Which spectral distortions does $\Lambda$CDM actually predict?

TL;DR

This paper reviews the predicted spectral distortions of the CMB within the DM model, discusses measurement prospects with future experiments, and highlights the importance of improved modeling for accurate interpretation.

Contribution

It provides a comprehensive summary of guaranteed CMB distortions in DM, assesses uncertainties, and compares approximation methods, emphasizing the potential of next-generation spectrometers.

Findings

Next-generation spectrometers will detect distortions from reionization and structure formation.

Future measurements can constrain small-scale power spectrum and spectral index running.

Current designs need improved foreground and instrumental modeling for better accuracy.

Abstract

Ever refined cosmological measurements have established the $\Lambda$CDM concordance model, with the key cosmological parameters being determined to percent-level precision today. This allows us to make explicit predictions for the spectral distortions of the cosmic microwave background (CMB) created by various processes occurring in the early Universe. Here, we summarize all guaranteed CMB distortions and assess their total uncertainty within $\Lambda$CDM. We also compare simple methods for approximating them, highlighting some of the subtle aspects when it comes to interpreting future distortion measurements. Under simplified assumptions, we briefly study how well a PIXIE-like experiment may measure the main distortion parameters (i.e., $\mu$ and $y$). Next generation CMB spectrometers are expected to detect the distortion caused by reionization and structure formation at extremely high significance. They will also be able to constrain the small-scale power spectrum through the associated $\mu$-distortion, improving limits on running of the spectral index. Distortions from the recombination era, adiabatic cooling of matter relative to the CMB and dark matter annihilation require a higher sensitivity than PIXIE in its current design. The crucial next step is an improved modeling of foregrounds and instrumental aspects, as we briefly discuss here.