Prof. David Alonso

Abstract:

We investigate how dust foreground complexity can affect measurements of the tensor-to-scalar ratio, r, in the context of the Simons Observatory, using a cross-spectrum component separation analysis. Employing a suite of simulations with realistic Galactic dust emission, we find that spatial variation in the dust frequency spectrum, parametrized by βd , can bias the estimate for r when modeled using a low-order moment expansion to capture this spatial variation. While this approach performs well across a broad range of dust complexity, the bias increases with more extreme spatial variation in dust frequency spectrum, reaching as high as r ∼ 0.03 for simulations with no primordial tensors and a spatial dispersion of σ(βd ) ≃ 0.3 — the most extreme case considered, yet still consistent with current observational constraints. This bias is driven by changes in the ℓ-dependence of the dust power spectrum as a function of frequency that can mimic a primordial B-mode tensor signal. Although low-order moment expansions fail to capture the full effect when the spatial variations of βd become large and highly non-Gaussian, our results show that extended parametric methods can still recover unbiased estimates of r under a wide range of dust complexities. We further find that the bias in r, at the highest degrees of dust complexity, is largely insensitive to the spatial structure of the dust amplitude and is instead dominated by spatial correlations between βd and dust amplitude, particularly at higher orders. If βd does spatially vary at the highest levels investigated here, we would expect to use more flexible foreground models to achieve an unbiased constraint on r for the noise levels anticipated from the Simons Observatory.

Abstract:

Standard cosmological weak lensing analyses using cosmic shear are inevitably sensitive to small-scale, non-linear clustering from low-redshift structures. The need to adequately model the clustering of matter on this non-linear regime, accounting for both gravitational and baryonic effects, adds significant uncertainty to weak lensing studies, particularly in the context of near-future Stage-IV datasets. In this paper, inspired by previous work on so-called “nulling” techniques, we present a general method that selects the linear combinations of a given tomographic cosmic shear dataset that are least sensitive to small-scale non-linearities, by essentially suppressing the contribution from low-redshift structures. We apply this method to the latest public cosmic shear data from the Dark Energy Survey, DES-Y3, that corresponds to 3 years of observation, and show: a) that a large fraction of the signal is dominated by the single mode that is most affected by non-linear scales, and b) that removing this mode leads to a ∼ 1σ upwards shift in the preferred value of S 8 ≡ σ 8√(ΩM/0.3), alleviating the tension with current CMB data. However, the removal of the most contaminated mode also results in a significant increase in the statistical uncertainties. Taking this into account, we find this shift to be compatible with a random fluctuation caused by removing this most-contaminated mode at the ∼ 1.4σ level. We also show that this technique may be used by future Stage-IV surveys to mitigate the sensitivity of the final constraints to baryonic effects, trading precision for robustness.

Abstract:

The Simons Observatory (SO) Small Aperture Telescopes (SATs) will observe the Cosmic Microwave Background (CMB) temperature and polarization at six frequency bands. Within these bands, the angular response of the telescope (beam) is convolved with the instrument's spectral response (commonly called bandpass) and the signal from the sky, which leads to the band-averaged telescope beam response, which is sampled and digitized. The spectral properties of the band-averaged beam depend on the natural variation of the beam within the band, referred to as beam chromaticity. In this paper, we quantify the impact of the interplay of beam chromaticity and intrinsic frequency scaling from the various components that dominate the polarized sky emission on the tensor-to-scalar ratio, r, and foreground parameters. We do so by employing a parametric power-spectrum-based foreground component separation algorithm, namely BBPower, to which we provide beam-convolved time domain simulations performed with the beamconv software while assuming an idealized version of the SO SAT optics. We find a small, 0.02σ, bias on r, due to beam chromaticity, which seems to mostly impact the dust spatial parameters, causing a maximum 0.77σ bias on the dust B-mode spectra amplitude, Ad , when employing Gaussian foreground simulations. However, we find all parameter biases to be smaller than 1σ at all times, independently of the foreground model. This includes the case where we introduce additional uncertainty on the bandpass shape, which accounts for approximately half of the total allowed gain uncertainty, as estimated in previous work for the SO SATs.