SOURCE-LINKED INTELLIGENCE

MAchine Learning Techniques and Advanced statistics FOR COSMOlogy

CORDIS · observation · Publication date unknown

MAchine Learning Techniques and Advanced statistics FOR COSMOlogy Some of the most pressing open problems in modern cosmology concern the nature of the cosmic dark sector, the mismatch between the theoretically predicted and observed values of the cosmological constant, and the growing number of cosmological tensions between independent observational probes. Most notably, the Hubble constant shows a significant and persistent statistical discrepancy between local determinations and those inferred from early-universe Cosmic Microwave Background data. These inconsistencies strongly suggest the need for new physics beyond the standard cosmological model. At the same time, current and forthcoming surveys are generating unprecedented volumes of data, whose accumulation and analysis demand substantial advances in statistical methodology before they can be effectively applied to targeted scient

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

205314.24

unit

EUR