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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2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
The HAges catalog compiles published asteroseismic and gyrochronological ages for 659 HWO target stars, finding that only ~5% have asteroseismic ages and ~20% have gyrochronal ages.
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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The HAges Catalog: Stellar Ages for High Priority HWO Target Stars
The HAges catalog compiles published asteroseismic and gyrochronological ages for 659 HWO target stars, finding that only ~5% have asteroseismic ages and ~20% have gyrochronal ages.