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Finite ADI shifts have well-defined solves and explicit statuses
Statement
For admitted inputs of Low-rank ADI for a continuous Lyapunov equation, the shift-pair validation and update procedure terminate with a declared status after at most updates and a finite scan of the shifts. For every admissible shift with , its exact shifted solve exists uniquely. On completed, has at most columns and with the recorded residual factor . This is not a convergence or real-factor assertion; paired real-data shifts may be processed in complex arithmetic.
Facts & Assumptions
Given: A Hurwitz matrix, a finite forcing factor and a finite shift list with the algorithm's exact finite linear-solve operations.
Low-rank ADI for a continuous Lyapunov equation defines the pair-consuming validation scan, individual-shift updates and statuses.
A negative-real-part shift of a Hurwitz matrix is invertible: Hurwitz and imply is invertible.
Proof
In the pairing scan, each accepted real entry advances the index by one and each accepted nonreal pair advances it by two; an unpaired entry returns immediately. Thus the scan has at most checks, including the empty list. For a pair the second entry is consumed by the validation scan, not incorrectly tested for a third partner. The update loop still visits both indices.
Each valid update has . By [F2] its exact linear system has a unique solution. Other shift checks return their declared status. Each matrix operation and positive scalar square root is finite, and the update index increases until or an earlier return, so the procedure terminates.
Initialization has zero factor columns and . Each successful update appends columns and sets and by its explicit recurrence. Hence completion has at most columns and exactly the recorded output relations, also for . No contraction or limiting shift property was used.
Depends on
Used by
Nothing in the library uses this result yet.
Cited to discharge well-definedness by Low-rank ADI for a continuous Lyapunov equation.
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Sources
- Valeria Simoncini, Computational Methods for Linear Matrix Equations, SIAM Review 58(3), 2016 (standard reference, not scraped)
- Elias Jarlebring, Numerical Methods for Lyapunov Equations, lecture notes in numerical linear algebra, 2017 (standard reference, not scraped)