Bertone, G., Cerdeño, D. G., Fornasa, M., Ruiz de Austri, R., & Trotta, R. (2010). Identification of dark matter particles with LHC and direct detection data. Phys. Rev. D, 82(5), 055008–7pp.
Abstract: Dark matter (DM) is currently searched for with a variety of detection strategies. Accelerator searches are particularly promising, but even if weakly interacting massive particles are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the DM in the Universe Omega(DM). We show that a significantly better reconstruction of the DM properties can be obtained with a combined analysis of LHC and direct detection data, by making a simple Ansatz on the weakly interacting massive particles local density rho(0)((chi) over bar1), i.e., by assuming that the local density scales with the cosmological relic abundance, (rho(0)((chi) over bar1)/rho(DM)) = (Omega(0)((chi) over bar1)/Omega(DM)). We demonstrate this method in an explicit example in the context of a 24-parameter supersymmetric model, with a neutralino lightest supersymmetric particle in the stau coannihilation region. Our results show that future ton-scale direct detection experiments will allow to break degeneracies in the supersymmetric parameter space and achieve a significantly better reconstruction of the neutralino composition and its relic density than with LHC data alone.
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Bertone, G., Cumberbatch, D., Ruiz de Austri, R., & Trotta, R. (2012). Dark Matter searches: the nightmare scenario. J. Cosmol. Astropart. Phys., 01(1), 004–24pp.
Abstract: The unfortunate case where the Large Hadron Collider (LHC) fails to discover physics Beyond the Standard Model (BSM) is sometimes referred to as the “Nightmare scenario” of particle physics. We study the consequences of this hypothetical scenario for Dark Matter (DM), in the framework of the constrained Minimal Supersymmetric Standard Model (cMSSM). We evaluate the surviving regions of the cMSSM parameter space after null searches at the LHC, using several different LHC configurations, and study the consequences for DM searches with ton-scale direct detectors and the IceCube neutrino telescope. We demonstrate that ton-scale direct detection experiments will be able to conclusively probe the cMSSM parameter space that would survive null searches at the LHC with 100 fb(-1) of integrated luminosity at 14TeV. We also demonstrate that IceCube (80 strings plus DeepCore) will be able to probe as much as similar or equal to 17% of the currently favoured parameter space after 5 years of observation.
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Bertone, G., Kong, K. C., Ruiz de Austri, R., & Trotta, R. (2011). Global fits of the minimal universal extra dimensions scenario. Phys. Rev. D, 83(3), 036008–15pp.
Abstract: In theories with universal extra dimensions (UED), the gamma(1) particle, first excited state of the hypercharge gauge boson, provides an excellent dark matter (DM) candidate. Here, we use a modified version of the SUPERBAYES code to perform a Bayesian analysis of the minimal UED scenario, in order to assess its detectability at accelerators and with DM experiments. We derive, in particular, the most probable range of mass and scattering cross sections off nucleons, keeping into account cosmological and electroweak precision constraints. The consequences for the detectability of the gamma(1) with direct and indirect experiments are dramatic. The spin-independent cross section probability distribution peaks at similar to 10(-11) pb, i.e. below the sensitivity of ton-scale experiments. The spin-dependent cross section drives the predicted neutrino flux from the center of the Sun below the reach of present and upcoming experiments. The only strategy that remains open appears to be direct detection with ton-scale experiments sensitive to spin-dependent cross sections. On the other hand, the LHC with 1 fb(-1) of data should be able to probe the current best-fit UED parameters.
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Boubekeur, L., Choi, K. Y., Ruiz de Austri, R., & Vives, O. (2010). The degenerate gravitino scenario. J. Cosmol. Astropart. Phys., 04(4), 005–26pp.
Abstract: In this work, we explore the “degenerate gravitino” scenario where the mass difference between the gravitino and the lightest MSSM particle is much smaller than the gravitino mass itself. In this case, the energy released in the decay of the next to lightest sypersymmetric particle (NLSP) is reduced. Consequently the cosmological and astrophysical constraints on the gravitino abundance, and hence on the reheating temperature, become softer than in the usual case. On the other hand, such small mass splittings generically imply a much longer lifetime for the NLSP. We find that, in the constrained MSSM (CMSSM), for neutralino LSP or NLSP, reheating temperatures compatible with thermal leptogenesis are reached for small splittings of order 10(-2) GeV. While for stau NLSP, temperatures of T-RH similar or equal to 4 x 10(9) GeV can be obtained even for splittings of order of tens of GeVs. This “degenerate gravitino” scenario offers a possible way out to the gravitino problem for thermal leptogenesis in supersymmetric theories.
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Bridges, M., Cranmer, K., Feroz, F., Hobson, M., Ruiz de Austri, R., & Trotta, R. (2011). A coverage study of the CMSSM based on ATLAS sensitivity using fast neural networks techniques. J. High Energy Phys., 03(3), 012–23pp.
Abstract: We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of similar to 10(4) with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.
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