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Chebyshev stage perturbations have an explicit quadratic bound
Statement
Let , let be a self-adjoint endomorphism of with its Euclidean inner product and . For first-order RKC assume the integer stage count and ; for linear second-order RKC assume and , where . In either branch, let or , respectively.
Write for the generic recurrence stage; in the second-order branch this is the of Second-order linear stabilized Runge–Kutta–Chebyshev step. Model the error injected into each recurrence update by vectors : If for every , then the final stage error relative to the unperturbed recurrence is at most For linear second-order RKC the returned state multiplies this bound by . An additional output perturbation of norm adds at most . This is a bound for the stated additive-error model; it does not assert a floating-point error size.
Facts & Assumptions
Given: The RKC recurrences, the stage-error vectors and their uniform bound, a self-adjoint nonpositive , and the corresponding spectral interval condition.
First-order stabilized explicit Runge–Kutta–Chebyshev step: in the linear case the stage recurrence is , , and .
Second-order linear stabilized Runge–Kutta–Chebyshev step: the linear RKC2 recurrence uses and returns .
Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis: a self-adjoint endomorphism on finite-dimensional real inner-product space has an orthonormal eigenbasis.
Polynomial evaluation at an endomorphism: and Orthonormal families, complete orthonormal systems and Hilbert bases: a polynomial acts on an eigenvector by its scalar evaluation at the eigenvalue; orthonormal coordinates give the squared norm as the sum of squared coordinates.
Cauchy-Schwarz with its equality case, the triangle inequality for , the parallelogram law and polarisation: the Euclidean norm satisfies the triangle inequality.
Proof
Put , where is the unperturbed recurrence with the same . The first two updates give and , and subtraction of the recurrences gives for .
By [F5], choose an orthonormal eigenbasis of . Under either spectral interval premise, the eigenvalues of lie in . Thus [F4] and [F6] imply for every vector : expand in that eigenbasis and bound each squared coordinate.
Define by polynomial evaluation [F6]. Induction using [F3] and step 1.1 gives For this is . At a successor stage, the coefficient of the most recent old perturbation is ; for every earlier perturbation, multiplying by and subtracting its prior coefficient uses . The new perturbation has coefficient . This proves the formula by induction.
Apply the triangle inequality [F7] to step 2.1 and then step 1.2: For linear RKC2 the returned perturbation is ; since , its norm is at most the same bound. Adding a separate output perturbation uses the triangle inequality once more.
Remarks
The bound grows quadratically with the number of stages. It applies to self-adjoint operators whose scaled eigenvalues stay in the certified interval. It does not control nonnormal transient growth or replace a separate bound on each arithmetic or matrix-action perturbation.
Depends on
- First-order stabilized explicit Runge–Kutta–Chebyshev step
- Second-order linear stabilized Runge–Kutta–Chebyshev step
- Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis
- Chebyshev polynomials of the first and second kinds by their three-term recurrences
- The Euclidean inner product $\langle x,y\rangle = \sum_{k<n} x_k y_k$ on $\mathbb{R}^n$
- Linear map between vector spaces over the same field
- Orthonormal families, complete orthonormal systems and Hilbert bases
- Polynomial evaluation at an endomorphism: $p(T)=\sum_k a_kT^k$
- Real and complex inner-product spaces and their induced length
- Self-adjoint and normal endomorphisms of a finite-dimensional real or complex inner product space
- The space $\mathcal L(V,W)$ of linear maps with pointwise addition and scalar multiplication
- Chebyshev bounds and endpoint derivatives used by stabilized Runge–Kutta methods
- Cauchy-Schwarz $\lvert\langle x,y\rangle\rvert \le \lVert x\rVert_2\lVert y\rVert_2$ with its equality case, the triangle inequality for $\lVert\cdot\rVert_2$, the parallelogram law and polarisation
Used by
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Sources
- Ibrahim Almuslimani and Gilles Vilmart, Explicit Stabilized Integrators for Stiff Optimal Control Problems, §2.2.1 (standard reference, not scraped)
- B.P. Sommeijer, L.F. Shampine, and J.G. Verwer, RKC: An explicit solver for parabolic PDEs, §2 (standard reference, not scraped)