Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Recent studies have reported tension between the presence of luminous, high-redshift galaxies and the halo mass functions predicted by standard cosmology. Here, an improved test is proposed using the presence of high-redshift Balmer breaks to probe the formation of early 104–105 M ⊙ baryonic minihalos. Unlike previous tests, this does not depend upon the mass-to-light ratio and has only a slight dependence upon the metallicity, stellar initial mass function, and star formation history, which are all weakly constrained at high redshift. We show that the strongest Balmer breaks allowed at z = 9 using the simplest ΛCDM cosmological model would allow a D 4000 as high as 1.26 under idealized circumstances and D 4000 ≤ 1.14 including realistic feedback models. Since current photometric template fitting to JWST sources infers the existence of stronger Balmer breaks out to z ≳ 11, upcoming spectroscopic follow-up will either demonstrate those templates are invalid at high redshift or imply new physics beyond “vanilla” ΛCDM.

Abstract:

Context. The upcoming Simons Observatory Small Aperture Telescopes aim at achieving a constraint on the primordial tensor-to-scalar ratio r at the level of σ (r = 0)≤0.003, observing the polarized CMB in the presence of partial sky coverage, cosmic variance, inhomogeneous non-white noise, and Galactic foregrounds. Aims. We present three different analysis pipelines able to constrain r given the latest available instrument performance, and compare their predictions on a set of sky simulations that allow us to explore a number of Galactic foreground models and elements of instrumental noise, relevant for the Simons Observatory. Methods. The three pipelines employ different combinations of parametric and non-parametric component separation at the map and power spectrum levels, and use B-mode purification to estimate the CMB B-mode power spectrum. We applied them to a common set of simulated realistic frequency maps, and compared and validated them with focus on their ability to extract robust constraints on the tensor-to-scalar ratio r. We evaluated their performance in terms of bias and statistical uncertainty on this parameter. Results. In most of the scenarios the three methodologies achieve similar performance. Nevertheless, several simulations with complex foreground signals lead to a > 2σ bias on r if analyzed with the default versions of these pipelines, highlighting the need for more sophisticated pipeline components that marginalize over foreground residuals. We show two such extensions, using power-spectrum-based and map-based methods, that are able to fully reduce the bias on r below the statistical uncertainties in all foreground models explored, at a moderate cost in terms of σ (r).