Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
Constraints on the missing baryons from the kinetic Sunyaev-Zeldovich effect in Planck data
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We estimate the amount of the {\it missing baryons} detected by the \Planck\ measurements of the cosmic microwave background in the direction of Central Galaxies (CGs) identified in the Sloan galaxy survey. The peculiar motion of the gas inside and around the CGs unveils values of the Thomson optical depth $\tau_{\rm T}$ in the range $0.2$--$2\times 10^{-4}$, indicating that the regions probed around CGs contain roughly half of the total amount of baryons in the Universe at the epoch where the CGs are found. If baryons follow dark matter, the measured $\tau_{\rm T}$s are compatible with the detection all the baryons existing inside and around the CGs.
citation-role summary
citation-polarity summary
fields
astro-ph.CO 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.