On coincidence problem in ELKO dark energy model

General Relativity and Gravitation (Impact Factor: 1.73). 09/2011; 44(9). DOI: 10.1007/s10714-012-1392-x
Source: arXiv

ABSTRACT We study the critical points of a universe dominated by Eigenspinoren des Ladungskonjugationsoperatorsin (ELKO) spinor field dark energy and a barotropic matter without considering a specific potential or interaction. The coincidence problem and attractor solutions are discussed at late time, and it is shown that the coincidence problem can not be solved in this model.


Available from: Hossein Mohseni Sadjadi, Aug 19, 2014
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    ABSTRACT: In this work it has been developed a new approach to study the stability of a system composed by an ELKO field interacting with dark matter, which could give some contribution in order to alleviate the cosmic coincidence problem. It is assumed that the potential that characterizes the ELKO field is not specified, but it is related to a constant parameter $\delta$. The strength of the interaction between the matter and the ELKO field is characterized by a constant parameter $\beta$ and it is also assumed that both the ELKO field as the matter energy density are related to their pressures by equations of state parameters $\omega_\phi$ and $\omega_m$, respectively. The system of equations is analysed by a dynamical system approach. It was found out the conditions of stability between the parameters $\delta$ and $\beta$ in order to have stable fixed points for the system for different values of the equation of state parameters $\omega_\phi$ and $\omega_m$, and the results are presented in form of tables. The possibility of decay of Elko field into dark matter or vice verse can be read directly from the tables, since the parameters $\delta$ and $\beta$ satisfy some inequalities. This opens the possibility to constrain the potential in order to have a stable system for different interactions terms between the Elko field and dark matter. The cosmic coincidence problem can be alleviated for some specific relations between the parameters of the model.