Observational constraints on K-inflation models

TL;DR

This paper extends a computational tool to analyze K-inflation models with non-canonical kinetic terms, and uses observational data to place weak constraints on these models, finding some cases are favored.

Contribution

The authors develop a numerical code extension for K-inflation models and perform MCMC analysis to constrain these models using WMAP7 data.

Findings

Constraints on kinetic terms are very weak with current data.

Addition of quadratic kinetic terms is not ruled out for quadratic potentials.

For quartic potentials, such kinetic terms are actually favored.

Abstract

We extend the ModeCode software of Mortonson, Peiris and Easther to enable numerical computation of perturbations in K-inflation models, where the scalar field no longer has a canonical kinetic term. Focussing on models where the kinetic and potential terms can be separated into a sum, we compute slow-roll predictions for various models and use these to verify the numerical code. A Markov chain Monte Carlo analysis is then used to impose constraints from WMAP7 data on the addition of a term quadratic in the kinetic energy to the Lagrangian of simple chaotic inflation models. For a quadratic potential, the data do not discriminate against addition of such a term, while for a quartic (\lambda \phi^4) potential inclusion of such a term is actually favoured. Overall, constraints on such a term from present data are found to be extremely weak.