Particle production during inflation: A Bayesian analysis with CMB data from Planck 2018

TL;DR

This paper investigates inflationary models with particle production bursts, comparing their predictions with Planck 2018 CMB data, and finds that models with multiple particle production events fit the data better than standard models.

Contribution

It introduces a Bayesian analysis of multi-burst particle production models during inflation using the latest CMB data, providing new constraints on model parameters.

Findings

Multi-bump models improve fit to CMB data over ΛCDM.

Coupling parameter g constrained to be less than 0.05.

Bayesian evidence favors multi-burst models over single-burst or standard models.

Abstract

A class of inflationary models that involve rapid bursts of particle productions predict observational signatures, such as bump-like features in the primordial scalar power spectrum. In this work, we analyze such models by comparing their predictions with the latest CMB data from Planck 2018. We consider two scenarios of particle production. The first one is a simple scenario consisting of a single burst of particle production during observable inflation. The second one consists of multiple bursts of particle production that lead to a series of bump-like features in the primordial power spectrum. We find that the second scenario of the multi-bump model gives better fit to the CMB data compared to the concordance $\Lambda$CDM model. We carried out model comparisons using Bayesian evidences. From the observational constraints on the amplitude of primordial features of the multi-bump model, we find that the coupling parameter $g$ responsible for particle production is bound to be $g< 0.05$.