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.
Periodic semi-Lagrangian error is controlled by local foot and interpolation defects
Statement
Fix and a periodic box with grid width . Let solve the nonconservative linear transport equation with the periodic velocity and global flow of A periodic C1 velocity has a global characteristic flow on a finite horizon. Consider equal time steps and node updates where reconstructs a nodal array as a periodic function and is a computed backward foot. Suppose constants , , and are uniform over the refinement family and independent of . Assume for all node arrays, the pointwise interpolation defect at each computed foot is at most for the exact samples , and, for compatible lifts of the computed and exact feet, the foot error satisfies , for integers . If and , then, with In the contractive case , this becomes For the explicit Euler and tensor multilinear algorithm, Explicit Euler gives a second-order local backward-foot defect, Tensor multilinear interpolation has a second-derivative error bound, and Periodic multilinear interpolation is convex and L-infinity contractive give and . Thus convergence for this branch follows, for example, when , , and . No classical advective CFL restriction is used; the joint consistency refinement is still required by this bound.
Facts & Assumptions
Given: A smooth periodic transport solution, a finite time grid, a bounded-stability interpolation operator, a pointwise interpolation defect bound, a certified local backward-foot error, and initial grid error .
Linear transport equations and their characteristic flow: for , the spatial characteristic solves .
Explicit Euler characteristic backtracking with multilinear interpolation: the default update is obtained by evaluating the previous grid field at an approximate backward foot and applying periodic multilinear interpolation.
A periodic C1 velocity has a global characteristic flow on a finite horizon: the exact backward characteristic exists on the full time interval.
The chain rule for total derivatives: : differentiating gives .
Explicit Euler gives a second-order local backward-foot defect: for the default explicit Euler foot, the local error is at most .
Periodic multilinear interpolation is convex and L-infinity contractive: for the default multilinear interpolant, .
Tensor multilinear interpolation has a second-derivative error bound: for the default interpolant the pointwise defect is at most , so one may take and when .
Proof
Along the exact characteristic , [F1] gives . The chain rule [F4] therefore gives . Hence .
Add and subtract and . The operator bound gives a first difference at most ; the interpolation defect contributes at most ; and the spatial Lipschitz bound for plus the foot error contributes at most . Since , this is at most . Taking the maximum over nodes yields .
Induction on in the recurrence gives : at the sum is empty, and the recurrence multiplies the preceding finite sum by and adds its next term. Taking proves the first bound.
If , the sum in step 3.1 is , so substituting the definition of gives the second bound. The default Euler and tensor multilinear branch has the stated local constants by [F5]–[F7]. Therefore the displayed sufficient refinement conditions make both error terms and the initial error tend to zero. No step uses ; consistency follows from the two explicit defect terms rather than a classical advective CFL condition.
Remarks
For , the geometric sum in the first estimate is not uniformly bounded as grows. A high-order interpolation or limiter must therefore supply its actual operator bound and local defect before this theorem yields a stable convergence claim. This theorem is for the periodic branch; a nonperiodic boundary branch must separately account for first-hit and boundary-data error as in A transverse backward boundary hit has a certified time and trace error bound.
Depends on
- Explicit Euler characteristic backtracking with multilinear interpolation
- Linear transport equations and their characteristic flow
- A periodic C1 velocity has a global characteristic flow on a finite horizon
- Periodic multilinear interpolation is convex and L-infinity contractive
- Tensor multilinear interpolation has a second-derivative error bound
- Explicit Euler gives a second-order local backward-foot defect
- The chain rule for total derivatives: $D(g\circ f)(a)=Dg(f(a))\circ Df(a)$
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
18 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
- European Centre for Medium-Range Weather Forecasts, Numerical Methods, Meteorological Training Course Lecture Series, 2002 (standard reference, not scraped)
- Lukas Einkemmer and Alexander Ostermann, On the error propagation of semi-Lagrange and Fourier methods for advection problems, Computers & Mathematics with Applications 69 (2015), 170–179 (standard reference, not scraped)