How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Implicit Runge–Kutta stage equations and update
Definition
Let , , , and let be a vector field on an open time-state domain (First-order systems, initial value problems, and solutions on intervals). For an initial state and time with , and a step , a stage vector is admissible only when for every . An admissible vector solves
When a solution is selected, the method update is
On the admissible stage set, the stage update residual is the vector with blocks
The associated stage derivative residual is . The tableau is stiffly accurate when for all and ; in that case the last stage equals the method update. The equations may have no, one, or several solutions in a proposed branch set; this definition alone asserts no solvability.
Depends on
Used by
- Implicit stiff time stepping with a branch and residual ledger Algorithm
- Constant-step BDF2 is second-order convergent with a consistent start and selected roots Corollary
- Collocation tableau from distinct quadrature nodes Definition
- Scalar stability function, A-stability, and L-stability for Runge–Kutta methods Definition
- Selected two-stage singly diagonally implicit Runge–Kutta tableau Definition
- The ARS(2,2,2) additive tableau and its three stages Definition
- Two-stage Radau IIA tableau Definition
- A contractive implicit Runge-Kutta stage branch has a nonsingular residual Jacobian Lemma
- Small-step implicit Runge–Kutta stages have a unique branch and controlled residual error Lemma
- The selected two-stage SDIRK method has order two and is scalar L-stable Proposition
- Two-stage Radau IIA has order three and is scalar L-stable Proposition
- An implicit Runge-Kutta stage has the stated parameter sensitivity on its selected branch Theorem
- Backward Euler, the selected SDIRK, and two-stage Radau IIA converge at their stated orders under controlled stage residuals Theorem
Dependency tree · two levels
4 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Ernst Hairer and Gerhard Wanner, Introduction à l’Analyse Numérique, Chapter III: Équations Différentielles Ordinaires (standard reference, not scraped)
- John C. Butcher, Implicit Runge–Kutta Methods, tutorial accompanying Numerical Methods for Ordinary Differential Equations (standard reference, not scraped)