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.
Two-dimensional logarithmic edge cutoff estimates
Statement
Let be a side of a shape-regular polygon of diameter with a matching quasiuniform boundary mesh of size . Let be the piecewise-linear boundary function equal to at the interior nodes of and at the endpoints and all other boundary nodes. For
one has . Also every continuous piecewise-affine on satisfies
Consequently, for the edge mean ,
where is nodal piecewise-linear interpolation on .
Facts & Assumptions
Given: A bounded-shape polygon, a shape-regular quasiuniform mesh, one side , and the seminorm/lifting equivalence of Discrete Schur energy and the fractional trace norm.
Scalar finite-element substructuring model: is the subdomain-to-mesh ratio, and shape regularity, polygon angles, the interior-cone parameter, scaled boundary-chart bounds and scaled mean-zero Poincare constants are uniform.
Discrete Schur energy and the fractional trace norm: the floating local Schur energy is the minimum over finite-element lifts of arbitrary boundary traces, is equivalent to the boundary Gagliardo seminorm modulo constants, and boundary data admit a stable finite-element lift.
Proof
If has no interior boundary node, then . If , scaling to unit length gives a uniform bound on both terms of . Otherwise the first and last mesh intervals have length comparable to , is linear from to and from to there, and it equals between them. The weighted integral on either endpoint interval is bounded by ; the plateau contributes at most . In the double integral, pairs in the plateau contribute zero. Pairs within one endpoint interval have integrand at most and hence contribute at most a constant. For one point in an endpoint interval and one outside it, integrating in the outside variable and then in gives a constant; the two endpoint intervals are treated in the same way. Therefore .
Put , , and . Choose a triangle containing a point where is maximal, and let be its centroid. Affine scaling gives . The uniform interior-cone condition in [F1] supplies at a cone of radius and angular interval of fixed positive length, contained in . Quasiuniformity and affine scaling give the global inverse bound . If is bounded, the inverse bound and mean-zero scaled Poincaré prove the claim directly. Otherwise choose . Along each cone ray, the integral of from to is at most , while weighted Cauchy–Schwarz gives Express by its value at minus these two radial integrals, square, and average with measure over , . The annulus has area comparable to ; the ray-energy term is independent of and integrates in to at most . Hence Mean-zero scaled Poincaré bounds the first term by , and the centroid comparison proves the asserted estimate. This is the radial argument underlying Widlund's estimate (5), with the centroid-to-maximum comparison included explicitly.
Put . In the first Gagliardo term use The weighted term is bounded by . Together these give On the two endpoint mesh intervals, is a quadratic interpolation error vanishing at both endpoints; scaling the interval to unit length bounds its norm by . The same estimate therefore holds for . The floating local Schur energy of the trace of is at most because it is the minimum over finite-element lifts; the lower trace-Schur bound in [F2] therefore gives . Also , so . Combining this with steps 1.1 and 1.2 proves the claimed squared-logarithmic multiplier estimate.
Depends on
Used by
Dependency tree · two levels
7 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
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 25–33 (standard reference, not scraped)
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2 §2.4, pp. 40–44 (standard reference, not scraped)