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Finite Schur–Parlett recurrence with block merging and inconclusive statuses
Definition
Input a finite complex matrix , , a holomorphic function on a neighborhood of with the finite derivative data required by the diagonal block evaluators, Schur controls, a Sylvester separation threshold , an initial partition of into nonempty contiguous intervals, and a finite table of exact Jordan certificates indexed by contiguous diagonal block intervals. The partition and certificates are supplied inputs; a missing certificate for any current block returns missing-jordan-data.
- Call Finite-budget computed Francis Schur reduction with explicit statuses in its complex branch. Propagate any non-Schur status. Treat its returned as candidates.
- Verify by exact arithmetic that , , and is upper triangular. If any identity fails, return schur-certificate-failure. The computed Schur routine's residual diagnostic alone does not pass this test.
- Start from the supplied contiguous block partition of . At each start or restart, initialize every block of to zero. For each block call Finite analytic evaluation from a supplied exact Jordan decomposition with its exact Jordan certificate. On status exact, store its returned matrix as . If a certificate or required derivative is missing, return missing-jordan-data; propagate any other non-exact status without storing a diagonal value.
- Visit block pairs by increasing distance . Form
Call Finite-budget Bartels-Stewart solve for a Sylvester equation on
with threshold . If it returns
success, store its exact solution as . If it returnssingular-pivotorpivot-separation-failureand the partition has multiple blocks, merge the contiguous blocks from through , discard their old diagonal data, and restart step 3. Each merge reduces the block count, so there are at most merges. Any other non-success status is returned as inconclusive-sylvester with its underlying status. - Return the factored value with status parlett-success.
The procedure makes no floating-point stability or error-bound claim. Its success branch requires exact Schur and local solve certificates.
Depends on
- Analytic primary matrix functions by Jordan blocks
- Finite analytic evaluation from a supplied exact Jordan decomposition
- A verified Jordan evaluation returns the primary matrix function
- Real and complex Schur forms
- Finite-budget computed Francis Schur reduction with explicit statuses
- Sylvester operator and Frobenius separation number
- A Sylvester equation is uniquely solvable exactly when the spectra are disjoint
- Finite-budget Bartels-Stewart solve for a Sylvester equation
- Successful certified Bartels-Stewart substitution returns the exact Sylvester solution
Used by
Dependency tree · two levels
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Sources
- Jan Zur, Matrix Functions, TU Berlin full lecture notes (standard reference, not scraped)
- Philip I. Davies and Nicholas J. Higham, A Schur–Parlett Algorithm for Computing Matrix Functions (standard reference, not scraped)