Abstract: We perform the baseline and energy optimization of the Neutrino Factory including the latest simulation results on the magnetized iron detector (MIND). We also consider the impact of tau decays, generated by v(mu) -> v(tau) or v(e) -> v(tau) appearance, on the mass hierarchy, CP violation, and theta(13) discovery reaches, which we find to be negligible for the considered detector. For the baseline-energy optimization for small sin(2) 2 theta(13), we qualitatively recover the results with earlier simulations of the MIND detector. We find optimal baselines of about 2 500km to 5 000km for the CP violation measurement, where now values of E-mu as low as about 12 GeV may be possible. However, for large sin(2) 2 theta(13), we demonstrate that the lower threshold and the backgrounds reconstructed at lower energies allow in fact for muon energies as low as 5 GeV at considerably shorter baselines, such as FNAL-Homestake. This implies that with the latest MIND analysis, low-and high-energy versions of the Neutrino Factory are just two different versions of the same experiment optimized for different parts of the parameter space. Apart from a green-field study of the updated detector performance, we discuss specific implementations for the two-baseline Neutrino Factory, where the considered detector sites are taken to be currently discussed underground laboratories. We find that reasonable setups can be found for the Neutrino Factory source in Asia, Europe, and North America, and that a triangular-shaped storage ring is possible in all cases based on geometrical arguments only.

Abstract: We study the contribution of nu(e) -> nu(tau) -> tau -> μtransitions to the wrong-sign muon sample of the golden channel of the Neutrino Factory. Muons from tau decays are not really a background, since they contain information from the oscillation signal, and represent a small fraction of the sample. However, if not properly handled they introduce serious systematic error, in particular if the detector/analysis are sensitive to muons of low energy. This systematic effect is particularly troublesome for large theta(13) >= 1 degrees and prevents the use of the Neutrino Factory as a precision facility for large theta(13). Such a systematic error disappears if the tau contribution to the golden muon sample is taken into account. The fact that the fluxes of the Neutrino Factory are exactly calculable permits the knowledge of the tau sample due to the nu(e) -> nu(tau) oscillation. We then compute the contribution to the muon sample arising from this sample in terms of the apparent muon energy. This requires the computation of a migration matrix M-ij which describes the contributions of the tau neutrinos of a given energy E-i, to the muon neutrinos of an apparent energy E-j. We demonstrate that applying M-ij to the data permits the full correction of the otherwise intolerable systematic error.

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.