Minimally Parametric Power Spectrum Reconstruction from the Lyman-alpha Forest

TL;DR

This paper introduces a minimally parametric method to reconstruct the primordial power spectrum from Lyman alpha forest data, avoiding strong prior assumptions and assessing the current data's limitations.

Contribution

It develops a new minimally parametric framework calibrated with simulations, enabling shape reconstruction without assuming a specific power law form.

Findings

No evidence for deviation from scale-invariance in current data

Current Lyman alpha data lack statistical power to precisely determine the power spectrum shape

Future BOSS data will significantly improve shape constraints and break degeneracies

Abstract

Current results from the Lyman alpha forest assume that the primordial power spectrum of density perturbations follows a simple power law form, with running. We present the first analysis of Lyman alpha data to study the effect of relaxing this strong assumption on primordial and astrophysical constraints. We perform a large suite of numerical simulations, using them to calibrate a minimally parametric framework for describing the power spectrum. Combined with cross-validation, a statistical technique which prevents over-fitting of the data, this framework allows us to reconstruct the power spectrum shape without strong prior assumptions. We find no evidence for deviation from scale-invariance; our analysis also shows that current Lyman alpha data do not have sufficient statistical power to robustly probe the shape of the power spectrum at these scales. In contrast, the ongoing Baryon Oscillation Sky Survey (BOSS) will be able to do so with high precision. Furthermore, this near-future data will be able to break degeneracies between the power spectrum shape and astrophysical parameters.