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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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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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Cabrera, M. E., Casas, J. A., Ruiz de Austri, R., & Trotta, R. (2011). Quantifying the tension between the Higgs mass and (g-2)(mu) in the constrained MSSM. Phys. Rev. D, 84(1), 015006–7pp.
Abstract: Supersymmetry has often been invoked as the new physics that might reconcile the experimental muon magnetic anomaly, a(mu), with the theoretical prediction (basing the computation of the hadronic contribution on e(+)e(-) data). However, in the context of the constrained minimal supersymmetric standard model (CMSSM), the required supersymmetric contributions (which grow with decreasing supersymmetric masses) are in potential tension with a possibly large Higgs mass (which requires large stop masses). In the limit of very large m(h) supersymmetry gets decoupled, and the CMSSM must show the same discrepancy as the standard model with a(mu). But it is much less clear for which size of m(h) does the tension start to be unbearable. In this paper, we quantify this tension with the help of Bayesian techniques. We find that for m(h) >= 125 GeV the maximum level of discrepancy given the current data (similar to 3.2 sigma) is already achieved. Requiring less than 3 sigma discrepancy, implies m(h) less than or similar to 120 GeV. For a larger Higgs mass we should give up either the CMSSM model or the computation of a(mu) based on e(+)e(-); or accept living with such an inconsistency.
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Feroz, F., Cranmer, K., Hobson, M., Ruiz de Austri, R., & Trotta, R. (2011). Challenges of profile likelihood evaluation in multi-dimensional SUSY scans. J. High Energy Phys., 06(6), 042–23pp.
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.
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Johannesson, G., Ruiz de Austri, R., Vincent, A. C., Moskalenko, I. V., Orlando, E., Porter, T. A., et al. (2016). Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion. Astrophys. J., 824(1), 16–19pp.
Abstract: We present the results of the most complete scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine-learning package. This is the first study to separate out low-mass isotopes (p, (p) over bar and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit p, (p) over bar, and He data are significantly different from those that fit light elements, including the B/C and Be-10/Be-9 secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests that each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best-fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update.
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