Kleiss, R. H. P., Malamos, I., Papadopoulos, C. G., & Verheyen, R. (2012). Counting to one: reducibility of one- and two-loop amplitudes at the integrand level. J. High Energy Phys., 12(12), 038–24pp.
Abstract: Calculation of amplitudes in perturbative quantum field theory involve large loop integrals. The complexity of those integrals, in combination with the large number of Feynman diagrams, make the calculations very difficult. Reduction methods proved to be very helpful, lowering the number of integrals that need to be actually calculated. Especially reduction at the integrand level improves the speed and set-up of these calculations. In this article we demonstrate, by counting the numbers of tensor structures and independent coefficients, how to write such relations at the integrand level for one-and two-loop amplitudes. We clarify their connection to the so-called spurious terms at one loop and discuss their structure in the two-loop case. This method is also applicable to higher loops, and the results obtained apply to both planar and non-planar diagrams.
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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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Hirsch, M., Reichert, L., & Porod, W. (2011). Supersymmetric mass spectra and the seesaw scale. J. High Energy Phys., 05(5), 086–32pp.
Abstract: Supersymmetric mass spectra within two variants of the seesaw mechanism, commonly known as type-II and type-III seesaw, are calculated using full 2-loop RGEs and minimal Supergravity boundary conditions. The type-II seesaw is realized using one pair of 15 and (15) over bar superfields, while the type-III is realized using three copies of 24(M) superfields. Using published, estimated errors on SUSY mass observables attainable at the LHC and in a combined LHC+ILC analysis, we calculate expected errors for the parameters of the models, most notably the seesaw scale. If SUSY particles are within the reach of the ILC, pure mSugra can be distinguished from mSugra plus type-II or type-III seesaw for nearly all relevant values of the seesaw scale. Even in the case when only the much less accurate LHC measurements are used, we find that indications for the seesaw can be found in favourable parts of the parameter space. Since our conclusions crucially depend on the reliability of the theoretically forecasted error bars, we discuss in some detail the accuracies which need to be achieved for the most important LHC and ILC observables before an analysis, such as the one presented here, can find any hints for type-II or type-III seesaw in SUSY spectra.
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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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Olmo, G. J. (2011). Palatini actions and quantum gravity phenomenology. J. Cosmol. Astropart. Phys., 10(10), 018–15pp.
Abstract: We show that an invariant an universal length scale can be consistently introduced in a generally covariant theory through the gravitational sector using the Palatini approach. The resulting theory is able to capture different aspects of quantum gravity phenomenology in a single framework. In particular, it is found that in this theory field excitations propagating with different energy-densities perceive different background metrics, which is a fundamental characteristic of the DSR and Rainbow Gravity approaches. We illustrate these properties with a particular gravitational model and explicitly show how the soccer ball problem is avoided in this framework. The isotropic and anisotropic cosmologies of this model also avoid the big bang singularity by means of a big bounce.
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