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Backward Euler step equation and algebraic residual
Definition
Let define a first-order initial-value problem on an open time-state domain . Given a time , step , and state with , an admissible endpoint must satisfy . The backward Euler endpoint is any such satisfying
Its update residual at an approximate endpoint with is
When is defined at the endpoint, the derivative residual is . The equation can have no, one, or several roots on a restricted admissible branch set; this definition by itself asserts neither existence nor uniqueness.
Depends on
Used by
- Finite-budget coupled backward Euler for an index-one DAE Algorithm
- 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
- Fine and coarse propagators on a common macro grid Definition
- A capacitor-resistor circuit has one consistent algebraic current Example
- A dissipative backward Euler solve with a controlled update residual Example
- A dissipative scalar heat mode with Parareal correction Example
- A scalar diffusion mode gives an explicit two-grid MGRIT matrix Example
- Backward Euler differentiates a stiff scalar decay fit on its exact branch Example
- Newton can exhaust its budget although the dissipative backward Euler root is unique Example
- Rosenbrock–Euler damps a stiff scalar decay with the backward-Euler factor Example
- Trapezoidal ringing on a stiff scalar decay equation Example
- Autonomous Rosenbrock–Euler is one Newton correction of backward Euler Proposition
- Backward Euler has a globally defined nonexpansive resolvent (contractive when strongly dissipative) Theorem
- Backward Euler, the selected SDIRK, and two-stage Radau IIA converge at their stated orders under controlled stage residuals Theorem
- Coupled backward Euler is first order for a regular index-one DAE 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, Introduction à l’Analyse Numérique, Chapter III: Équations Différentielles Ordinaires (standard reference, not scraped)
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, §6.6 Multistep methods (standard reference, not scraped)