arXiv subjects

Ion Stancu

Publications and source records attributed to Ion Stancu.

4 recordsLinked to original sources

arXiv2006

Cascade Training Technique for Particle Identification

The cascade training technique which was developed during our work on the MiniBooNE particle identification has been found to be a very efficient way to improve the selection performance, especially when very low background contamination levels are desired. The detailed description of this technique is presented here based on the MiniBooNE detector Monte Carlo simulations, using both artifical neural networks and boosted decision trees as examples.

physics.data-an↗

arXiv2004

Boosted Decision Trees as an Alternative to Artificial Neural Networks for Particle Identification

The efficacy of particle identification is compared using artificial neutral networks and boosted decision trees. The comparison is performed in the context of the MiniBooNE, an experiment at Fermilab searching for neutrino oscillations. Based on studies of Monte Carlo samples of simulated data, particle identification with boosting algorithms has better performance than that with artificial neural networks for the MiniBooNE experiment. Although the tests in this paper were for one experiment, it is expected that boosting algorithms will find wide application in physics.

physics.data-an↗

arXiv1999

Hierarchical Four-Neutrino Oscillations With a Decay Option

We present a new and novel synthesis of all existing neutrino data regarding the disappearance and appearance of $ν_e$ and $ν_μ$. We assume four neutrinos: $ν_e, ν_μ, ν_τ$, as well as a heavier singlet neutrino $ν_s$ of a few eV. The latter may decay into a massless Goldstone boson (the singlet Majoron) and a linear combination of the doublet antineutrinos. We comment on how this scenario may be verified or falsified in future experiments.

hep-ph↗

arXiv1999

Can the Super-Kamiokande Atmospheric Data Predict the Solar Neutrino Deficit ?

In this Letter we show that the evidence for neutrino oscillations from the Super-Kamiokande atmospheric neutrino data fully determines the 3x3 neutrino-oscillations mixing matrix and predicts an energy independent solar neutrino deficit at the level of 45%. This corresponds to a ratio of measured to predicted neutrino flux of R_e^{Solar} = 0.55, in good agreement with the experimental results. We achieve this result within the framework of a minimal, three-generations neutrino mixing, with mass squared differences of dM^2 = 0.45 eV^2 and dm^2 = O(10^-3) eV^2. The mixing matrix derived here is characterized by the mixing angles theta = 35.1, beta = 5.5, and psi = 23.3, and a vanishing CP-violating phase, delta = 0.

hep-ph↗