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The Hermitian positive-definite Gohberg–Semencul formula is exact and quadratic
Statement
Let be Hermitian positive definite, and let . Run General-RHS Hermitian Toeplitz solve by reflection recursion and Gohberg–Semencul in exact arithmetic. It returns . If and are the first and last inverse columns, then The recursion and four triangular Toeplitz products use complex arithmetic operations and storage beyond the input, output, and lag vector. This is an exact-arithmetic cost statement and makes no finite-precision stability claim.
Facts & Assumptions
Given: An integer , a Hermitian positive-definite Toeplitz matrix , its lag sequence, and an arbitrary .
, Hermitian symmetry is , and reverses coordinates. Toeplitz, circulant, and finite-index conventions for structured solvers
The conjugate-reversal recursion produces and for . Complex Hermitian Toeplitz bordering yields reflection coefficients and positive pivots
The algorithm forms , , and applies the displayed triangular Toeplitz expression to . General-RHS Hermitian Toeplitz solve by reflection recursion and Gohberg–Semencul
Hermitian positive-definite matrices are invertible. A matrix admits a Cholesky factorisation with positive diagonal exactly when it is Hermitian positive definite, and that factor is unique
Matrix products use the finite entrywise convention of Rectangular matrix multiplication and the identity matrix , including zero-sized shapes. Here the adjoint is the conjugate transpose, .
Proof
If , then with , is empty, , and . Also and , so the algorithm returns . Hence assume .
Put , , and . Then and by [F1]–[F2]. The reversal identity gives . Moreover, , because implies . Thus the Schur complement is . In , the top block equation gives ; substituting this in the last equation gives . Hence . Thus .
Entrywise, because . Also . Taking inverses in the reversal identity gives , so . Since is positive real, . The first-column block equation gives , and step 2.1 gives .
Set and . By step 3.1, is Hermitian and . Since the first row and column of and vanish, and ; these are the corresponding first row and column of . For , subtract from . The identity entries agree because exactly when . Reindexing the second finite sum gives The coefficient matrix is , while and .
The right side in step 4.1 is . Applying and using [F2] and the reversal identity gives . By step 3.1, and . Therefore, for every , . Together with the boundary entries in step 4.1, this proves
The shift is nilpotent, . Summing for telescopes to . The columns of are , and the columns of are , so substituting the identity of step 5.1 into the telescoping sum yields the stated Gohberg–Semencul formula. The algorithm’s output is therefore .
The reflection recursion costs operations and workspace by [F2]. Each triangular Toeplitz product in step 6.1 evaluates at most products and a comparable number of additions; the four products therefore cost . The two generator vectors and intermediate vectors require storage, and the algorithm never materializes an triangular factor.
Remarks
The proof identifies an exact inverse representation. It does not establish that finite-precision Levinson or Gohberg–Semencul evaluation is backward stable; pivot and cancellation growth require separate analysis.
Depends on
- General-RHS Hermitian Toeplitz solve by reflection recursion and Gohberg–Semencul
- Lower-shift displacement rank and generator pairs
- Rectangular matrix multiplication and the identity matrix $I_n$, including zero-sized shapes
- Toeplitz, circulant, and finite-index conventions for structured solvers
- Complex Hermitian Toeplitz bordering yields reflection coefficients and positive pivots
- A matrix admits a Cholesky factorisation with positive diagonal exactly when it is Hermitian positive definite, and that factor is unique
Used by
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Sources
- George Labahn and Tamir Shalom, Inversion of Toeplitz Matrices with Only Two Standard Equations, Theorem 1.1 (standard reference, not scraped)
- Daniel Kressner and Robert Luce, Fast computation of the matrix exponential for a Toeplitz matrix, §§2–3.1 (standard reference, not scraped)