Abstract: As we anticipate the first results of the 2016 run, we assess the discovery potential of the LHC to “natural supersymmetry.” To begin with, we explore the region of the model parameter space that can be excluded with various center-of-mass energies (13 TeV and 14 TeV) and different luminosities (20 fb(-1), 100 fb(-1), 300 fb(-1) and 3000 fb(-1)). We find that the bounds at 95% C.L. on stops vary from m((t1) over tilde) greater than or similar to 800 GeV expected this summer to m((t1) over tilde) greater than or similar to 1500 GeV at the end of the high luminosity run, while gluino bounds are expected to range from m((g) over tilde) greater than or similar to 1700 GeV to m((g) over tilde) greater than or similar to 2500 GeV over the same time period. However, more pessimistically, we find that if no signal begins to appear this summer, only a very small region of parameter space can be discovered with 5 sigma significance. For this conclusion to change, we find that both theoretical and systematic uncertainties will need to be significantly reduced.

Abstract: Motivated by the recent diphoton excess reported by both the ATLAS and CMS collaborations, we provide a model-independent combination of diphoton results obtained at root s = 8 and 13 TeV at the LHC. We consider resonant s-channel production of a spin-0 and spin-2 particle with a mass of 750 GeV that subsequently decays to two photons. The size of the excess reported by ATLAS appears to be in a slight tension with other measurements under the spin-2 particle hypothesis.

Abstract: A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300,000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce theATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/.

Abstract: We present the most comprehensive global fits to date of three supersymmetric models motivated by grand unification: the Constrained Minimal Supersymmetric Standard Model (CMSSM), and its Non-Universal Higgs Mass generalisations NUHM1 and NUHM2. We include likelihoods from a number of direct and indirect dark matter searches, a large collection of electroweak precision and flavour observables, direct searches for supersymmetry at LEP and Runs I and II of the LHC, and constraints from Higgs observables. Our analysis improves on existing results not only in terms of the number of included observables, but also in the level of detail with which we treat them, our sampling techniques for scanning the parameter space, and our treatment of nuisance parameters. We show that stau co-annihilation is now ruled out in the CMSSM at more than 95% confidence. Stop co-annihilation turns out to be one of the most promising mechanisms for achieving an appropriate relic density of darkmatter in all threemodels, whilst avoiding all other constraints. We find high-likelihood regions of parameter space featuring light stops and charginos, making them potentially detectable in the near future at the LHC. We also show that tonne-scale direct detection will play a largely complementary role, probing large parts of the remaining viable parameter space, including essentially all models with multi-TeV neutralinos.

Abstract: We analyze a displaced dilepton signal expected at the LHC for a tau left sneutrino as the lightest supersymmetric particle with a mass in the range 45-100 GeV. The sneutrinos are pair produced via a virtual W, Z or gamma in the s channel and, given the large value of the tau Yukawa coupling, their decays into two dileptons or a dilepton plus missing transverse energy from neutrinos can be significant. The discussion is carried out in the framework of the μnu SSM, where the presence of R-parity violating couplings involving right-handed neutrinos solves the μproblem and can reproduce the neutrino data. To probe the tau left sneutrinos we compare the predictions of this scenario with the ATLAS search for long-lived particles using displaced lepton pairs in pp collisions at root s = 8 TeV, allowing us to constrain the parameter space of the model. We also consider an optimization of the trigger requirements used in existing displaced-vertex searches by means of a high level trigger that exploits tracker information. This optimization is generically useful for a light metastable particle decaying into soft charged leptons. The constraints on the sneutrino turn out to be more stringent. We finally discuss the prospects for the 13 TeV LHC searches as well as further potential optimizations.