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Enhancing Cosmological Constraints from Foreground-Cleaned CMB Maps Using Large-Scale Structure Surveys

Published 28 Aug 2026 in astro-ph.CO | (2608.28487v1)

Abstract: Extragalactic foregrounds contaminate cosmic microwave background (CMB) temperature maps at small angular scales and limit their utility for precision cosmology. The internal linear combination (ILC) is a well-known technique for suppressing these contaminants, but residual foreground power remains a limiting factor. Kusiak et al. (2023) proposed adding galaxy number-density maps as additional ILC channels, exploiting their correlation with the large-scale structure sourcing these foregrounds to suppress contamination. Here we apply this framework to forecast the gains in CMB-based cosmological parameter constraints from near- and next-generation experiments. Using a halo-model foreground pipeline and a Fisher forecast from joint TT+TE+EE power spectra, we quantify the improvement from galaxy-tracer-assisted ILC cleaning across three configurations: enhanced Simons Observatory (SO) with unWISE or Rubin-like galaxy catalogs, and a futuristic CMB-HD configuration with a hypothetical deep galaxy survey. We find that adding galaxy tracers reduces the residual foreground power in the cleaned temperature map by 4%\sim4\%, 22%\sim22\%, and 32%\sim32\% at 10,000\ell\sim10,000 for the unWISE, Rubin-like, and futuristic samples, respectively. For the overall variance of the cleaned map at 10,000\ell\sim10,000, it provides 8%8\%, 24%24\%, and 17%17\% improvements for each combination. The resulting reduction in marginalized parameter error bars is modest for the base six-parameter ΛΛCDM model: sub-percent for SO+unWISE, rising to 2%\sim2\% for SO+Rubin-like tracer. Including the effective number of relativistic species NeffN_{\rm eff}, we find at most 2.2%2.2\% improvements for both SO+Rubin-like and CMB-HD+Futuristic tracer. These results establish the expected gains from combining near-term CMB experiments with current and forthcoming large-scale-structure surveys.

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