Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.
H.,Analysis of a complex of statistical variables into principal components.,Journal of Educational Psychology24(6)(1933) 417–441
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
nucl-th 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning
Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.