Broad Grid of 2-component kilonova models
Creators
- 1. LANL
- 2. LANL, U. of A., UNM, GWU
- 3. LANL, Northwestern U.
- 4. RIT, LANL
- 5. LANL, JINA
- 6. RIT
Description
Abstract for data in kn_sim_cube_v1.tar.gz:
This dataset is a grid of multi-angle, multi-wavelength spectra from 900 2D axisymmetric, 2-component kilonova models. The masses and velocities of each component are 0.001, 0.003, 0.01, 0.03, or 0.1 M⊙ and 0.05, 0.15, or 0.3 c, respectively. The models in this dataset have been described by Wollaeger et al (2021), "A Broad Grid of 2D Kilonova Emission Models" (NASA ADS link here). This dataset is also posted on the LANL CTA website. The upload is a tarball with 3 files per model: spectra (_spec_), luminosity (_lums_), and broadband magnitudes (_mags_). The model name has model properties, for example: Run_TS_dyn_all_lanth_wind1_all_md0.03_vd0.3_mw0.003_vw0.05_lums_2020-04-25.dat is a luminosity file produced on 4/25/2020 with toroidal (T) low-Ye ejecta, spherical (S) high-Ye ejecta, "Wind 1" high-Ye composition (wind1), 0.03 M⊙ and 0.3c low-Ye ejecta mass and velocity, and 0.003 M⊙ and 0.05c high-Ye ejecta mass and velocity. The data format is described in data_format.pdf.
Abstract for data in active_learning_sims.tar.gz:
This dataset is also of multi-angle, multi-wavelength spectra from 2D axisymmetric, 2-component kilonova models, but is generated by automated placement (active learning) in mass-velocity of each component, rather than being restricted to the above grid values. The models and AL placement methods have been described by Ristic et al (2021), "Interpolating Detailed Simulations of Kilonovae: Adaptive Learning and Parameter Inference Applications" (NASA ADS link here). This dataset is also posted on the LANL CTA website. The data contained in active_learning_sims.tar.gz is formatted the same way as in kn_sim_cube_v1.tar.gz, following the description in data_format.pdf.
Notes
Files
data_format.pdf
Files
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Additional details
References
- Wollaeger et al. (2021). A Broad Grid of 2D Kilonova Emission Models. arXiv:2105.11543
- Ristic et al. (2021). Interpolating Detailed Simulations of Kilonovae: Adaptive Learning and Parameter Inference Applications. arXiv:2105.07013