English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We explore data analysis techniques for signatures from heavy particleproduction during inflation. Heavy particules can be produced by time dependentmasses and couplings, which are ubiquitous in string theory. These localizedexcitations induce curvature perturbations with non-zero correlation functionsat all orders. In particular, Flauger et. al. 2016 has shown that thesignal-to-noise as a function of the order $N$ of the correlation function canpeak for $N$ of order $\mathcal{O}(1)$ to $\mathcal{O}(100)$ for an interestingspace of models. As previous non-Gaussianity analyses have focused on$N=\{3,4\}$, in principle this provides an unexplored data analysis window withnew discovery potential. We derive estimators for arbitrary $N$-point functionsin this model and discuss their properties and covariances. To lowest order,the heavy particle production phenomenology reduces to a classical Poissonprocess, which can be implemented as a search for spherically symmetricprofiles in the curvature perturbations. We explicitly show how to recover thisresult from the $N$-point functions and their estimators. Our focus in thispaper is on method development, but we provide an initial data analysis usingWMAP data, which illustrates the particularities of higher $N$-point functionsearches.

Higher N-point function data analysis techniques for heavy particle production and WMAP results