Finding inverse metric tensor when there are off-diagonal terms

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To find the inverse of a metric tensor with off-diagonal terms, particularly in the Kerr metric, one can simplify the problem by recognizing that the only off-diagonal elements involve the time and azimuthal coordinates. The contravariant components for the diagonal elements can be directly calculated as the reciprocals of the corresponding covariant components. The key to simplifying the inversion of the 4x4 matrix lies in the blockwise inversion theorem, which allows the separation of the matrix into smaller sub-matrices that can be inverted independently. By rearranging the coordinates, the matrix can be expressed in a form that highlights this structure, facilitating the inversion process. Understanding this theorem significantly reduces the complexity of finding the inverse of the metric tensor.
Nabigh R
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How do you find the inverse of metric tensor when there are off-diagonals?
More specifivally, given the (Kerr) metric,
$$ d \tau^2 = g_{tt} dt^2 + 2g_{t \phi} dt d\phi +g_{rr} dr^2 + g_{\theta \theta} d \theta^2 + g_{\phi \phi} d \phi^2 + $$
we have the metric tensor;
$$ g_{\mu \nu} = \begin{pmatrix}
g_{tt} & 0 & 0 & g_{t \phi} \\
0 & g_{rr} & 0 & 0 \\
0 & 0 & g_{\theta \theta} & 0 \\
g_{\phi t} & 0 & 0 & g_{\phi \phi} \\
\end{pmatrix} $$
In "A First Course in General Relativity", Schutz say that since the only off-diagonal element involves ##t## and ##\phi##, the contravariant components ##g^{rr}## and ##g^{\theta \theta}## are given by ##g^{rr} = \frac{1}{g_{rr}}## and ##g^{\theta \theta} = \frac{1}{g_{\theta \theta}}##. And then invert the matrix
\begin{pmatrix}
g_{tt} & g_{t \phi} \\
g_{\phi t} & g_{\phi \phi} \\
\end{pmatrix}
to find ##g^{tt}##, ##g^{\phi t}## and ## g^{\phi \phi} ##. I don't get why we can do that. Is it some kind on generalised version for the inverse of a diagonal matrix.
If ## A = \begin{pmatrix}
a_{11} & 0 & 0 & 0 \\
0 & a_{22} & 0 & 0 \\
0 & 0 & a_{33} & 0 \\
0 & 0 & 0 & a_{44} \\
\end{pmatrix} ##
then ## A^{-1} = \begin{pmatrix}
\frac{1}{a_{11}} & 0 & 0 & 0 \\
0 & \frac{1}{a_{22}} & 0 & 0 \\
0 & 0 & \frac{1}{a_{33}} & 0 \\
0 & 0 & 0 & \frac{1}{a_{44}} \\
\end{pmatrix} ##
 
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Thanks Mentz :-D I know I can get ##g^{\mu \nu}## by inverting the matrix representation of ##g_{\mu \nu}##. But what I want to know is reasoning Schutz used to simplify the problem of finding the inverse of a ##4 \times 4## matrix to that of finding the inverse of a ##2 \times 2## matrix :-)
If there is a general theorem or something that allows it, then it sure can save me a lot of work.
 
It's perhaps easier to see by writing the coordinates in a different order:
$$ g_{\mu \nu} = \begin{pmatrix}
g_{tt} & g_{t \phi} & 0 & 0 \\
g_{\phi t} & g_{\phi \phi} & 0 & 0 \\
0 & 0 & g_{\theta \theta} & 0 \\
0 & 0 & 0 & g_{rr} \\
\end{pmatrix} $$
and the observation that if you can decompose a matrix into smaller sub-matrices
$$ \textbf{A} = \left( \begin{array}{c|c}
\textbf{P} & \textbf{0} \\
\hline
\textbf{0} & \textbf{Q}
\end{array} \right) $$
then it inverts as
$$ \textbf{A}^{-1} = \left( \begin{array}{c|c}
\textbf{P}^{-1} & \textbf{0} \\
\hline
\textbf{0} & \textbf{Q}^{-1}
\end{array} \right) $$
(then finally put the coordinates back into the original order).
 
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Thanks a lot Greg. That's just what I was looking for. Just saw blockwise inversion theorem of matrices on Wikipedia. Since it didn't occur me to change the order of coordinates, I didn't make the connection. Thanks again :approve:
 
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