Neutrinoless double beta decay constrained by the existence of large extra dimensions

We present the possible influence on the half-life of neutrinoless double beta decay coming from the existence of $n$ extra spatial dimensions. The half-life in question depends on the mass of the electron neutrino. We base our analysis on the Majorana neutrino mass mechanism in Arkani-Hamed--Dimopoulos--Dvali model.Comment: I decided to move the collection of my papers to arXiv for easier access. Proceedings of the Nuclear Physics Workshop in Kazimierz Dolny, Poland, 200

Fermion-boson loops with bilinear R-parity violation leading to Majorana neutrino mass and magnetic moments

We present analytic expressions corresponding to a set of one loop Feynman diagrams, built within R-parity violating (RpV) minimal supersymmetric standard model (MSSM). Diagrams involve both bilinear and trilinear RpV couplings and represent Majorana neutrino masses and magnetic moments.Comment: I've decided to move the collection of my papers to arXiv for easier access. Proceedings of the Nuclear Physics Workshop in Kazimierz Dolny, Poland, 200

Constraining Bilinear R-Parity Violation from Neutrino Masses

We confront the R-parity violating MSSM model with the neutrino oscillation data. Investigating the 1-loop particle-sparticle diagrams with additional bilinear insertions on the external neutrino lines we construct the relevant contributions to the neutrino mass matrix. A comparison of the so-obtained matrices with the experimental ones assuming normal or inverted hierarchy and taking into account possible CP violating phases, allows to set constraints on the values of the bilinear coupling constants. A similar calculation is presented with the input from the Heidelberg-Moscow neutrinoless double beta decay experiment. We base our analysis on the renormalization group evolution of the MSSM parameters which are unified at the GUT scale. Using the obtained bounds we calculate the contributions to the Majorana neutrino transition magnetic moments.Comment: I've decided to move the collection of my papers to arXiv for easier acces

Neutrino mass in GUT constrained supersymmetry with R-parity violation in light of neutrino oscillations

The neutrino masses are generated in grand unified theory (GUT) constrained supersymmetric model with R-parity violation. The neutrinos acquire masses via tree-level neutrino-neutralino mixing as well as via one-loop radiative corrections. The theoretical mass matrix is compared with the phenomenological one, which is reconstructed by using neutrino oscillation and neutrinoless double beta decay data. This procedure allows to obtain significantly stronger constraints on R-parity breaking parameters than those existing in the literature. The implication of normal and inverted neutrino mass hierarchy on the sneutrino expectation values, lepton-Higgs bilinear and trilinear R-parity breaking couplings is also discussed

Majorana neutrino magnetic moments

The presence of trilinear R-parity violating interactions in the MSSM lagrangian leads to existence of quark-squark and lepton-slepton loops which generate mass of the neutrino. By introducing interaction with an external photon the magnetic moment is obtained. We derive bounds on that quantity being around one order of magnitude stronger than those present in the literature.Comment: I've decided to move the collection of my papers to arXiv for easier access. Proceedings of the Nuclear Physics Workshop in Kazimierz Dolny, Poland, 200

Hebbian encoding in the biological visual system

We examined neural networks built of several hundred Hodgkin-Huxley neurons. The main aim of the research described below was to simulate memory processes occurring in hippocampus and biological visual system. In our model we chose the ancient Chinese I-Ching Oracle as a set of input patterns. Maps of Hebbian weights appearing on the output device of the model can be analysed by artificial neural networks playing a role of some kind of visual consciousness

Liquid state machine built of Hodgkin-Huxley neurons-pattern recognition and informational entropy

Neural networks built of Hodgkin-Huxley neurons are examined. Such structures behave like Liquid State Machines. They can effectively process geometrical patterns shown to artificial retina into precisely defined output. The analysis of output responses is performed in two ways: by means of Artificial Neural Network and by calculating informational entropy