Study of accelerator neutrino interactions in a liquid argon TPC
arXiv:hep-ex/0703026
Abstract
We study the potentialities of a 50 liter liquid argon TPC prototype operated at the CERN WANF neutrino beam. We concentrate on the selection and reconstruction of quasi-elastic events and measure the cross section for this reaction.
Ph.D. Thesis. University of Granada, 2007. 171 pages, 85 figures
References in corpus (24)
- Resonant Leptogenesis
- Non-decoupling of Heavy Neutrinos and Lepton Flavour Violation
- Limits on Neutrino Mixing with new Heavy Particles
- Charged Lepton Flavour Violation from Massive Neutrinos in Z Decays
- Radiatively induced leptogenesis in a minimal seesaw model
- Z-induced FCNCs and their effects on Neutrino Oscillations
- Three-Neutrino Mixing after the First Results from K2K and KamLAND
- Low-scale leptogenesis and soft supersymmetry breaking
- Neutrino physics at large colliders
- The Drift Chambers Of The Nomad Experiment
- Performance Of A Liquid Argon Time Projection Chamber Exposed To The WANF Neutrino Beam
- l W nu production at CLIC: a window to TeV scale non-decoupled neutrinos
- The ICARUS Experiment, A Second-Generation Proton Decay Experiment and Neutrino Observatory at the Gran Sasso Laboratory
- Matter effects and CP violating neutrino oscillations with non-decoupling heavy neutrinos
- Particle Physics Implications of Neutrinoless Double Beta Decay
- A model for leptogenesis at the TeV scale
- Higgs Search by Neural Networks at LHC
- Heavy neutrinos production and decay in future colliders
- Testing the Majorana nature of neutralinos in supersymmetric theories
- Discriminating signal from background using neural networks. Application to top-quark search at the Fermilab Tevatron
- Neutral heavy lepton production at next high energy linear colliders
- Extra Dimensions, Isosinglet Charged Leptons and Neutrino Factories
- Experimental study of quasi-elastic neutrino interactions on Ar with a liquid Ar TPC exposed to the WANF neutrino beam
- Event Selection Using an Extended Fisher Discriminant Method