Hi,
imagine that you subtract asome number from your eigenvalues so that all
Eigenvalues are negative. Then you can use Eigenvalues[..,1] to get the
smallest. This can be achieved by subtracting n IdentityMatrix from your
matrix, where n is larger than you largest positive eigenvalue.
Therefore, the following gives you the samllest eigenvalue:
n+Eigenvalues[m- n IdentityMatrix[dimension],1]
hope this helps, Daniel
-Eigenvalues[-A, 1, Method -> {Arnoldi, MaxIterations -> 10^5,
Criteria -> RealPart}]
will compute the largest eigenvalue of -A (by real part), which is the
smallest eigenvalue of A. Unfortunately, the Mathematica documentation
on the subject of sparse-matrix diagonalization is very sparse.
Roman.