There are many methods for diagonalizing matrices; probably the most widely used is the combination of household transformations and the QR algorithm.
- Is there any superior method for diagonalizing large, non-sparse real symmetric matrices?
Superiority can be a bit muddy, so I define it as fast, numerically stable, does not require large amounts of extra memory, and lends itself to parallelization and vectorization.
- Crosspost: SciComp.SE