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Evaluating Integration Methods for Nuclear Reaction Network Simulations

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This study surveys various algorithms for solving stiff ordinary differential equations in nuclear reaction networks. Results indicate that no single integration algorithm or linear algebra package is universally optimal across all scenarios. For high-resolution simulations with few isotopes, the Kaps-Rentrop integration method, paired with the GIFT linear algebra package, is most efficient. Conversely, the Bader-Deuflhard integration method alongside the UMFPACK or MA28 linear algebra packages is ideal for under-resolved simulations with numerous isotopes. This flexibility allows users to select integration methods at run-time within FLASH.

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Evaluating Integration Methods for Nuclear Reaction Network Simulations

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  1. Nuclear Reaction Networks Package Storage Zeros RHS Method Comment Rank ------------ ----------- ------- ------ ---------- ------------- -------- LAPACK dense no yes LU + BLAS 2 LUDCMP dense no yes LU Recipes 3 LEQS dense yes no Gauss Legacy 3 GIFT dense yes no Gauss Writes F77 1 MA28 sparse yes yes LU Coke Classic 1 UMFPACK sparse yes yes LU New Coke 2 Y12M sparse yes yes LU Drop Tol 2 BiCG sparse yes yes Krylov Templates 3 We have survyed several methods for solving the stiff system of ordinary differential equations that constitute nuclear reaction networks. Our results suggest that there is no single choice of the integration algorithm or linear algebra package that is ideal for all nuclear reaction networks under all cirumstances. For highly resolved simulations with a small number of isotopes to evolve, a Kaps-Rentrop integration coupled with the GIFT linear algebra package is the most efficient. For under resolved simulations with a large number of isotopes to evolve, a Bader-Deuflhard integration coupled with the UMFPACK or MA28 linear algebra package is the most efficient. In FLASH one may choose at run-time, how the equations are to integrated, which algebra package to use, and analytic or tabular nuclear reaction rate evalutions. An Accelerated Strategic Computing Initiative (ASCI) Academic Strategic Alliances Program (ASAP) Center at The University of Chicago

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