Error Upper Bounds for a Computational Method for Nonlinear Boundary and Initial-Value Problems

This work develops a computational approach for boundary and initial-value problems by using operational matrices, in order to run an evolutive process in a Hilbert space. Besides, upper bounds for errors in the solutions and in their derivatives can be estimated providing accuracy measures.

Effects of a CPT-even and Lorentz-violating nonminimal coupling on electron-positron scattering

We propose a new CPT-even and Lorentz-violating nonminimal coupling between fermions and Abelian gauge fields involving the CPT-even tensor (K-F)(mu nu alpha beta) of the standard model extension. We thus investigate its effects on the cross section of the electron-positron scattering by analyzing the process e(+) + e(-) -> mu(+) + mu(-). Such a study was performed for the parity-odd and parity-even nonbirefringent components of the Lorentz-violating (K-F)(mu nu alpha beta) tensor. Finally, by using experimental data available in the literature, we have imposed upper bounds as tight as 10(-12) (eV)(-1) on the magnitude of the CPT-even and Lorentz-violating parameters while nonminimally coupled. DOI: 10.1103/PhysRevD.86.125033

Noncommutative magnetic moment, fundamental length, and lepton size

Upper bounds on fundamental length are discussed that follow from the fact that a magnetic moment is inherent in a charged particle in noncommutative (NC) electrodynamics. The strongest result thus obtained for the fundamental length is still larger than the estimate of electron or muon size achieved following the Brodsky-Drell and Dehlmet approach to lepton compositeness. This means that NC electrodynamics cannot alone explain the whole existing discrepancy between the theoretical and experimental values of the muon magnetic moment. On the contrary, as measurements and calculations are further improved, the fundamental length estimate based on electron data may go down to match its compositeness radius.

Mutual Information Rate and Bounds for It

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators.