Detectable Data-driven Features in the Primordial Scalar Power Spectrum

TL;DR

This paper investigates how future large-scale surveys like Euclid, SKA, and CMB-S4 can constrain deviations from the standard inflationary model by analyzing fluctuations in the primordial scalar power spectrum, using a model-independent parametrization.

Contribution

It introduces a method to parametrically analyze primordial power spectrum fluctuations and forecasts their detectability with upcoming surveys, comparing different observational probes.

Findings

Constraints are tightest for CMB anisotropies and galaxy clustering.

Similar patterns of fluctuations are forecasted for different surveys, with increasing wiggles for higher modes.

The proposed modes can reconstruct physically motivated primordial power spectrum patterns.

Abstract

In this work we explore the power of future large-scale surveys to constrain possible deviations from the standard single-field slow-roll inflationary scenario. Specifically, we parametrize possible fluctuations around the almost scale-invariant primordial scalar power spectrum in a model independent way. We then use their imprints on the simulated matter distribution, as observed by the galaxy clustering and weak lensing probes of Euclid and Square Kilometer Array, to construct the best constrainable patterns of fluctuations. For comparison, we make similar forecasts for a futuristic CMB-S4-like survey. The modes are found to have similar, yet shifted, patterns, with increasing number of wiggles as the mode number increases. The forecasted constraints are tightest for CMB anisotropies and galaxy clustering, depending on the details of the specifications of the survey. As case studies, we explore how two greatly different physically motivated patterns of primordial power spectrum are reconstructed by the proposed modes. We propose a figure of merit based on the amount of information delivered by the modes to truncate the mode hierarchy which is automatically generated by the analysis.