Abstract: We perform a classification of all potential supersymmetric R-parity violating signatures at the LHC to address the question: are existing bounds on supersymmetric models robust, or are there still signatures not covered by existing searches, allowing LHCscale supersymmetry to be hiding? We analyze all possible scenarios with one dominant RPV trilinear coupling at a time, allowing for arbitrary LSPs and mass spectra. We consider direct production of the LSP, as well as production via gauge-cascades, and find 6 different experimental signatures for the LL <overline> E -case, 6 for the LQ <overline> D -case, and 5 for the <overline> U <overline> D <overline> D -case; together these provide complete coverage of the RPV-MSSM landscape. This set of signatures is confronted with the existing searches by ATLAS and CMS. We find all signatures have been covered at the LHC, although not at the sensitivity level needed to probe the direct production of all LSP types. For the case of a dominant LL <overline> E -operator, we use CheckMATE to quantify the current lower bounds on the supersymmetric masses and find the limits to be comparable to or better than the R-parity conserving case. Our treatment can be easily extended to scenarios with more than one non-zero RPV coupling.

Abstract: The results of a search for new phenomena in final states with b-jets and missing transverse momentum using 139 fb(-1) of proton-proton data collected at a centre-of-mass energy root s = 13 TeV by the ATLAS detector at the LHC are reported. The analysis targets final states produced by the decay of a pair-produced supersymmetric bottom squark into a bottom quark and a stable neutralino. The analysis also seeks evidence for models of pair production of dark matter particles produced through the decay of a generic scalar or pseudoscalar mediator state in association with a pair of bottom quarks, and models of pair production of scalar third-generation down-type leptoquarks. No significant excess of events over the Standard Model background expectation is observed in any of the signal regions considered by the analysis. Bottom squark masses below 1270 GeV are excluded at 95% confidence level if the neutralino is massless. In the case of nearly mass-degenerate bottom squarks and neutralinos, the use of dedicated secondary-vertex identification techniques permits the exclusion of bottom squarks with masses up to 660 GeV for mass splittings between the squark and the neutralino of 10 GeV. These limits extend substantially beyond the regions of parameter space excluded by similar ATLAS searches performed previously.

Abstract: A search for strongly produced supersymmetric particles using signatures involving multiple energetic jets and either two isolated same-sign leptons (e or mu), or at least three isolated leptons, is presented. The analysis relies on the identification of b-jets and high missing transverse momentum to achieve good sensitivity. A data sample of proton-proton collisions at root s = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to a total integrated luminosity of 36.1 fb(-1), is used for the search. No significant excess over the Standard Model prediction is observed. The results are interpreted in several simplified supersymmetric models featuring R-parity conservation or R-parity violation, extending the exclusion limits from previous searches. In models considering gluino pair production, gluino masses are excluded up to 1.87 TeV at 95% confidence level. When bottom squarks are pair-produced and decay to a chargino and a top quark, models with bottom squark masses below 700 GeV and light neutralinos are excluded at 95% confidence level. In addition, model-independent limits are set on a possible contribution of new phenomena to the signal region yields.

Abstract: We study the phenomenology of a supersymmetric left-right model, assuming minimal supergravity boundary conditions. Both left-right and (B-L) symmetries are broken at an energy scale close to, but significantly below the GUT scale. Neutrino data is explained via a seesaw mechanism. We calculate the RGEs for superpotential and soft parameters complete at 2-loop order. At low energies lepton flavour violation (LFV) and small, but potentially measurable mass splittings in the charged scalar lepton sector appear, due to the RGE running. Different from the supersymmetric “pure seesaw” models, both, LFV and slepton mass splittings, occur not only in the left-but also in the right slepton sector. Especially, ratios of LFV slepton decays, such as Br((tau) over bar (R) -> μchi(0)(1))/Br((tau) over bar (L) -> μchi(0)(1)) are sensitive to the ratio of (B-L) and left-right symmetry breaking scales. Also the model predicts a polarization asymmetry of the outgoing positrons in the decay mu(+) -> e(+)gamma, A similar to [0, 1], which differs from the pure seesaw “prediction” A = 1. Observation of any of these signals allows to distinguish this model from any of the three standard, pure (mSugra) seesaw setups.

Abstract: Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist confidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MULTINEST, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration previously used in the literarture is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MULTINEST configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MULTINEST is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.