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Kim, J. S., Rolbiecki, K., & Ruiz de Austri, R. (2016). Model-independent combination of diphoton constraints at 750 GeV. Eur. Phys. J. C, 76(5), 251–8pp.
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.
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De Romeri, V., Kim, J. S., Martin Lozano, V., Rolbiecki, K., & Ruiz de Austri, R. (2016). Confronting dark matter with the diphoton excess from a parent resonance decay. Eur. Phys. J. C, 76(5), 262–13pp.
Abstract: A diphoton excess with an invariant mass of about 750 GeV has been recently reported by both ATLAS and CMS experiments at LHC. While the simplest interpretation requires the resonant production of a 750 GeV (pseudo) scalar, here we consider an alternative setup, with an additional heavy parent particle which decays into a pair of 750 GeV resonances. This configuration improves the agreement between the 8 and 13 TeV data. Moreover, we include a dark matter candidate in the form of a Majorana fermion which interacts through the 750 GeV portal. The invisible decays of the light resonance help to suppress additional decay channels into Standard Model particles in association with the diphoton signal. We realise our hierarchical framework in the context of an effective theory, and we analyse the diphoton signal as well as the consistency with other LHC searches. We finally address the interplay of the LHC results with the dark matter phenomenology, namely the compatibility with the relic density abundance and the indirect detection bounds.
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Caron, S., Kim, J. S., Rolbiecki, K., Ruiz de Austri, R., & Stienen, B. (2017). The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning. Eur. Phys. J. C, 77(4), 257–25pp.
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/.
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van Beekveld, M., Beenakker, W., Caron, S., Peeters, R., & Ruiz de Austri, R. (2017). Supersymmetry with dark matter is still natural. Phys. Rev. D, 96(3), 035015–7pp.
Abstract: We identify the parameter regions of the phenomenological minimal supersymmetric standard model (pMSSM) with the minimal possible fine-tuning. We show that the fine-tuning of the pMSSM is not large, nor under pressure by LHC searches. Low sbottom, stop and gluino masses turn out to be less relevant for low fine-tuning than commonly assumed. We show a link between low fine-tuning and the dark matter relic density. Fine-tuning arguments point to models with a dark matter candidate yielding the correct dark matter relic density: a bino-higgsino particle with a mass of 35-155 GeV. Some of these candidates are compatible with recent hints seen in astrophysics experiments such as Fermi-LAT and AMS-02. We argue that upcoming direct search experiments, such as XENON1T, will test all of the most natural solutions in the next few years due to the sensitivity of these experiments on the spin-dependent WIMP-nucleon cross section.
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GAMBIT Collaboration(Athron, P. et al), & Ruiz de Austri, R. (2017). Global fits of GUT-scale SUSY models with GAMBIT. Eur. Phys. J. C, 77(12), 824–44pp.
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.
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