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Parameter based distances and masses using simple neural nets

Presentation #426.06 in the session Stellar Populations and Evolution II.

Published onJun 29, 2022
Parameter based distances and masses using simple neural nets

We derive distances and masses of stars from the APOGEE DR17 data release using simple neural networks. Training data for distances comes from GAIA EDR3, supplemented by literature distances for star clusters. For masses, the network is trained on asteroseismic masses for evolved stars and from isochrone masses for main sequence stars. The models are trained on effective temperature, surface gravity, metallicity and carbon and nitrogen abundances. We present an assessment of the accuracy and precision of the derived values. Using the masses, we derive ages for evolved stars based on the correspondence between mass and age based on isochrones.

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