Skeletal Kinetics Reduction for Astrophysical Reaction Networks
A.G.Nouri, Y. Liu, P. Givi, H. Babaee, D. Livescu

TL;DR
This paper introduces a new method for creating simplified nuclear reaction models using sensitivity analysis and the f-OTD scheme, specifically applied to supernova Ia conditions, improving prediction accuracy of key isotopes.
Contribution
The paper develops a novel skeletal reduction methodology based on local sensitivities and the f-OTD scheme, tailored for astrophysical nuclear reaction networks, and demonstrates its effectiveness in supernova simulations.
Findings
A skeletal model with 150 isotopes accurately predicts $^{56}$Ni in SNe Ia.
The new models outperform previous intuitive models in energy and isotope predictions.
Decreasing electron fraction $ exttt{y}_e$ reduces $^{56}$Ni production, highlighting sensitivity to initial conditions.
Abstract
A novel methodology is developed to extract accurate skeletal reaction models for nuclear combustion. Local sensitivities of isotope mass fractions with respect to reaction rates are modeled based on the forced optimally time-dependent (f-OTD) scheme. These sensitivities are then analyzed temporally to generate skeletal models. The methodology is demonstrated by conducting skeletal reduction of constant density and temperature burning of carbon and oxygen relevant to SNe Ia. The 495-isotopes Torch model is chosen as the detailed reaction network. A map of maximum production of in SNe Ia is produced for different temperatures, densities, and proton to neutron ratios. The f-OTD simulations and the sensitivity analyses are then performed with initial conditions from this map. A series of skeletal models are derived and their performances are assessed by comparison against…
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Taxonomy
TopicsProtein Structure and Dynamics · Computational Drug Discovery Methods · Molecular spectroscopy and chirality
