|
Edelhauser, L., Porod, W., & Singh, R. K. (2010). Spin discrimination in three-body decays. J. High Energy Phys., 08(8), 053–31pp.
Abstract: The identification of the correct model for physics beyond the Standard Model requires the determination of the spin of new particles. We investigate to which extent the spin of a new particle X can be identified in scenarios where it decays dominantly in three-body decays X -> f (f) over barY. Here we assume that Y is a candidate for dark matter and escapes direct detection at a high energy collider such as the LHC. We show that in the case that all intermediate particles are heavy, one can get information on the spins of X and Y at the LHC by exploiting the invariant mass distribution of the two standard model fermions. We develop a model-independent strategy to determine the spins without prior knowledge of the unknown couplings and test it in a series of Monte Carlo studies.
|
|
|
Cervera-Villanueva, A., Laing, A., Martin-Albo, J., & Soler, F. J. P. (2010). Performance of the MIND detector at a Neutrino Factory using realistic muon reconstruction. Nucl. Instrum. Methods Phys. Res. A, 624(3), 601–614.
Abstract: A Neutrino Factory producing an intense beam composed of v(e)((v) over bar (e)) and (v) over bar (mu)(v(mu)) from muon decays has been shown to have the greatest sensitivity to the two currently unmeasured neutrino mixing parameters theta(13) and delta(CP) Using the wrong-sign muon signal to measure v(e)-> v(mu)((v) over bar (e) ->(v) over bar (mu)) oscillations in a 50kt Magnetised Iron Neutrino Detector (MIND) sensitivity to delta(CP) could be maintained down to small values of theta(13) However the detector efficiencies used in these previous studies were calculated assuming perfect pattern recognition In this paper MIND is reassessed taking into account for the first time a realistic pattern recognition for the muon candidate Reoptimisation of the analysis utilises a combination of methods including a multivariate analysis similar to the one used in MINOS to maintain high efficiency while suppressing backgrounds ensuring that the signal selection efficiency and the background levels are comparable or better than the ones in previous analyses As a result MIND remains the most sensitive future facility for the discovery of CP violation from neutrino oscillations.
|
|
|
Carbone, C., Mena, O., & Verde, L. (2010). Cosmological parameters degeneracies and non-Gaussian halo bias. J. Cosmol. Astropart. Phys., 07(7), 020–17pp.
Abstract: We study the impact of the cosmological parameters uncertainties on the measurements of primordial non-Gaussianity through the large-scale non-Gaussian halo bias effect. While this is not expected to be an issue for the standard Lambda CDM model, it may not be the case for more general models that modify the large-scale shape of the power spectrum. We consider the so-called local non-Gaussianity model, parametrized by the f(NL) non-Gaussianity parameter which is zero for a Gaussian case, and make forecasts on f(NL) from planned surveys, alone and combined with a Planck CMB prior. In particular, we consider EUCLID- and LSST-like surveys and forecast the correlations among f(NL) and the running of the spectral index alpha(s), the dark energy equation of state w, the effective sound speed of dark energy perturbations c(s)(2), the total mass of massive neutrinos M-nu = Sigma m(nu), and the number of extra relativistic degrees of freedom N-nu(rel). Neglecting CMB information on f(NL) and scales k > 0.03h/Mpc, we find that, if N-nu(rel) is assumed to be known, the uncertainty on cosmological parameters increases the error on f(NL) by 10 to 30% depending on the survey. Thus the f(NL) constraint is remarkable robust to cosmological model uncertainties. On the other hand, if N-nu(rel) is simultaneously constrained from the data, the f(NL) error increases by similar to 80%. Finally, future surveys which provide a large sample of galaxies or galaxy clusters over a volume comparable to the Hubble volume can measure primordial non-Gaussianity of the local form with a marginalized 1-sigma error of the order Delta f(NL) similar to 2 – 5, after combination with CMB priors for the remaining cosmological parameters. These results are competitive with CMB bispectrum constraints achievable with an ideal CMB experiment.
|
|
|
Baron, R., Boucaud, P., Dimopoulos, P., Frezzotti, R., Palao, D., Rossi, G., et al. (2010). Light meson physics from maximally twisted mass lattice QCD. J. High Energy Phys., 08(8), 097–41pp.
Abstract: We present a comprehensive investigation of light meson physics using maximally twisted mass fermions for N-f = 2 mass-degenerate quark flavours. By employing four values of the lattice spacing, spatial lattice extents ranging from 2.0 fm to 2.5 fm and pseudo scalar masses in the range 280 less than or similar to m(PS) less than or similar to 650MeV we control the major systematic effects of our calculation. This enables us to confront our N-f = 2 data with SU(2) chiral perturbation theory and extract low energy constants of the effective chiral Lagrangian and derived quantities, such as the light quark mass.
|
|
|
Trotta, R., Johannesson, G., Moskalenko, I. V., Porter, T. A., Ruiz de Austri, R., & Strong, A. W. (2011). Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis. Astrophys. J., 729(2), 106–16pp.
Abstract: Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.
|
|