论文标题
相对论理想磁流失动力学中原始变量的强大恢复
Robust Recovery of Primitive Variables in Relativistic Ideal Magnetohydrodynamics
论文作者
论文摘要
一般相对论的理想磁水动力学的现代模拟代码都面临着长期存在的技术问题，这是由于需要从随着时间推移进化的变量中恢复基本变量的需要。在相对论的情况下，这需要一个非线性方程系统的数值解。尽管有几种方法可用，但没有证明完全可靠。最近比较不同方法的研究表明，所有方法都可能失败，尤其是对于强磁性和中等洛伦兹因子的重要情况。在这里，我们提出了一种新的鲁棒，高效和精确的解决方案方案，以及证明解决方案的存在和独特性，以及精确度的分析界限。此外，该方案使我们能够可靠地检测到导致非物理状态的进化误差，并自动为典型的无害病例应用校正。该方法的参考实现可公开作为软件库。该库的目的是提高二进制中子星合并模拟的可靠性，尤其是在研究射流形成和磁性驱动风中。
Modern simulation codes for general relativistic ideal magnetohydrodynamics are all facing a long standing technical problem given by the need to recover fundamental variables from those variables that are evolved in time. In the relativistic case, this requires the numerical solution of a system of nonlinear equations. Although several approaches are available, none has proven completely reliable. A recent study comparing different methods showed that all can fail, in particular for the important case of strong magnetization and moderate Lorentz factors. Here, we propose a new robust, efficient, and accurate solution scheme, along with a proof for the existence and uniqueness of a solution, and analytic bounds for the accuracy. Further, the scheme allows us to reliably detect evolution errors leading to unphysical states and automatically applies corrections for typical harmless cases. A reference implementation of the method is made publicly available as a software library. The aim of this library is to improve the reliability of binary neutron star merger simulations, in particular in the investigation of jet formation and magnetically driven winds.
