VizieR Online Data Catalog: DNN internal structure code (Alibert+, 2019)
Abstract
We trained Deep Neural Networks to compute the critical core mass and envelope masses of forming planets, for a variety of conditions (formation location, temperature and pressure in the disc, core mass, solid accretion rate). The resulting DNNs, which can be easily implemented with the tools we provide on github (https://github.com/yalibert/DNN internalstructure/), give very similar results to the ones obtained by solving the internal structure equations, using a much reduced computer time.
(1 data file).- Publication:
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VizieR Online Data Catalog
- Pub Date:
- March 2019
- Bibcode:
- 2019yCat..36260021A
- Keywords:
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- Models