Constraints on the canonical single-field slow-roll inflation model from observations

TL;DR

This paper constrains the canonical single-field slow-roll inflation model using recent observational data, favoring models with concave potentials and providing tight bounds on tensor spectral indices.

Contribution

It introduces two methods to constrain slow-roll parameters directly from data and applies them to evaluate inflation models against observations.

Findings

Monomial potential inflation models are disfavored.

Concave potential models like Starobinsky inflation are preferred.

Tensor spectral index is constrained to be very small, |n_t| ≲ 4.7×10^{-3}.

Abstract

In this paper we use two methods to constrain the the canonical single-field slow-roll inflation model. The first method exploits the analytic slow-roll-parameter dependence of primordial perturbations, and the second consists of a phenomenological parameterization of the primordial spectra of both scalar and tensor perturbations. We constrain the slow-roll parameters directly by adopting the latest datasets, including Planck satellite data, BICEP2/Keck data and Baryon Acoustic Oscillation data. An advantage of this method is that we can work out the predictions of single-field slow-roll inflation model by using these constrained slow-roll parameters. We illustrate the predictions of the parameters characterizing the scalar power spectrum and constrain some inflation models. We find that the inflation model with monomial potential is disfavored, and the inflation models with a concave potential, such as the Starobinsky inflation model, brane inflation model are preferred. From the constraints on the slow-roll parameters, the derived tensor spectral index in the single-field slow-roll inflation model is quite small, namely $|n_t|\lesssim 4.7\times 10^{-3}$ which will be very difficult to be measured by CMB data only in the future, and the absolute value of derived running of tensor spectral index is not larger than $1.56\times 10^{-4}$ at $95\%$ confidence level.