Robust forecasts on fundamental physics from the foreground-obscured, gravitationally-lensed CMB polarization

Recent results from the BICEP, Keck Array and Planck Collaborations demonstrate that Galactic foregrounds are an unavoidable obstacle in the search for evidence of inflationary gravitational waves in the cosmic microwave background (CMB) polarization. Beyond the foregrounds, the effect of lensing by intervening large-scale structure further obscures all but the strongest inflationary signals permitted by current data. With a plethora of ongoing and upcoming experiments aiming to measure these signatures, careful and self-consistent consideration of experiments' foreground- and lensing-removal capabilities is critical in obtaining credible forecasts of their performance. We investigate the capabilities of instruments such as Advanced ACTPo1, BICEP3 and Keck Array, CLASS, EBEX10K, PIPER, Simons Array, SPT-3G and SPIDER, and projects as COrE+, LiteBIRD-ext, PIXIE and Stage IV, to clean contamination due to polarized synchrotron and dust from raw multi-frequency data, and remove lensing from the resulting co-added CMB maps (either using iterative CMB-only techniques or through cross-correlation with external data). Incorporating these effects, we present forecasts for the constraining power of these experiments in terms of inflationary physics, the neutrino sector, and dark energy parameters. Made publicly available through an online interface, this tool enables the next generation of CMB experiments to foreground proof their designs, optimize their frequency coverage to maximize scientific output, and determine where cross-experimental collaboration would be most beneficial. We find that analyzing data from ground, balloon and space instruments in complementary combinations can significantly improve component separation performance, delensing, and cosmological constraints over individual datasets. In particular, we find that a combination of post-2020 ground- and space-based experiments could achieve constraints such as sigma (r) similar to 1.3 x 10(-4), sigma(n(t)) similar to 0.03, sigma(ns) similar to 1.8 x 10(-3), sigma(alpha(s)) similar to 1.7 x 10(-3), alpha(M-nu) similar to 31 meV, sigma(w) similar to 0.09, sigma(w(0)) similar to 0.25, sigma(w(a)) similar to 0.50, sigma(N-eff) similar to 0.024 and sigma(Omega(k)) similar to 1.5 x 10(-3), after component separation and iterative delensing.