Statistical Pattern Recognition: Application to ${\nu }_{\mu }\to {\nu }_{\tau }$ Oscillation Searches Based on Kinematic Criteria

Abstract

Classic statistical techniques (like the multi-dimensional likelihood and the Fisher discriminant method) together with Multi-layer Perceptron and Learning Vector Quantization Neural Networks have been systematically used in order to find the best sensitivity when searching for ${\nu }_{\mu }\to {\nu }_{\tau }$ oscillations. We discovered that for a general direct ${\nu }_{\tau }$ appearance search based on kinematic criteria: a) An optimal discrimination power is obtained using only three variables ($E_{visible}$, $P_T^{miss}$ and ${\rho }_l$) and their correlations. Increasing the number of variables (or combinations of variables) only increases the complexity of the problem, but does not result in a sensible change of the expected sensitivity. b) The multi-layer perceptron approach offers the best performance. As an example to assert numerically those points, we have considered the problem of ${\nu }_{\tau }$ appearance at the CNGS beam using a Liquid Argon TPC detector.

24 pages, 15 figures

References in corpus (15)

• Evidence for oscillation of atmospheric neutrinos
• Direct Evidence for Neutrino Flavor Transformation from Neutral-Current Interactions in the Sudbury Neutrino Observatory
• First Results from KamLAND: Evidence for Reactor Anti-Neutrino Disappearance
• Indications of Neutrino Oscillation in a 250 km Long-baseline Experiment
• Evidence for an oscillatory signature in atmospheric neutrino oscillation
• Golden measurements at a neutrino factory
• Neutrino Beams from Muon Storage Rings: Characteristics and Physics Potential
• Neutrino oscillation physics with a neutrino factory
• Final NOMAD results on nu_mu->nu_tau and nu_e->nu_tau oscillations including a new search for nu_tau appearance using hadronic tau decays
• Long-Baseline Study of the Leading Neutrino Oscillation at a Neutrino Factory
• Physics potential at a neutrino factory: can we benefit from more than just detecting muons?
• On the energy and baseline optimization to study effects related to the $\delta$-phase (CP-/T-violation) in neutrino oscillations at a Neutrino Factory
• Higgs Search by Neural Networks at LHC
• Discriminating signal from background using neural networks. Application to top-quark search at the Fermilab Tevatron
• A novel concept for a anti nu_e Neutrino Factory

Cited by in corpus (3)

• Performance Of A Liquid Argon Time Projection Chamber Exposed To The WANF Neutrino Beam
• An incremental approach to unravel the neutrino mass hierarchy and CP violation with a long-baseline Superbeam for large ${\theta }_{13}$
• Future liquid Argon detectors