TITLE: Inverse of sparse matrix is not generally sparse
QUESTION [13 upvotes]: I have a question regarding inverse of square sparse matrices(or can be restricted to real symmetric positive definite matrices).
I encountered several times the web pages which states that the inverse of the sparse matrix is not usually sparse and my experience also said so. One exception can be diagonal matrices.
How theses kind of assertions can be verified?

REPLY [5 votes]: A good example is an arrow matrix, like
\begin{equation*}
A = \begin{bmatrix}
1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\
1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 \\
1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\
1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 \\
1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 \\
1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 \\
1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 \\
1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 \\
\end{bmatrix}.
\end{equation*}
You can check that $A^{-1}$ is dense.  The LU factors of $A$ are not very sparse either.
However, it is possible to find a "sparse LU" factorization for $A$:
\begin{equation*}
A = PLUQ^T,
\end{equation*}
where $P$ and $Q$ are permutation matrices and $L$ and $U$ are sparse.  You can observe this in Matlab using the lu function.