The QSE-reduced network for silicon burning

Iron and neighboring nuclei are formed in massive stars before core collapse and during supernova outbursts. Complete and incomplete silicon burning is responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 70. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. Examination of the physics of silicon burning reveals that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present a hybrid equilibrium scheme, which takes advantage of this quasi-equilibrium (QSE) in order to reduce the number of independent variables calculated. This allows accurate prediction of the nuclear abundance evolution, deleptionization, and energy generation. During silicon burning the QSE-reduced network runs about an order of magnitude faster than the full network that it replaces and requires roughly a third as many variables without a significant loss of accuracy. These reductions in computational cost make the QSE-reduced network well suited for inclusion within hydrodynamic simulations, particularly in multi-dimensional applications.