian techniques, can effectively find the correct values of the CMSSM parameters by comparing histograms of events with multijets + missing transverse momentum displayed in the effective-mass variable. The procedure is in fact very efficient to identify the true supersymmetric model, in the case supersymmetry is really there and accessible to the LHC.

Abstract: We test the impact of the ATLAS and CMS multilepton searches performed at the LHC with 8 as well as 13 TeV center-of-mass energy (using only the pre-2018 results) on the chargino and neutralino sector of the next-to-minimal supersymmetric Standard Model (NMSSM). Our purpose consists in analyzing the actual reach of these searches for a full model and in emphasizing effects beyond the minimal supersymmetric Standard Model (MSSM) that affect the performance of current (MSSM-inspired) electroweakino searches. To this end, we consider several scenarios characterizing specific features of the NMSSM electroweakino sector. We then perform a detailed collider study, generating Monte Carlo events through PYTHIA and testing against current LHC constraints implemented in the public tool CheckMATE. We find e.g., that supersymmetric decay chains involving intermediate singlino or Higgs-singlet states can modify the naive MSSM-like picture of the constraints by inducing final states with softer or less easily identifiable SM particles-reversely, a compressed configuration with singlino next-to-lightest supersymmetric particle occasionally induces final states that are rich with photons, which could provide complementary search channels.