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Juan I. Montijano

Publications and source records attributed to Juan I. Montijano.

4 recordsLinked to original sources

On the order of Runge Kutta methods reusing last stage

In this paper we consider explicit Runge--Kutta (RK) methods for the numerical solution of Initial Value Problems (IVPs) in differential equations in which the last function evaluation in a step is reused, substituting the first evaluation for the next step. This requirement implies that, except for the first step, the computational cost of an $s$--stage explicit RK method reduces from $s$ to $(s-1)$ function evaluations per step. It will be seen that, in general, if a RK method has order $p$, when introducing this reused stage the new method has in general order $<p$. In this context we study the conditions on the coefficients of an explicit RK method with order $p$ such that the global error of the method reusing the last stage has the same order $p$ of accuracy. A detailed study on the conditions that the coefficients of an $s$ stage method with order $p$ must satisfy for the method reusing the last stage has also order $p$. In particular, for the families of $s$--stage explicit RK methods with the highest order $p=s$ we identify those methods reusing the last stage which retain the order of of the original method. The results of some numerical experiments are presented to confirm the theoretical results.

math.NA↗

Model for prognostic of symptomatic, asymptomatic and hospitalized COVID-19 cases with correct demography evolution

The aim of this study is to propose a modified Susceptible-Exposed-Infectious-Removed (SEIR) model that describes the behaviour of symptomatic, asymptomatic and hospitalized patients of COVID-19 epidemic, including the effect of demographic variation of population. It is shown that considering a population growth proportional to the total population leads to solutions with a qualitative behaviour different from the behaviour obtained in many studies, where constant growth ratio is assumed. An exhaustive theoretical study is carried out and the basic reproduction number $R_0$ is computed from the model equations. It is proved that if $R_0<1$ then the disease-free manifold is globally asymptotically stable, that is, the epidemics remits. Global and local stability of the equilibrium points is also studied. Numerical simulations are used to show the agreement between numerical results and theoretical properties. The model is fitted to experimental data corresponding to the pandemic evolution in the República de Cuba, showing a proper behaviour of infected cases which let us think that can provide a correct estimation of asymptomatic cases. In conclusion, the model seems to be an adequate tool for the study and control of infectious diseases in particular the COVID-19 disease transmission.

q-bio.PE↗

Spectrally accurate space-time solution of Hamiltonian PDEs

Recently, the numerical solution of multi-frequency, highly-oscillatory Hamiltonian problems has been attacked by using Hamiltonian Boundary Value Methods (HBVMs) as spectral methods in time. When the problem derives from the space semi- discretization of (possibly Hamiltonian) partial differential equations (PDEs), the resulting problem may be stiffly-oscillatory, rather than highly-oscillatory. In such a case, a different implementation of the methods is needed, in order to gain the maximum efficiency.

math.NA↗

Chebyshev Polynomials in Distributed Consensus Applications

In this paper we analyze the use of Chebyshev polynomials in distributed consensus applications. We study the properties of these polynomials to propose a distributed algorithm that reaches the consensus in a fast way. The algorithm is expressed in the form of a linear iteration and, at each step, the agents only require to transmit their current state to their neighbors. The difference with respect to previous approaches is that the update rule used by the network is based on the second order difference equation that describes the Chebyshev polynomials of first kind. As a consequence, we show that our algorithm achieves the consensus using far less iterations than other approaches. We characterize the main properties of the algorithm for both, fixed and switching communication topologies. The main contribution of the paper is the study of the properties of the Chebyshev polynomials in distributed consensus applications, proposing an algorithm that increases the convergence rate with respect to existing approaches. Theoretical results, as well as experiments with synthetic data, show the benefits using our algorithm.

eess.SY↗