6,111 research outputs found
Spectral averaging techniques for Jacobi matrices
Spectral averaging techniques for one-dimensional discrete Schroedinger
operators are revisited and extended. In particular, simultaneous averaging
over several parameters is discussed. Special focus is put on proving lower
bounds on the density of the averaged spectral measures. These Wegner type
estimates are used to analyze stability properties for the spectral types of
Jacobi matrices under local perturbations
Transient situations in traffic flow: Modelling the Mexico City Cuernavaca Highway
In this paper a recent variable anticipation cellular automata model for
single-lane traffic flow is extended to analyze the situation of free and
congested flow in the Highway from Mexico City to Cuernavaca. This highway
presents free flow in standard days; but in the returning day of long weekends
or holidays it exhibits congested flow and in rush hours jamming appears. We
illustrate how our CA model for traffic flow can deal appropriately with
transient situations and can be used to search new alternatives that allow to
improve the traffic flow in Mexican highways.Comment: Paper accepted to be published in the Proceedings of Second Mexican
Meeting on Mathematical and Experimental Physics (September 2004), El Colegio
Nacional, Mexico City, Mexic
Estimating a pressure dependent thermal conductivity coefficient with applications in food technology
In this paper we introduce a method to estimate a pressure dependent thermal
conductivity coefficient arising in a heat diffusion model with applications in
food technology. To address the known smoothing effect of the direct problem,
we model the uncertainty of the conductivity coefficient as a hierarchical
Gaussian Markov random field (GMRF) restricted to uniqueness conditions for the
solution of the inverse problem established in Fraguela et al. Furthermore, we
propose a Single Variable Exchange Metropolis-Hastings algorithm to sample the
corresponding conditional probability distribution of the conductivity
coefficient given observations of the temperature. Sensitivity analysis of the
direct problem suggests that large integration times are necessary to identify
the thermal conductivity coefficient. Numerical evidence indicates that a
signal to noise ratio of roughly 1000 suffices to reliably retrieve the thermal
conductivity coefficient
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