update: auto commit

This commit is contained in:
2026-04-10 02:55:48 -04:00
parent e1b8ea4132
commit 33cc90d409
+4
View File
@@ -904,6 +904,10 @@ $}
\begin{frame}{Appendix}{Why can't we fully automate the workflow using Mathematica?} \begin{frame}{Appendix}{Why can't we fully automate the workflow using Mathematica?}
There are coefficients before each constraint term we add, and it's very common that they have to meet some conditions to recover the hyperbolicity, for example, in GH they require that $\gamma_3 = \gamma_1 \gamma_2$, and in FOBSSN they require that $\kappa^\phi = 0$. And many coefficients cannot be parameters at all, they may have to be something like the lapse function $\lapse$. There are coefficients before each constraint term we add, and it's very common that they have to meet some conditions to recover the hyperbolicity, for example, in GH they require that $\gamma_3 = \gamma_1 \gamma_2$, and in FOBSSN they require that $\kappa^\phi = 0$. And many coefficients cannot be parameters at all, they may have to be something like the lapse function $\lapse$.
Then what about adding all possible terms with undetermined coefficients, and solve the coefficients by the conditions of hyperbolicity?
Yes, I thought about it. We need a function that takes the principal symbol matrix as input, and outputs the conditions on the coefficients for the principal symbol matrix to be diagonalizable with real eigenvalues. I do wrote such a function, but it cannot be simple. When apply to our case, it will run forever.
\end{frame} \end{frame}
\end{document} \end{document}