Deep learning infers Δν and ν_max from one-month TESS and K2 observations of red giants with reliable results for ~50% of Kepler/K2 samples and ~23% of TESS stars, plus ΔΠ1 for ~200 K2 young red giants that match known patterns.
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Asteroseismic fits to g-dominated mixed modes in four red giants suggest convective overshooting rises with mass and yield a core rotation rate of 0.7409 μHz for KIC 11968334.
citing papers explorer
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Inferring Asteroseismic Parameters from Short Observations Using Deep Learning: Application to TESS and K2 Red Giants
Deep learning infers Δν and ν_max from one-month TESS and K2 observations of red giants with reliable results for ~50% of Kepler/K2 samples and ~23% of TESS stars, plus ΔΠ1 for ~200 K2 young red giants that match known patterns.
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Probing Red Giant Interiors with G-Dominated Mixed Modes I: The Cases of KIC 9145955, KIC 9970396, KIC 9882316 and KIC 11968334
Asteroseismic fits to g-dominated mixed modes in four red giants suggest convective overshooting rises with mass and yield a core rotation rate of 0.7409 μHz for KIC 11968334.