The Future of Primordial Features with Large-Scale Structure Surveys

TL;DR

Future large-scale structure surveys have the potential to significantly enhance the detection and constraint of primordial features, especially oscillatory signals, offering new insights into the early universe beyond current CMB data.

Contribution

This study classifies primordial feature models, provides templates for their power spectra, and evaluates how upcoming LSS surveys can improve constraints compared to Planck.

Findings

LSS surveys can reduce feature amplitude errors by a factor of 5 or more.

They are particularly sensitive to oscillatory features due to 3D information.

LSS surveys will significantly improve primordial feature constraints in the next decade.

Abstract

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopic and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.