Disentangling Doppler modulation, aberration and the temperature dipole in the CMB

TL;DR

This paper develops a method to separately measure Doppler and aberration effects in the CMB, accounting for intrinsic dipole contributions and observational complexities, to improve understanding of the CMB dipole origin.

Contribution

It introduces a pipeline to independently estimate Doppler and aberration couplings in the CMB, addressing contamination from unit conversion and realistic observational effects.

Findings

Pipeline achieves unbiased estimators with ~20% larger uncertainties than theory

Forecasts achievable precision for Planck 2018 and future experiments

Provides a cross-check alternative pipeline for robustness

Abstract

An observer in relative motion to the Cosmic Microwave Background (CMB) rest frame is sensitive to both aberration and Doppler effects. Both effects introduce similar but non-identical off-diagonal couplings in the spherical harmonic coefficients. The CMB temperature dipole may have additional contributions from an intrinsic component, which in turn produces different aberration and Doppler couplings. Moreover, the standard conversion from intensity measurements into temperature also introduces spurious Doppler-like couplings. In order to learn about the intrinsic dipole it is therefore important to measure both aberration and Doppler couplings in an independent manner while also removing the spurious contributions from unit conversion, which are degenerate with the dipole. Here we present a pipeline to measure the Doppler and aberration signal independently from each other and from the dipole itself. We also consider realistic beaming, noise and mask effects. Our pipeline results in independent and unbiased estimators which have uncertainties only ~20% larger than the simple theoretical expectations. We discuss the achievable precision in each measurement for Planck 2018, and also forecast them for future ground-based experiments with the Simons Observatory and CMB-S4. An alternative pipeline is presented in order to cross-check results and improve robustness.