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Abstract:

We present Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) maps of the Cosmic Microwave Background temperature and polarization anisotropy at arcminute resolution over three frequency bands centered on 98, 150 and 220 GHz. The maps are based on data collected with the AdvancedACT camera over the period 2017–2022 and cover 19,000 square degrees with a median combined depth of 10 μK arcmin. We describe the instrument, mapmaking and map properties and illustrate them with a number of figures and tables. The ACT DR6 maps and derived products are available on LAMBDA at https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html. We also provide an interactive web atlas at https://phy-act1.princeton.edu/public/snaess/actpol/dr6/atlas and HiPS data sets in Aladin (e.g. https://alasky.cds.unistra.fr/ACT/DR4DR6/color_CMB).

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.