update: auto commit

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2026-04-10 03:09:14 -04:00
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@@ -916,7 +916,10 @@ $}
\mqty(1 & a \\ 0 & 1), \mqty(1 & a \\ 0 & 1),
\end{equation*} \end{equation*}
if we ask Mathematica to compute the eigenvectors, it will give us $\myvec{v}_1 = \mqty(1 \\ 0)$ and $\myvec{v}_2 = \mqty(0 \\ 0)$, because unless $a=0$, this matrix have a Jordan block. So the geometric multiplicity is less than the algebraic multiplicity except on a zero-measure set, that's why Mathematica thinks there is no second linearly independent eigenvector. If we simply check if the eigenvectors are linearly independent, we will miss the condition $a=0$ and get false. if we ask Mathematica to compute the eigenvectors, it will give us $\myvec{v}_1 = \mqty(1 \\ 0)$ and $\myvec{v}_2 = \mqty(0 \\ 0)$, because unless $a=0$, this matrix have a Jordan block. So the geometric multiplicity is less than the algebraic multiplicity except on a zero-measure set, that's why Mathematica thinks there is no second linearly independent eigenvector. If we simply check if the eigenvectors are linearly independent, we will miss the condition $a=0$ and get false.
\end{frame}
\begin{frame}{Appendix}{Why can't we fully automate the workflow using Mathematica?}
The correct way is to check the geometric multiplicity for each eigenvalues. Say we get eigenvalues $\lambda_1, ..., \lambda_k$ with the algebraic multiplicity $m_1, ..., m_k$. Under the assumption that all these eigenvalues are different from each other, we check $\dim\ker(A - \lambda_i I)$ for each $i$.
\end{frame} \end{frame}
\end{document} \end{document}