Abstract
We present a database of 45,000 atmospheric models (which will become 80,000 models by the end of the project) with stellar masses between 9 and 120 \( {\text{M}}_{ \odot } \), covering the region of the OB main sequence and W-R stars in the H–R diagram. The models were calculated using the ABACUS I supercomputer and the stellar atmosphere code CMFGEN. The parameter space has 6 dimensions: the effective temperature Teff, the luminosity L, the metallicity Z, and three stellar wind parameters, namely the exponent β, the terminal velocity V∞, and the volume filling factor Fcl. For each model, we also calculate synthetic spectra in the UV (900–2000 Å), optical (3500–7000 Å), and near IR (10000–30000 Å) regions. To facilitate comparison with observations, the synthetic spectra were rotationally broaden using ROTIN3, by covering v sin i velocities between 10 and 350 km/s−1 with steps of 10 km/s−1, resulting in a library of 1 575 000 synthetic spectra. In order to demonstrate the benefits of employing the databases of pre-calculated models, we also present the results of the re-analysis of ε Ori by using our grid.
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Acknowledgments
The authors acknowledge the use of the ABACUS-I supercomputer at the Laboratory of Applied Mathematics and High-Performance Computing of the Mathematics Department of CINVESTAV-IPN, where this work was performed. J. Zsargo acknowledges CONACyT CB-2011-01 No. 168632 grant for support. The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the ENERXICO Project, grant agreement no 828947 and under the Mexican CONACYT-SENER-Hidrocarburos grant agreement B-S-69926. J.K. acknowledges financial support by the Consejo Nacional de Ciencia y Tecnología (CONACyT), Mexico, under grant 283151.
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Zsargó, J. et al. (2019). Creating and Using Large Grids of Pre-calculated Model Atmospheres for Rapid Analysis of Stellar Spectra. In: Torres, M., Klapp, J. (eds) Supercomputing. ISUM 2019. Communications in Computer and Information Science, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-38043-4_19
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DOI: https://doi.org/10.1007/978-3-030-38043-4_19
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