A neural network trained on simulations infers stripping times for Sagittarius stream stars from phase-space data, measuring a 0.3 dex/Gyr metallicity gradient and estimating ages for globular clusters such as Pal 12 and NGC 2419.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
astro-ph.GA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
In low-extinction galactic open clusters fast and slow rotators populate distinct parts of the extended main-sequence turnoff while differential extinction inflates the turnoff width and biases age estimates in others.
citing papers explorer
-
Reconstructing the Stripping History of the Sagittarius Stream with Neural Networks
A neural network trained on simulations infers stripping times for Sagittarius stream stars from phase-space data, measuring a 0.3 dex/Gyr metallicity gradient and estimating ages for globular clusters such as Pal 12 and NGC 2419.
-
Investigating Extended Main-Sequence Turnoffs in Galactic Open Clusters
In low-extinction galactic open clusters fast and slow rotators populate distinct parts of the extended main-sequence turnoff while differential extinction inflates the turnoff width and biases age estimates in others.