Forecasts indicate 10-sigma detection for squeezed triangles and 100-sigma for combined shapes in the 21cm-galaxy cross-bispectrum with 100 hours of SKA-Mid interferometric observations on scales 0.2 to 0.9 per Mpc.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
astro-ph.CO 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
unclear 1representative citing papers
A review chapter groups machine learning methods for 21 cm cosmology by their pipeline roles in handling contaminated data, accelerating simulations, and inferring astrophysical parameters.
citing papers explorer
-
Probing the large-scale structure with 21cm-galaxy cross-bispectrum: Estimates from simulations and forecasts for upcoming cosmological surveys
Forecasts indicate 10-sigma detection for squeezed triangles and 100-sigma for combined shapes in the 21cm-galaxy cross-bispectrum with 100 hours of SKA-Mid interferometric observations on scales 0.2 to 0.9 per Mpc.
-
Application of Machine Learning to 21 cm Cosmology
A review chapter groups machine learning methods for 21 cm cosmology by their pipeline roles in handling contaminated data, accelerating simulations, and inferring astrophysical parameters.