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✓ 15 results · all verified · 13 also independently AI-judged
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Adaptive finite-element methods

1 · Prerequisites

2 · Summary

The prerequisite page variational-crimes-and-strang-lemmas supplies the conforming variational framework. All functions and data are real-valued. This page fixes a bounded polygon in two dimensions, matching shape-regular affine triangles, continuous zero-boundary P1 spaces, exact integration, and exact Galerkin solves. It defines element residuals, outward normal-flux jumps, P0 cell-data oscillation, deterministic bulk marking, and budgeted conforming newest-vertex bisection (NVB).

The local moment interpolant and its patch, trace, and reproduction estimates support residual reliability. Cell and edge bubble tests give local efficiency and a marked correction lower bound up to data oscillation. The bulk sets remain the deterministic Dörfler marks; the refinement procedure requests three generations also on their original edge neighbors, supplying the adjacent-cell interior tests for the correction bound. This patch request has at most four times as many cells as the bulk union, and cumulative closure complexity includes that factor. Separate results prove NVB generation geometry, edge-label closure, cumulative refinement counts, common-overlay cardinality, localization of the Galerkin correction, and reduction of data oscillation and the residual estimator. Galerkin orthogonality gives exact energy decrease for the Laplacian; constant convection uses a distinct quasi-orthogonality branch with its explicit dual-pickup and fine-mesh condition.

The contraction result combines energy error, data oscillation, and (with a separate positive weight) the residual estimator. Optimal work complexity is proved only for P1 newest-vertex bisection for the Laplacian with data piecewise constant on the initial mesh and a declared approximation-class bound for 0<s≤1/2. The coefficient-dependent residual and projected edge-oscillation interface is definitional; this page proves no general coefficient-complexity theorem and makes no three-dimensional NVB claim.

3 · Logical flowchart

4 · Definitions, theorems and proofs

CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passOpen item page →

Weak well-posedness for constant divergence-free convection

Statement

Assume Countable Choice as in the cited Sobolev and Lax–Milgram suppliers. Let Ω⊂R2 be a bounded polygon, b∈R2 constant, and f∈L2(Ω;R). Here H01 is the zero-boundary closure of Zero-boundary Sobolev space as a norm closure. There is a unique real-valued u∈H01(Ω;R) satisfying ∫Ω∇u⋅∇v+(b⋅∇u)v dx=∫Ωfv dx(v∈H01(Ω)). No H2 regularity is asserted.

Facts & Assumptions

[A1]

Countable Choice is assumed for the cited Sobolev, Poincare and Lax–Milgram interfaces (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, a bounded polygon Ω, constant b, f∈L2(Ω), and the real Hilbert space H01(Ω).

[F1]

On a domain bounded in one direction, ∥v∥L2≤CP∥∇v∥L2 for every v∈H01; the supplier assumes Countable Choice (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction, The Axiom of Countable Choice (ACω)).

[F2]

The real bounded coercive (not necessarily symmetric) Lax–Milgram theorem assumes Countable Choice and gives a unique variational solution for every bounded linear functional (The Lax--Milgram theorem, The Axiom of Countable Choice (ACω)).

[F3]

W1,2 is a Hilbert space under its Sobolev inner product; its zero-boundary closure is closed, and Poincare makes the gradient norm equivalent to the inherited norm (The Sobolev space H1 is a Hilbert space, Hilbert space, Zero-boundary Sobolev space as a norm closure, The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction).

Proof

1.1A1F1F3givenalgebra

A bounded polygon lies in a finite-width slab, so [F1] applies. Define a(w,v)=∫∇w⋅∇v+(b⋅∇w)v. Cauchy–Schwarz and [F1] give ∣a(w,v)∣≤(1+∣b∣CP)∥∇w∥2∥∇v∥2; also F(v)=∫fv is linear and ∣F(v)∣≤CP∥f∥2∥∇v∥2. The gradient norm is complete on H01 by [F3], since Poincare makes it equivalent to the complete inherited H1 norm.

1.2A1F1F3givenalgebra

For w∈Cc∞(Ω), ∫(b⋅∇w)w=12∫b⋅∇(w2)=0 by compact support and constant b. Approximation in H01 extends this identity to every w∈H01, because w↦∫(b⋅∇w)w is continuous in the H1 norm and compactly supported smooth functions are dense by [F3]. Hence a(w,w)=∥∇w∥22, so a is coercive with constant 1 in the gradient norm.

2.1A1F1F2F3step 1.1step 1.2∎

Apply [F2] to the real Hilbert space H01(Ω) equipped with inner product (w,v)H=∫∇w⋅∇v, the bounded form from step 1.1, and its coercivity from step 1.2. This gives a unique u satisfying a(u,v)=F(v) for all v. These are exactly the displayed weak equations. Countable Choice is inherited from [F1], [F2] and [F3]; no full Axiom of Choice or elliptic regularity is used.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

A local moment interpolant for conforming P1 meshes

Definition

Assume Countable Choice for the H01 convention of The Axiom of Countable Choice (ACω).

Fix a finite conforming triangular mesh T. For each interior vertex z, choose the incident triangle with least fixed mesh index and denote it Kz. On the reference triangle K^, let λ^1,λ^2,λ^3 be its barycentric coordinates. The Gram matrix Gij=∫K^λ^iλ^j is positive definite because ∫K^p2>0 for every nonzero p∈P1(K^). Thus there are unique dual affine polynomials ψ^i∈P1(K^) with ∫K^λ^jψ^i=δij. Pull them to Kz by the affine map using the normalized measure so ∫Kzφyψz,Kz=δzy for its three local nodal hats.

For v∈H01(Ω) set cz(v)=∫Kzvψz,Kz at interior vertices and cz(v)=0 at boundary vertices. Define ITv=∑z interiorcz(v)φz, where φz is the continuous piecewise-affine nodal hat. The sum is finite and belongs to the conforming zero-boundary P1 space. This is a moment quasi-interpolant; it is not a point-evaluation operator on arbitrary Sobolev classes.

Interface

The Sobolev spaces and zero-boundary closure use Integer-order Sobolev spaces and their norms and Zero-boundary Sobolev space as a norm closure. The mesh and finite-element conventions use Matching affine simplicial meshes and shape regularity and Broken and conforming polynomial spaces on a matching mesh. Reproduction and bounds are established by a separate theorem on this page.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Compatible 2D newest-vertex-bisection meshes

Definition

A compatible labeled initial mesh is a finite matching affine simplicial triangulation T0 of a polygon in R2 as in Matching affine simplicial meshes and shape regularity, equipped with labels on its edges such that each triangle has one edge labeled 0 and two labeled 1, and every shared edge has the same label from both incident triangles. Matching means that distinct cell interiors are disjoint and any nonempty cell intersection is a whole common face: in two dimensions it may be a vertex or an edge. For a descendant triangle of generation g(K), its three edge labels, in any order, are (g(K)+1,g(K)+1,g(K)). The unique edge labeled g(K) is its reference edge.

To bisect K, join the midpoint of its reference edge to the opposite vertex. The two resulting triangles have generation g(K)+1. In each child, the two new half-edges and the bisector receive label g(K)+2; the one inherited nonreference edge retains label g(K)+1 and is the child's reference edge. A finite bisection forest is the collection of the initial triangles and all descendants reached by finitely many such bisections; its leaves form a triangulation when all shared-edge subdivisions agree. The admissible family T(T0) consists of the matching conforming leaf triangulations generated by these compatible bisections. A refinement T≤T∗ means every cell of T∗ lies in a cell of T.

For deterministic operational ordering, fix a finite starting mesh in this family and a total order of its cells. Enumerate those operational roots as K1,…,KN in that order; this starting mesh may already be a geometric descendant of T0, and operational numbering does not reset its generations or edge labels. Give root Kr identifier (r,∅) and order its three vertices lexicographically by their two real coordinates. If a parent has identifier (r,w), with w a finite binary word, let A be the earlier endpoint of its labeled reference edge in its stored vertex list, let B be the other endpoint, let C be the opposite vertex, and let M=(A+B)/2. Its children with vertex sets {A,M,C} and {B,M,C} receive identifiers (r,w0) and (r,w1), respectively. Each child's stored vertex list is the parent list restricted to its two retained vertices, in their previous order, followed by M. These lists are bookkeeping orders, independent of the orientation convention for affine reference maps. Compare identifiers first by root rank, then lexicographically by binary word, with 0<1 and a proper prefix before its extensions. This is a total order, so every finite nonempty pending set has a unique least identifier. Distinct roots or distinct binary paths have distinct identifiers, and a retained cell keeps its identifier and vertex list through all subsequent calls. This operational decoration changes no geometric bisection, reference edge, admissible triangulation or finite-element space.

The compatible initial labeling is a hypothesis, not a consequence of an arbitrary initial triangulation. This definition is two-dimensional and makes no claim about three-dimensional closure or complexity.

Interface

The geometry and closure properties of this family are separate theorems on the same page.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Residual indicators and data oscillation for P1 AFEM

Definition

Assume Countable Choice for the L2 and Sobolev conventions of The Axiom of Countable Choice (ACω).

All functions and data are real-valued. Let Ω⊂R2 be a bounded polygon and let T be a finite conforming matching triangulation by nondegenerate affine triangles, with maximum shape-regularity constant Γ. Write hK=diam⁡K and hE=diam⁡E. Let V(T) be the continuous, piecewise-affine zero-boundary subspace of Broken and conforming polynomial spaces on a matching mesh, which lies in H01(Ω;R) by Continuous matching piecewise polynomials belong to W1p and Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare. The exact weak model is −Δu+b⋅∇u=f,u∈H01(Ω;R),f∈L2(Ω;R),b∈R2 constant. The weak form is ∫Ω∇u⋅∇v+(b⋅∇u)v dx=∫Ωfv dx for every v∈H01(Ω;R). The case b=0 is the symmetric Laplace model. Given U∈V(T), its cell residual is RK(U)=f∣K−b⋅∇(U∣K); this is f+ΔU−b⋅∇U because ΔU=0 on each cell. For an interior edge E=K+∩K− define the outward flux jump JE(U)=∇U∣K+⋅nK++∇U∣K−⋅nK−, where nK± are the unit outward normals. Set ηK(U)2=hK2∥RK(U)∥L2(K)2+12∑E⊂∂K, E interiorhE∥JE(U)∥L2(E)2, and η(U,S)2=∑K∈SηK(U)2 for S⊂T. The factor 1/2 assigns each interior-edge contribution once globally. Let ΠK0 be the L2(K) projection onto constants. The cell data oscillation is osc⁡K(U)2=hK2∥RK(U)−ΠK0RK(U)∥L2(K)2,osc⁡(U,S)2=∑K∈Sosc⁡K(U)2. Since b⋅∇U is constant on K, this oscillation equals hK2∥f−ΠK0f∥22.

For a separate definitional interface, consider the symmetric diffusion model −div⁡(A∇u)=f, where A is a symmetric uniformly elliptic matrix field in the sense of Uniformly elliptic divergence-form operators and their sesquilinear forms and is Lipschitz on each cell. Its cell residual for a piecewise-affine U is RKA(U)=f+div⁡(A∇U), and its outward conormal-flux jump is the sum of A∇U⋅nK from the two incident cells. Let ΠE0 be the L2(E) projection onto constants. The projected edge term hE∥JEA−ΠE0JEA∥L2(E)2 records nonconstant conormal flux. The reliability, contraction, and complexity results authored here concern A=I only; this extension supplies notation and no coefficient-dependent theorem.

Prerequisite interface

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Uniform Poincare inequalities on vertex and cell patches

Statement

Assume Countable Choice, as in the reference-simplex trace and Poincare suppliers.

Let T be a conforming shape-regular triangular mesh. For an interior vertex z, let ωz be the union of its incident triangles; for a boundary vertex use the same patch. There is a constant C depending only on the shape-regularity bound such that, at an interior vertex, every v∈H1(ωz) satisfies ∥v−vωz∥L2(ωz)≤Chz∥∇v∥L2(ωz), where vωz is the patch mean and hz=max⁡K⊂ωzhK. On a boundary vertex patch, every v∈H01(Ω) satisfies ∥v∥L2(ωz)≤Chz∥∇v∥L2(ωz). For a cell K, define ωK=⋃z∈V(K)ωz, where V(K) is its set of three vertices. If K does not meet ∂Ω, the corresponding mean-zero estimate holds on ωK with scale hK; if K meets ∂Ω and v∈H01(Ω), then ∥v∥L2(ωK)≤ChK∥∇v∥L2(ωK).

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, a conforming triangular mesh with shape-regularity bound Γ, an interior or boundary vertex z, and respectively v∈H1(ωz) or v∈H01(Ω).

[F1]

On a reference simplex, mean-zero functions satisfy Poincaré's inequality and the trace is bounded by the H1 norm; affine scaling gives the corresponding cell bounds (Poincare–Wirtinger inequality on a reference simplex, Sobolev face traces and Gauss–Green on a reference simplex, Shape regularity controls affine simplex geometry, Zero-boundary Sobolev space as a norm closure).

[F2]

Shape regularity bounds the minimum angle away from zero; the polygonal mesh vertex stars are edge-connected and boundary stars meet a boundary edge (Shape regularity controls affine simplex geometry).

Proof

1.1A1F1F2givenalgebra

Scaling [F1] to each triangle K gives ∥v−vK∥L2(K)≤ChK∥∇v∥L2(K) and ∥v−vK∥L2(E)≤ChK1/2∥∇v∥L2(K) for every edge E⊂∂K. Shape regularity makes hE comparable to hK. If K,L share E, their traces of v agree, so ∣vK−vL∣ ∣E∣1/2≤∥v−vK∥L2(E)+∥v−vL∥L2(E)≤Chz1/2(∥∇v∥L2(K)+∥∇v∥L2(L)). Using ∣E∣1/2≥chz1/2 for cells in one shape-regular vertex star bounds the difference of neighboring means by the two gradient norms.

2.1step 1.1F2algebra

The star has at most NΓ cells, and its dual edge graph is connected. Join each cell to a fixed cell by a graph path of length at most NΓ−1 and apply step 1.1 along that path. The cell Poincaré bound from step 1.1 then gives ∥v−vK∥L2(ωz)≤Chz∥∇v∥L2(ωz). Since ∣vωz−vK∣≤∣ωz∣−1/2∥v−vK∥L2(ωz), replacing vK by the patch mean proves the interior estimate.

3.1A1F1F2step 1.1step 2.1given

For a boundary vertex patch choose one boundary edge E0⊂∂ωz. By the definition of H01 as the H1-closure of compactly supported smooth functions, and the continuous local trace bound in [F1], the trace of v is zero on E0. The trace inequality in step 1.1 therefore gives ∣vK∣ ∣E0∣1/2=∥v−vK∥L2(E0)≤Chz1/2∥∇v∥L2(K) for the incident cell K. The same bounded-path comparison of cell means from step 2.1 controls every cell mean in the star by C∥∇v∥L2(ωz). Summing the cell Poincaré bounds proves the boundary estimate.

4.1A1F1F2step 2.1step 3.1given∎

For a cell patch ωK, the three vertex stars are edge-connected because they all contain K, and the number of cells is at most three times the valence bound from [F2]. Along each edge-adjacency path, neighboring cell diameters are comparable by shape regularity, so all diameters in the patch are comparable to hK. The mean-zero estimate follows by applying the cell-mean comparison of step 2.1 over this connected finite graph. If K meets the boundary, ωK contains a boundary edge; apply the zero-trace argument of step 3.1 there and the same path comparison to all cells in the union. These two estimates are the asserted cell-patch inequalities.

AlgorithmAlgorithm: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

Dorfler marking and conforming newest-vertex refinement

Definition

Input: a finite labeled conforming mesh T, exact nonnegative arrays (ηK2)K∈T and (oK2)K∈T, where ηK2 is the cell estimator contribution and oK2 the cell data-oscillation contribution, bulk-fraction parameters θE,θO∈(0,1], a per-call total bisection budget B∈N0, and a stable total order of mesh identifiers. On the first call on a mesh not yet carrying operational forest identifiers, rank its cells by the supplied order and initialize the operational roots and vertex lists of Compatible 2D newest-vertex-bisection meshes. This initialization preserves the supplied order on those cells and does not change their geometric generations or labels. On subsequent calls retain that forest decoration and use its identifier order. Thus each current input leaf, including every generated descendant, has a specified identifier. For an array qK≥0 and θ∈(0,1], sort by decreasing qK and then increasing identifier. If ∑KqK=0, return the empty set. Otherwise return the shortest initial segment whose sum is at least θ∑KqK. Thus these parameters are fractions of the squared contributions (the square-root convention for the usual estimator-norm parameter). Call the resulting sets ME,MO and set M=ME∪MO.

Before modifying the mesh, form the original edge-neighbor request set Q={L∈T:L=K or L shares an edge with some K∈M}. Thus ME,MO and their union M remain the bulk marks; Q is the larger refinement request, with M⊆Q and #Q≤4#M because a triangle has at most three edge neighbors. For M=∅, also Q=∅. Set a remaining-generation flag qK=3 on each cell in Q and qK=0 on every other cell. Repeatedly take the pending leaf with least stable identifier and process its reference edge. If the reference edge is on the polygon boundary, bisect that leaf. If its interior reference neighbor has the same generation, bisect the compatible pair simultaneously. If the neighbor has generation one lower, recursively process that neighbor first and then re-inspect the original leaf; this follows the finite reference-edge chain until the edge can be split conformingly. Every split leaf T is replaced by its two children with the binary-path identifiers and stored vertex lists prescribed by Compatible 2D newest-vertex-bisection meshes, each inheriting qT−1 when qT>0 and otherwise 0. Thus conformity splits may propagate without scheduling extra uniform generations, while every originally requested cell in Q and its descendants complete all three requested generations. Process simultaneous pairs in the same transaction and use the fixed identifier order for all pending leaves. Stop when all remaining-generation flags vanish. Count every bisection against B. If closure or a pending request would exceed the remaining budget, discard the tentative splits and their new identifiers, retaining the original identifiers and vertex lists, and return the original mesh with status budget-exhausted; otherwise return the refined matching mesh with status complete. Invalid arrays, nonfinite or negative entries, invalid parameters, or incompatible labels return invalid-input without changing the mesh. All arithmetic and comparisons in this mathematical algorithm are exact; implementation error, linear algebra, and quadrature are outside its scope.

Postconditions

A complete output is a conforming descendant, contains the uniform three-generation subdivision of every original cell in Q, and hence has an interior vertex in every bulk-marked cell and all its original edge neighbors. Every originally marked cell is refined; the sets ME,MO themselves are unchanged by the patch expansion. Termination, shape regularity and cumulative element counts are separate result claims on this page. This definition makes no operation bound claim for a single refinement call.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-6-luna)Open item page →

The P1 AFEM approximation class

Definition

Assume Countable Choice. The space H01(Ω) is the closure of Cc∞(Ω) in the H1 norm, as in Zero-boundary Sobolev space as a norm closure and The Axiom of Countable Choice (ACω).

Fix a compatible initial triangulation T0, its 2D NVB family T(T0) from Compatible 2D newest-vertex-bisection meshes, and a weak solution u∈H01(Ω) of the symmetric A=I, b=0 model in Residual indicators and data oscillation for P1 AFEM. For a conforming refinement T, let V(T) be its continuous P1 zero-boundary space and define E(T;u)=inf⁡v∈V(T)∥∇(u−v)∥L2(Ω),EN(u)=inf⁡T∈T(T0)#T−#T0≤NE(T;u). For s>0, the approximation seminorm and class are ∣u∣As=sup⁡N≥0(N+1)sEN(u),As={u∈H01(Ω):∣u∣As<∞}. The infimum is over a nonempty finite-budget set because T0 is allowed. This definition concerns best energy approximation, not the number of cells selected by an algorithm. For the symmetric Laplace Galerkin solution, Céa quasi-optimality for coercive conforming Galerkin problems supplies the unique exact solution, while Galerkin orthogonality for conforming approximations gives orthogonality in the gradient inner product. Expanding the square shows that the exact Galerkin error equals E(T;u).

Interface

The model, P1 spaces, and energy norm are those of Broken and conforming polynomial spaces on a matching mesh and Residual indicators and data oscillation for P1 AFEM. This class is used only in the restricted P1 Laplace optimal-complexity result on this page.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Quasi-orthogonality for constant convection on a fine initial mesh

Statement

Assume Countable Choice, as in the zero-boundary Sobolev convention.

Let TH≤Th be nested conforming meshes and let UH,Uh be exact P1 Galerkin solutions for the constant-convection model of Residual indicators and data oscillation for P1 AFEM. Write ej=u−Uj and d=Uh−UH. For b=0, ∥∇eh∥22=∥∇eH∥22−∥∇d∥22. For constant b, assume the explicit dual-pickup bound ∥eh∥L2≤CDh0s∥∇eh∥L2 for the nested sequence, with s>0, where h0=max⁡K∈T0diam⁡K, and put μ=CDh0s∣b∣<1. Then ∥∇eh∥22≤(1−μ)−1∥∇eH∥22−∥∇d∥22. The dual-pickup bound is an additional hypothesis. It is not asserted for every polygon or mesh.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, nested conforming P1 spaces, exact Galerkin solutions, constant b, and in the nonsymmetric case the stated dual-pickup bound.

[F1]

Galerkin orthogonality says a(u−Uh,vh)=0 for every vh∈V(Th); nestedness puts d=Uh−UH in the fine space (Galerkin orthogonality for conforming approximations).

[F2]

H01 is the closure of compactly supported smooth functions in H1; constant-vector integration by parts on those functions extends by continuity to this closure (Zero-boundary Sobolev space as a norm closure, Integer-order Sobolev spaces and their norms).

Proof

1.1A1F1givenalgebra

If b=0, [F1] with vh=d gives (∇eh,∇d)=0. Since eH=eh+d, expanding the squared norm yields ∥∇eH∥22=∥∇eh∥22+∥∇d∥22. Rearrangement is the symmetric identity.

1.2A1F1F2givenalgebra

For constant b, [F1] gives (∇eh,∇d)+(b⋅∇eh,d)=0. By [F2], (b⋅∇eh,d)=−(b⋅∇d,eh). Expanding eH=eh+d therefore gives ∥∇eH∥22=∥∇eh∥22+∥∇d∥22+2(b⋅∇d,eh). The sign in this identity follows directly from the preceding orthogonality equation.

2.1A1step 1.2givenalgebra∎

By the assumed dual-pickup estimate and Cauchy–Schwarz, ∣2(b⋅∇d,eh)∣≤2∣b∣∥∇d∥2∥eh∥2≤2μ∥∇d∥2∥∇eh∥2≤μ(∥∇d∥22+∥∇eh∥22). Using this in step 1.2 gives (1−μ)∥∇eh∥22≤∥∇eH∥22−(1−μ)∥∇d∥22. Divide by 1−μ>0 to obtain the stated estimate.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passjudge pass (gpt-6-luna)Open item page →

Shape regularity and local reduction under 2D newest-vertex bisection

Statement

For any compatible 2D initial labeling from Compatible 2D newest-vertex-bisection meshes, every conforming NVB descendant has shape regularity bounded by a constant depending only on the initial mesh. Three complete generations of uniform bisection of a triangle split each original edge at its midpoint, create a new interior midpoint on the median from the opposite vertex, and give child diameters at most half the parent diameter.

Three-generation reference picture

The drawing shows three uniform NVB generations of ABC with reference edge AB. M,N,P are the midpoints of the three original sides; S is the midpoint of median CM and is interior; Q,R are the midpoints of AM,BM. The eight leaves and their coordinates are verified in proof step 2.1. The dashed original edge AB is the reference edge. The picture fixes the point conventions only; no proof relies on it.

ABCMNPSQR

Facts & Assumptions

Given: A finite shape-regular conforming triangular initial mesh with compatible edge labels as in Compatible 2D newest-vertex-bisection meshes.

[F1]

Each bisection splits the reference edge at its midpoint and assigns the two newly created edges and inherited edges the labels specified by generation; shared edges have one common label (Compatible 2D newest-vertex-bisection meshes).

Proof

1.1F1givenalgebra

Write the parent vertices as A,B,C, with reference edge AB, midpoint M, and squared side lengths X=∣AC∣2, Y=∣BC∣2, Z=∣AB∣2. The two first children have edge-length squares {X,Z/4,W} and {Y,Z/4,W}, where W=∣(A+B)/2−C∣2=(2X+2Y−Z)/4 by expanding the squared norm. The four labeled types have squared edge lists {X,Y,Z}, {Z/4,X,W}, {Z/4,Y,W}, and {X/4,Y/4,W}. In type 1 the reference side has square X, and the new median square is (2(Z/4)+2W−X)/4=Y/4; its children therefore have side lists {X/4,Z/4,Y/4} and {X/4,W,Y/4}, which are a quarter-scale type 0 and type 3. The type 2 calculation interchanges X,Y. In type 3 the reference side has square W, and its median square is (2(X/4)+2(Y/4)−W)/4=Z/16; its children are quarter-scale types 1 and 2. Type 0 gives types 1 and 2 by the first bisection. Hence this finite list is closed under every labeled bisection and no other normalized shape occurs.

2.1F1step 1.1given

Each of the finitely many normalized triangles in step 1.1 is nondegenerate: its area is half the parent area at each bisection and its side lengths are the explicit midpoint lengths, so its three angles are positive. The minimum of these finitely many angles and the initial minimum angle is positive. Hence all descendants have a common positive minimum angle and a common shape-regularity bound. The angle minimum over this finite list is positive; the maximum shape-regularity constant over it and the initial cells is therefore finite.

3.1F1step 1.1algebra∎

After the first generation the midpoint M of AB is present. The second generation bisects AC and BC, adding their midpoints N and P. The four second-generation triangles have reference edges on the segments AM,BM,CM; the third generation bisects those segments, in particular CM, adding its midpoint S in the interior of ABC. The eight leaves have vertex triples (A,N,Q),(Q,M,N),(N,M,S),(N,S,C),(P,M,R),(P,R,B),(P,C,S),(P,S,M), where Q=(A+M)/2 and R=(B+M)/2. Subtracting these vertex coordinates shows that each leaf side is an original side divided by 2, the median ∣C−M∣ divided by 2, or the reference side divided by 4. Since M lies on AB, convexity of the norm gives ∣C−M∣≤max⁡{∣C−A∣,∣C−B∣}≤diam⁡(ABC). Thus every leaf side, and hence every leaf diameter, is at most half the parent diameter.

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Element and edge residual representation for P1 Galerkin errors

Statement

Assume Countable Choice, as in the Sobolev and simplex trace suppliers.

Let T be a matching triangular mesh, U∈V(T), and u solve the weak model from Residual indicators and data oscillation for P1 AFEM. For every v∈H01(Ω), ∫Ω∇(u−U)⋅∇v+(b⋅∇(u−U))v=∑K∈T∫KRK(U)v−∑E interior∫EJE(U)v.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, the weak equation, matching affine triangles, continuous P1 function U, and v∈H01(Ω).

[F1]

On an affine simplex, Green's identity holds for the polynomial vector field ∇U and Sobolev test functions; opposite outward normals cancel on a shared matching facet (Sobolev face traces and Gauss–Green on a reference simplex, Interior facet orientations cancel in a matching mesh).

[F2]

H01 is the closure of smooth compactly supported functions, and continuous matching piecewise-affine functions with zero boundary values belong to this space (Zero-boundary Sobolev space as a norm closure, Continuous matching piecewise polynomials belong to W1p, Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare).

Proof

1.1A1F1given

For smooth compactly supported v, integrate ∫K∇U⋅∇v=−∫KΔU v+∫∂K(∇U⋅nK)v on every cell using [F1]. Since U∣K is affine, ΔU=0. The sum of boundary integrals on each interior edge is ∫EJE(U)v, and boundary-edge terms vanish because v is compactly supported.

2.1step 1.1givenalgebra

The weak residual is (f,v)−∫∇U⋅∇v−∫(b⋅∇U)v. Substituting step 1.1 gives cell integrands f−b⋅∇U=RK(U) and the negative of the summed outward flux jumps. This is the displayed formula for smooth compactly supported v.

3.1A1F1F2step 2.1∎

Smooth compactly supported functions are dense in H01 by its definition. Every term in the identity is continuous in the H1 norm: volume terms use f,∇U∈L2, and edge terms use the trace inequality from [F1] on the finite mesh. Passing to the limit extends step 2.1 to all v∈H01.

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Local approximation and reproduction of the P1 moment interpolant

Statement

Assume Countable Choice, as in the Sobolev, affine-scaling and trace suppliers.

Let T be a shape-regular conforming triangular mesh and let IT be the moment interpolant from A local moment interpolant for conforming P1 meshes. For each cell K, let ωK be the union of vertex stars of its vertices. There is a constant C depending only on shape regularity such that for every v∈H01(Ω), ∥v−ITv∥L2(K)≤ChK∥∇v∥L2(ωK),∥∇ITv∥L2(K)≤C∥∇v∥L2(ωK), and, for every interior edge E⊂∂K, ∥v−ITv∥L2(E)≤ChE1/2∥∇v∥L2(ωK∪ωK′), where K′ is the other incident cell. The operator maps into V(T) and reproduces every member of V(T).

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, a shape-regular conforming triangular mesh, v∈H01(Ω), the moment interpolant of A local moment interpolant for conforming P1 meshes, and the patch inequalities of Uniform Poincare inequalities on vertex and cell patches.

[F1]

On each reference triangle, the three barycentric coordinates form a basis of P1 and their Gram matrix is positive definite; affine scaling transfers the dual moments and polynomial norm bounds to every shape-regular cell (A local moment interpolant for conforming P1 meshes, Polynomial derivative and face norms are controlled on a reference simplex, Shape regularity controls affine simplex geometry).

[F2]

Matching continuous piecewise-affine functions belong to W1,2, and a continuous piecewise-affine function with zero boundary nodal values belongs to W01,2 (Continuous matching piecewise polynomials belong to W1p, Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare).

[F3]

Vertex stars have bounded overlap and uniformly bounded valence on a shape-regular conforming mesh (Uniform Poincare inequalities on vertex and cell patches).

Proof

1.1A1F1F2given

The definition gives finitely many coefficients, each an integral against a bounded affine polynomial, hence a linear functional on L2(Kz); the resulting finite sum is continuous piecewise affine. Its boundary nodal coefficients are zero, so [F2] places it in V(T). If v∈V(T), then on the selected cell Kz its affine restriction is a linear combination of the three local hats. The dual moment identities recover its nodal coefficient at z, so cz(v)=v(z) at every interior vertex; at boundary vertices both the coefficient and the P1 trace value are zero. Therefore ITv=v.

1.2A1F1F3givenalgebra

For a cell K not meeting the boundary, set c=vωK; for a boundary cell set c=0. The patch Poincaré estimate gives ∥v−c∥L2(ωK)≤ChK∥∇v∥L2(ωK). For each interior vertex z of K, put az=cz(v)−c=∫Kz(v−c)ψz,Kz; this equality follows from the dual identities, which give ∫Kzψz,Kz=1. These are local integrals of an L2(Kz) function, with no application of IT to v−c. The scaled dual bound gives ∣az∣≤ChK−1∥v−c∥L2(Kz), since Kz⊂ωK and its diameter is comparable to hK. At a boundary vertex of K, necessarily c=0 and the corresponding coefficient difference is zero. The three barycentric hats on K sum to one, so (ITv−c)∣K=∑z∈V(K), z interiorazφz∣K. Each hat has L2(K) norm at most ChK and gradient norm at most C. Thus ∥ITv−c∥L2(K)≤C∥v−c∥L2(ωK) and ∥∇ITv∥L2(K)≤ChK−1∥v−c∥L2(ωK). The patch inequality and v−ITv=(v−c)−(ITv−c) prove the first two bounds. This argument uses only that each selected Kz is incident to z, so its constants are uniform over all such selections.

2.1A1F1F3step 1.2algebra∎

Apply the scaled trace inequality to v−ITv on K. The first two bounds from step 1.2 control the cell L2 term and its gradient; the neighboring patch gives the same estimates on K′. Since hE and hK are comparable by shape regularity, this yields the asserted edge bound.

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Common NVB refinement and overlay cardinality

Statement

For two compatible conforming NVB descendants T1,T2 of the same initial mesh T0, the union of their bisection forests defines a smallest common conforming overlay T1⊕T2 and #(T1⊕T2)≤#T1+#T2−#T0.

Facts & Assumptions

Given: A fixed compatible labeled initial triangulation and two of its finite conforming bisection forests.

[F1]

Compatible initial labels and the midpoint bisection rule uniquely assign labels to descendant edges, independent of which incident triangle generates the shared edge (Compatible 2D newest-vertex-bisection meshes, Shape regularity and local reduction under 2D newest-vertex bisection).

Proof

1.1F1givenconstruct

Let Fi be the finite binary forest for Ti. Their node union F=F1∪F2 is a forest: every nonroot node keeps its parent, and a node is either a leaf in both forests or has its same two children in at least one; if it has children in either forest, the union contains both. The common initial edges have equal labels. Induct on the bisection depth of any shared edge: its midpoint is uniquely determined by the segment, and its two half-edge labels are determined by the same generation rule [F1]; therefore both incident forests prescribe the same descendants on that edge. The leaves of F consequently form a matching conforming triangulation refining both T1 and T2. Any common refinement must contain every node split in either forest, so it contains F and refines its leaf partition. Thus this is the smallest common conforming overlay.

2.1step 1.1algebra∎

For each initial root, a finite full binary tree with i internal nodes has i+1 leaves; induction on i proves this because splitting one leaf increases the leaf count by one. The internal nodes of F are the union of the internal nodes of F1,F2, so #Int⁡(F)≤#Int⁡(F1)+#Int⁡(F2). Summing the leaf identity over the #T0 roots gives #Ti=#T0+#Int⁡(Fi) and the same identity for the overlay. Substitution proves the inequality.

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Data oscillation reduction under three-generation refinement

Statement

Assume Countable Choice for the L2 projection convention.

Suppose the three-generation marked refinement call completes and returns T∗≥T, and let osc⁡T(K)2=hK2∥f−ΠK0f∥22. For a Dörfler set MO with parameter θO∈(0,1], osc⁡T∗2≤γOosc⁡T2,γO=1−34θO<1.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, f∈L2(Ω), nested matching cells, P0 projections, and a three-generation refinement of every K∈MO.

[F1]

Three generations give each descendant of a marked parent diameter at most half its diameter (Shape regularity and local reduction under 2D newest-vertex bisection).

[F2]

The Dörfler set satisfies ∑K∈MOosc⁡T(K)2≥θOosc⁡T2 by its construction (Dorfler marking and conforming newest-vertex refinement).

Proof

1.1A1F1givenalgebra

For each parent K∈T, let K′ range over its descendants in T∗, including K′=K if it is unrefined. Nestedness of the piecewise-constant spaces gives ∑K′⊂K∥f−ΠK′0f∥L2(K′)2≤∥f−ΠK0f∥L2(K)2. Indeed, the childwise projection space contains the parent constant space, and the L2 orthogonal projection minimizes squared error. If K∈MO, the completed call supplies three generations, so [F1] gives hK′2≤hK2/4 and the sum of descendant oscillations is at most one quarter of the parent oscillation. For every other parent, containment gives hK′≤hK, so its descendant oscillations sum to at most its original contribution. An unrefined cell retains its contribution exactly.

2.1A1F2step 1.1algebra∎

Summing step 1.1 over refined parents gives osc⁡T∗2≤osc⁡T2−34∑K∈MOosc⁡T(K)2. Apply the bulk inequality [F2] to obtain the stated γO. If all oscillations vanish, both sides are zero and the same inequality holds.

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Localized energy estimate for nested Galerkin solutions

Statement

Assume Countable Choice, as in the Sobolev interpolation suppliers.

Let T≤T∗ be conforming P1 meshes with exact Galerkin solutions U,U∗. Let R={K∈T:K is subdivided in T∗} and let ω(R) be the union of the vertex stars of cells in R. Then ∥∇(U∗−U)∥L2(Ω)2≤C∑K∈RηK(U)2, where C depends on shape regularity, ∣b∣hmax⁡, and the local interpolant constants.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, a nested matching refinement, exact conforming P1 Galerkin solutions, and the constant-convection model.

[F1]

The coarse residual pairs the weak error with any H01 function as the cell residual sum minus the outward flux jump sum (Element and edge residual representation for P1 Galerkin errors).

[F2]

The local moment interpolant is P1-reproducing and satisfies local volume, gradient and edge estimates (Local approximation and reproduction of the P1 moment interpolant).

[F3]

Galerkin orthogonality holds on both nested conforming spaces (Galerkin orthogonality for conforming approximations).

Proof

1.1A1F2givenconstructalgebra

Define an auxiliary coarse moment map J:H01(Ω)→V(T) for this nested pair. At each interior vertex z, choose the least-index incident coarse cell Lz∉R if one exists, otherwise the original selected cell Kz, and use its dual affine moment qz(w)=∫Lzwψz,Lz; at boundary vertices use zero. Set Jw=∑z interiorqz(w)φz. The same conforming zero-boundary membership argument as in [F2] applies. Its bounds are uniform: on a cell K use the patch mean c when K misses the boundary and c=0 otherwise. Then qz(w)−c=∫Lz(w−c)ψz,Lz for interior vertices, while boundary coefficient differences are zero. Because Lz⊂ωK and hLz≍hK, the scaled dual bound gives ∣qz(w)−c∣≤ChK−1∥w−c∥L2(Lz). The hat bounds and patch Poincaré argument in the proof of [F2] therefore give ∥w−Jw∥L2(K)≤ChK∥∇w∥L2(ωK) and ∥∇Jw∥L2(K)≤C∥∇w∥L2(ωK). Applying the same scaled trace inequality as in [F2] gives its edge bound as well. All these operations have input w∈H01(Ω); shifted functions enter only the local integrals.

2.1A1F3step 1.1givenalgebra

Put d=U∗−U. The fine Galerkin equation and coarse equation imply a(u−U∗,d)=0 and a(u−U,Jd)=0. Since b is constant and d∈H01(Ω), ∫(b⋅∇d)d=0, so a(d,d)=∥∇d∥22. Also a(u−U,d)=a(d,d) because u−U=d+(u−U∗) and fine orthogonality kills the latter term paired with d. Hence ∥∇d∥22=a(u−U,d−Jd).

3.1A1F1F2step 1.1step 2.1algebra∎

If K∉R, then d is affine on K. At every interior vertex z of K, the selected Lz is also unchanged, so d∣Lz is affine and its dual moment equals the common nodal value d(z); boundary coefficients equal d(z)=0. Consequently Jd=d on every unchanged cell. The trace of d−Jd also vanishes on every edge incident to an unchanged cell. Thus [F1] applied to step 2.1 contains only volume residuals on R and interior edges with both incident cells in R. Use the volume and edge estimates proved in step 1.1. The surviving squared residual weights are bounded by C∑K∈RηK(U)2, since each surviving edge contribution occurs in the indicators of its incident refined cells. Cauchy–Schwarz and uniformly bounded overlap of the coarse vertex patches bound the other factor by C∥∇d∥2, giving ∥∇d∥22≤C(∑K∈RηK(U)2)1/2∥∇d∥2. If this gradient norm is zero the claim is immediate; otherwise divide by it and square.

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Termination and cumulative complexity of NVB conformity closure

Statement

Fix a compatible labeled initial mesh. Recursive reference-edge closure of any finite marked set terminates, produces a matching conforming NVB descendant, and preserves the shape bound of Shape regularity and local reduction under 2D newest-vertex bisection. For any sequence of finite request sets Qk, with three uniform generations requested on each cell of Qk, there is a constant Cgen depending only on the initial mesh such that #Tn−#T0≤Cgen∑k=0n−1#Qk. For the algorithm Dorfler marking and conforming newest-vertex refinement, keep Mk=ME,k∪MO,k as the bulk-marked set and use its original edge-neighbor request set Qk. Then #Qk≤4#Mk, so with Ccl=4Cgen, #Tn−#T0≤Ccl∑k=0n−1#Mk. The constant is for the cumulative sequence; no uniform bound on the added cells in one single refinement call is asserted.

Facts & Assumptions

Given: A compatible labeled initial triangulation, finite request sets Qk, bulk sets Mk when using patch expansion, and the recursive closure rule of Dorfler marking and conforming newest-vertex refinement.

[F1]

In every descendant, edge labels have the generation pattern (g+1,g+1,g), the reference edge has label g, and bisection uses midpoint subdivision (Compatible 2D newest-vertex-bisection meshes).

[F2]

All descendants have a uniform shape-regularity bound; three requested generations split marked parent edges and the mesh remains geometrically similar within a finite family of shapes (Shape regularity and local reduction under 2D newest-vertex bisection).

Proof

1.1F1givenalgebra

For a current cell K, follow its interior reference-edge neighbor. The common label is g(K); by [F1] the neighbor either has the same generation, giving a compatibly divisible pair, or has generation g(K)−1. Continue in the latter case. Strict generation drops terminate at a boundary reference edge or compatible pair. Refine from that terminal end and re-inspect each earlier pending leaf, as the algorithm prescribes. A coarser neighbor may need two bisections: after its reference-edge split, the child containing the pending common edge has that inherited edge as reference and is bisected before returning to K. These are children or grandchildren of a chain cell L; for a coarser chain cell g(L)≤g(K)−1, so their generations are at most g(K)+1. The terminal partner and K itself need one split. Each processed common edge is split on both sides, so the resulting mesh is conforming. The finite chain and this finite reinspection give termination for one request, and the finitely many requested descendant generations give termination of a complete call.

2.1F1F2step 1.1algebra

Let g(K) denote generation. Each bisection halves area, and [F2] gives constants c0,C0>0 depending only on the finitely many initial shapes such that c0 2−g(K)≤∣K∣≤C0 2−g(K) and diam⁡K≤C0 2−g(K)/2. In the backward chain of step 1.1 there is at most one cell at each generation, plus at most one terminal compatible partner. Hence the sum of diameters from generation gmin⁡ upward is at most D02−gmin⁡/2 with D0=2C0/(1−2−1/2). Every created cell is a child of K or its terminal same-generation partner, or a child or grandchild of a strictly coarser chain cell. Step 1.1 therefore gives g(T)≤g(K)+1. For a created cell T within an original chain cell L, the portion of the chain between K and L has its lowest generation g(L); summing its diameters gives dist⁡(K,T)≤D12−g(T)/2 with D1=4D0. The chain is finite by the integer generation drop, and these estimates supply the geometric radius used below.

3.1step 2.1givenalgebra

First consider one-generation requests in a finite sequence and let M be the union of all requested cells. For a final cell T and marked cell T∗ define a nonnegative allocation λ(T,T∗)={a(g(T∗)−g(T)),dist⁡(T,T∗)<D B 2−g(T)/2 and g(T)≤g(T∗)+1,0,otherwise, where a(ℓ)=(ℓ+2)−2 for ℓ≥−1, b(ℓ)=2ℓ/3 for ℓ≥0, A=∑ℓ≥−1a(ℓ)<∞, B=∑ℓ≥02−ℓ/2b(ℓ)<∞, and D=2D1+2C0, with D1 from step 2.1. The series for B is geometric with ratio 2−1/6<1, and c∗=inf⁡ℓ≥1a(ℓ)b(ℓ)>0 because 2ℓ/3/(ℓ+2)2 tends to infinity.

3.2step 2.1givenalgebra

Fix T∗∈M with generation g∗. At a fixed generation g≤g∗+1, cells with nonzero allocation lie in a ball of radius DB2−g/2 about T∗. Each has area at least c02−g by step 2.1, while that ball enlarged by one cell diameter has area at most CD2−g. Since cell interiors are disjoint, their number is at most a constant ND independent of g,T∗, and the final level. Summing weights over generations therefore gives ∑T∈Tn∖T0λ(T,T∗)≤ND∑ℓ≥−1a(ℓ)=NDA=:C1.

3.3step 2.1givenalgebra

Fix a new cell T0 in the final forest. Trace its unique parent backward through the finite refinement history. If the parent was created during closure, take the least-ID requested cell whose recursive chain created it; repeat this at each earlier creation time. This gives a finite sequence of requested cells T1,…,TJ ending at an initial cell. Step 2.1 gives g(Tj+1)≥g(Tj)−1 and, for each consecutive pair in the sequence, dist⁡(Tj−1,Tj)≤D12−g(Tj−1)/2. Let s be the first index with g(Ts)=g(T0)−1. The prefix whose links join T0 to Ts is T0,…,Ts−1; each of its generations is g(T0)+ℓ for some ℓ≥0. The triangle inequality for set distances includes the diameters of the intervening cells. Steps 2.1 and the diameter bound control the sum by (D1+C0) times the corresponding generation sum; D=2(D1+C0) leaves strict slack. Consequently, if this prefix has at most b(ℓ) cells at every generation g(T0)+ℓ, then dist⁡(T0,Ts)<DB 2−g(T0)/2. Thus the terminal requested cell Ts lies in the allocation radius and contributes a(−1)>0. Otherwise let j∗ be the first prefix with more than b(ℓ∗) cells at some generation g(T0)+ℓ∗. Every earlier link prefix satisfies the displayed distance bound. If ℓ∗=0, since T0 is new and b(0)=1, at least one other cell of that generation is a marked cell and contributes a(0). If ℓ∗>0, all cells of that generation in the prefix are marked; each lies within the allocation radius and contributes a(ℓ∗). In this case their total is greater than a(ℓ∗)b(ℓ∗)≥c∗. Hence every new cell receives at least C2=min⁡{a(−1),a(0),c∗}>0 allocation.

4.1step 3.2step 3.3algebra∎

Sum the lower bound from step 3.3 over new cells and interchange the two finite sums. The upper bound from step 3.2 gives C2(#Tn−#T0)≤∑T∗∈M∑T∉T0λ(T,T∗)≤C1#M. For three requested generations, view each parent in Qk as successive one-generation requests. There are at most 2j−1#Qk virtual requests at stage j=1,2,3, even if closure performs some requested splits before their scheduled turn. The total is at most 7#Qk, giving Cgen=7C1/C2. For the algorithm, every original triangle has at most three edge neighbors, so #Qk≤4#Mk; hence Ccl=28C1/C2 proves the displayed estimate in terms of the unchanged bulk marks. Empty marks give no requests or splits, and all bisections, including those needed for patch expansion and conformity, are counted.

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Residual reliability and local efficiency for P1 AFEM

Statement

Assume Countable Choice, as in the Sobolev trace and inverse-estimate suppliers.

Let T be a conforming shape-regular triangular mesh, let u∈H01(Ω) solve the model of Residual indicators and data oscillation for P1 AFEM, and let U∈V(T) be its exact P1 Galerkin solution. There are constants Crel,Ceff depending only on the shape bound and ∣b∣hmax⁡ such that ∥∇(u−U)∥22≤Crelη(U,T)2, and for every K∈T, ηK(U)2≤Ceff(∥∇(u−U)∥L2(ωK)2+osc⁡(U,ωK)2), where ωK is the union of K and its edge neighbors. If T∗≥T contains the uniform three-generation subdivision of every cell in the original edge-neighbor patch ω(M) of M⊂T (in particular, every complete call of Dorfler marking and conforming newest-vertex refinement has this property) and U∗ is the exact fine Galerkin solution, then η(U, M)2≤Ceff(∥∇(U∗−U)∥L2(ω(M))2+osc⁡(U,ω(M))2), with ω(M) the union of edge-neighbor patches of marked cells. All constants are independent of the refinement level.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, the exact weak solution, conforming P1 Galerkin solution, shape-regular matching mesh, residual estimator, and three-generation refinement of the bulk marks and their original edge neighbors.

[F1]

The error pairs with an arbitrary H01 test function as the sum of cell residuals and negative outward flux jumps (Element and edge residual representation for P1 Galerkin errors).

[F2]

The moment interpolant has local L2, gradient, edge-trace bounds, maps into the conforming zero-boundary P1 space, and reproduces P1 functions (Local approximation and reproduction of the P1 moment interpolant).

[F3]

Polynomial inverse and affine-scaling estimates on shape-regular triangles give uniform norm bounds for fixed-degree barycentric bubbles and P1 hats (Polynomial inverse and discrete trace inequalities, Shape regularity controls affine simplex geometry).

[F4]

Three generations place an interior median midpoint in each requested triangle, with the eight explicit leaves of the reference pattern, and a midpoint in each original edge; the refined family is uniformly shape regular (Shape regularity and local reduction under 2D newest-vertex bisection).

[F5]

Continuous matching piecewise polynomials with zero boundary trace belong to H01 (Continuous matching piecewise polynomials belong to W1p, Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare).

Proof

1.1A1F1F2givenalgebra

Put e=u−U and write a(w,v)=∫Ω∇w⋅∇v+(b⋅∇w)v. By the exact Galerkin equation, a(U,vh)=∫Ωfvh for every vh∈V(T); subtracting from the weak equation gives a(e,vh)=0. For w∈Cc∞(Ω), constancy of b gives ∫(b⋅∇w)w=12∫b⋅∇(w2)=0. The map w↦∫(b⋅∇w)w is continuous in H1, so density extends this identity to all w∈H01. Hence a(e,e)=∥∇e∥22 and, since ITe∈V(T), ∥∇e∥22=a(e,e−ITe). Apply [F1] to e−ITe. Cauchy–Schwarz, the cell and edge interpolation bounds [F2], and finite overlap of vertex patches give ∥∇e∥22≤Cη(U,T)∥∇e∥2. If ∥∇e∥2=0 reliability is immediate; otherwise divide by it and square. This proves the global upper bound.

1.2A1F1F3F5givenalgebra

For each cell let RˉK=ΠK0RK, and let λ1,λ2,λ3 be its barycentric coordinates. The polynomial ψK=27λ1λ2λ3, extended by zero outside K, has zero trace on ∂K, satisfies 0≤ψK≤1, and has ∫KψK=(9/20)∣K∣. Thus vK=RˉKψK is an admissible H01 test by [F5]. By affine scaling and [F3], ∥vK∥L2(K)≤C∥RˉK∥L2(K) and ∥∇vK∥L2(K)≤ChK−1∥RˉK∥L2(K). The residual identity has no edge term for this test, so RˉK∫KvK=a(e,vK)+∫K(RˉK−RK(U))vK. The left side is at least c∥RˉK∥L2(K)2, while the two terms on the right are bounded by C(1+∣b∣hK)hK−1∥∇e∥L2(K)∥RˉK∥L2(K) and C∥RK−RˉK∥L2(K)∥RˉK∥L2(K), respectively. If RˉK≠0, division and multiplication by hK give hK∥RˉK∥L2(K)≤C(1+∣b∣hK)∥∇e∥L2(K)+ChK∥RK−RˉK∥L2(K); if it is zero, the same bound for hK∥RK∥L2(K) follows from RK=RK−RˉK. Hence in all cases hK∥RK∥L2(K)≤C(1+∣b∣hK)∥∇e∥L2(K)+Cosc⁡K(U).

2.1A1F1F3F5step 1.2algebra

On an interior edge E=K+∩K− write ωE=K+∪K−, and let λi±,λj± be the barycentric coordinates of its endpoints on the two incident cells. Define ψE=4λi+λj+ on K+, ψE=4λi−λj− on K−, and zero outside their union. These traces agree on E, vanish on the other edges of the patch, and satisfy ∫EψE=(2/3)hE, ∥ψE∥L2(K+∪K−)≤ChE, and ∥∇ψE∥L2(K+∪K−)≤C by [F3]. The function ψE is an admissible H01 test by [F5]. Put J=JE(U), which is constant for P1 with A=I, and test [F1] with vE=JψE. All edge terms other than the one on E vanish. Its magnitude is (2/3)hEJ2. The cell terms are bounded by ChE∣J∣(∥RK+(U)∥2+∥RK−(U)∥2), and the form term by C(1+∣b∣hE)∣J∣∥∇e∥L2(K+∪K−). Use step 1.2, hE≍hK±, and the definitions of the oscillations to obtain hE∣J∣≤C(1+∣b∣hmax⁡)(∥∇e∥L2(K+∪K−)+osc⁡(U,K+∪K−)); the bound is trivial if J=0. Since hE1/2∥JE(U)∥L2(E)=hE∣J∣, summing with bounded patch overlap and the cell estimate of step 1.2 proves the local efficiency assertion.

2.2F1F3F4F5step 1.2algebra

Set d=U∗−U. For every original cell L in ω(M), use its fixed uniform-three-generation pattern from [F4]. Its P1 hat ϕL at the interior median midpoint is zero on ∂L. Exactly four of the eight equal-area leaves meet that midpoint, so ∫LϕL=4(∣L∣/8)/3=∣L∣/6. Reference scaling gives ∥ϕL∥L2(L)≤ChL and ∥∇ϕL∥L2(L)≤C. Extend by zero and prolong to T∗: containment of the fixed pattern makes this a fine P1 function even after arbitrary additional closure or refinement. For every fine test v∗, fine Galerkin orthogonality gives a(u−U,v∗)=a(d,v∗). Testing with v∗=RˉLϕL, where RˉL=ΠL0RL, yields the cell estimate by exactly the residual splitting and zero-mean remainder argument of step 1.2, now with ∫LϕL=∣L∣/6: hL∥RL(U)∥L2(L)≤C(1+∣b∣hmax⁡)∥∇d∥L2(L)+Cosc⁡L(U). The case RˉL=0 uses only the oscillation remainder, so no zero quantity is divided by. This bound is now available on every neighbor needed below.

3.1F1F3F4F5step 2.1step 2.2algebra∎

For each interior edge E incident to a cell of M, both original incident cells belong to ω(M). Define a common trace tent tE on E: it is zero at its two endpoints, one at its midpoint, and affine on each half. On each incident cell's fixed three-generation pattern, prescribe nodal values tE(z) at nodes on E and zero at every pattern node off E, then interpolate P1. In particular any quarter points on a reference edge have value 1/2, rather than zero. The traces from the two cells equal the same full tent even when their reference labels differ; all other original edge traces are zero. Thus the two pieces glue to a continuous function ψE supported on ωE, zero on its boundary, with ∫EψE=hE/2,∥ψE∥L2(ωE)≤ChE,∥∇ψE∥L2(ωE)≤C. Indeed each cell uses eight fixed-shape leaves, nodal values in [0,1], and affine scaling; shape regularity gives hL≍hE for the two cells. Prolong these reference functions to T∗, retaining their values, support, integrals and bounds; do not replace them by nodal hats on the possibly much finer actual mesh. For J=JE(U), test with JψE. The only original edge term is J2hE/2, so the residual identity and local form bound give hE∣J∣≤C(1+∣b∣hE)∥∇d∥L2(ωE)+ChE∑L⊂ωE∥RL(U)∥L2(L). For J=0 this is immediate. Applying step 2.2 on both incident cells yields the desired edge estimate in terms of correction energy and oscillation on ωE. Summing squared cell and edge estimates over M has bounded overlap: each triangle belongs to at most its own and its three neighbors' patches. This proves the marked estimate with precisely ω(M) on the right and constants independent of all extra refinement.

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Dorfler marking is cardinality-optimal up to mesh closure

Statement

Assume Countable Choice for the Sobolev and residual-estimator suppliers.

Assume b=0, f is constant on each initial cell, and T is a conforming descendant. Let eT and ηT be the exact P1 Galerkin energy error and residual estimator. Let T∗ be another conforming NVB descendant of T0 with exact Galerkin solution U∗. If eT∗≤λeT for some 0<λ<1, then the cells subdivided in the overlay T⊕T∗ form a Dörfler set with parameter θ∗=(1−λ2)/(ClocCeff)>0, where Cloc is the localized refinement constant and Ceff the global efficiency constant. Consequently the deterministic smallest-cardinality Dörfler set for any fixed 0<θE≤min⁡(1,θ∗) has cardinality at most #T∗−#T0.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, the symmetric Laplace problem, f piecewise constant on T0, conforming P1 Galerkin solutions on nested meshes, and the comparison error decrease.

[F1]

If f is P0 on T0, then its projection oscillation vanishes on every descendant; global efficiency and reliability give Ceff−1ηT2≤eT2≤CrelηT2 (Residual indicators and data oscillation for P1 AFEM, Residual reliability and local efficiency for P1 AFEM).

[F2]

The energy errors of nested symmetric Galerkin solutions satisfy Pythagorean orthogonality (Quasi-orthogonality for constant convection on a fine initial mesh).

[F3]

A nested refinement localizes the Galerkin correction to the estimator on the coarse cells it subdivides (Localized energy estimate for nested Galerkin solutions).

[F4]

The overlay is the smallest common conforming refinement and has the cardinality bound #(T⊕T∗)≤#T+#T∗−#T0 (Common NVB refinement and overlay cardinality).

Proof

1.1A1F1F2F3givenalgebra

Let T+=T⊕T∗ and let U,U∗,U+ be the exact Galerkin solutions. Best approximation on the overlay gives eT+≤eT∗≤λeT. By [F2], ∥∇(U+−U)∥22=eT2−eT+2≥(1−λ2)eT2. By [F3], this correction square is at most ClocηT(R)2, where R is the set of coarse cells subdivided in T+. By [F1], ηT2≤CeffeT2. Combining proves ηT(R)2≥θ∗ηT2. If eT=0, then the comparison condition and all indicators are zero and the empty set is Dörfler.

2.1F4step 1.1algebra∎

The bulk algorithm sorts nonnegative weights in decreasing order. Among all sets of a fixed size m, the first m sorted weights have maximal sum: replacing any omitted larger weight for a selected smaller one cannot decrease the sum, and repeating yields the prefix. Therefore the shortest prefix reaching threshold θEηT2 has minimum cardinality among all Dörfler sets. Since R is such a set whenever θE≤θ∗, ∣ME∣≤∣R∣. The overlay cardinality bound [F4] gives ∣R∣≤#T+−#T≤#T∗−#T0.

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Reduction of the P1 residual estimator after marked refinement

Statement

Assume Countable Choice, as in the residual and inverse-estimate suppliers.

Suppose the refinement call completes with a matching descendant T∗≥T and every cell in the Dörfler estimator set ME receives three generations of refinement, with exact Galerkin solutions U,U∗. For every ε>0, ηT∗(U∗)2≤(1+ε)ηT(U)2−12ηT(U,ME)2+Cε(1+∣b∣2hmax⁡2)∥∇(U∗−U)∥22. The constant depends only on ε and the uniform shape bound.

Facts & Assumptions

[A1]

Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice (ACω)).

Given: Countable Choice, the P1 residual estimator with A=I,c=0, the exact Galerkin solutions, a conforming three-generation refinement of the bulk set, and ε>0.

[F1]

Cell and edge residuals are RK(U)=f−b⋅∇U and the outward flux jumps; their estimator weights are hK2 and hE (Residual indicators and data oscillation for P1 AFEM).

[F2]

A marked parent is subdivided with child diameters at most half its diameter, and matching closure preserves the mesh family (Shape regularity and local reduction under 2D newest-vertex bisection, Termination and cumulative complexity of NVB conformity closure).

[F3]

Shape-regular affine P1 meshes satisfy a uniform inverse discrete-trace bound for jumps of piecewise gradients (Polynomial inverse and discrete trace inequalities, Shape regularity controls affine simplex geometry).

Proof

1.1A1F1F2givenalgebra

Write d=U∗−U. On a fine child K′⊂K, RK′(U∗)=RK(U)−b⋅∇d. Young's inequality gives hK′2∥RK′(U∗)∥22≤(1+ε)hK′2∥RK(U)∥22+(1+ε−1)∣b∣2hK′2∥∇d∥L2(K′)2. Unmarked cells retain the same old volume weight. On marked parents, [F2] makes the old residual part at most one quarter its old value. Summing, and charging closure-refined cells to their old parent, bounds the volume contribution by (1+ε) times the old volume sum minus 34 of its marked volume sum, plus Cε∣b∣2hmax⁡2∥∇d∥22.

2.1A1F1F2F3step 1.1algebra∎

On every split old edge, each subedge length is at most half the parent length and the sum of their lengths is the parent length; hence the sum of squared subedge lengths is at most one half the squared parent length. The old jump is constant along each parent edge, so its inherited contribution is reduced by at least one half whenever its marked cell is refined. On new interior edges within one old parent the old affine gradient has zero jump. The new jump is the old jump plus the jump of ∇d; Young's inequality and [F3] give a remainder at most Cε∥∇d∥22. Assign each old edge half to each incident cell as in the definition. Combining this with step 1.1, the marked cell and edge reductions are at least one half of ηT(U,ME)2; absorb the remaining nonnegative reduction into the left inequality to obtain the displayed bound.

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Linear contraction of AFEM energy error and oscillation

Statement

Assume the Axiom of Choice and Countable Choice for the weak elliptic existence suppliers used to instantiate either model branch.

Let (Tk,Uk) be generated by exact P1 Galerkin solves and the three-generation algorithm with θE,θO∈(0,1], and assume every per-call bisection budget is sufficient for a complete refinement. For the estimator and oscillation of Residual indicators and data oscillation for P1 AFEM, write ek=∥∇(u−Uk)∥2, ηk=η(Uk,Tk) and osc⁡k=osc⁡(Uk,Tk). On the symmetric branch b=0, no initial-mesh smallness is needed. On the constant-convection branch assume the uniform dual-pickup bound of Quasi-orthogonality for constant convection on a fine initial mesh and set μ=CDh0s∣b∣. Define κ=min⁡{12,θECeffCrel},ν={0,b=0,μ/(1−μ),b≠0. In the convection branch assume μ<1, so that ν is defined and the quasi-orthogonality estimate applies, and assume ν<κ. Then there are β>0 and 0<α<1, depending only on the displayed constants and marking parameters, such that ek+12+βosc⁡k+12≤α(ek2+βosc⁡k2).

Moreover, after possibly reducing a positive weight σ, there are β′>0 and 0<α′<1 such that ek+12+β′osc⁡k+12+σηk+12≤α′(ek2+β′osc⁡k2+σηk2). This second assertion records the residual-estimator reduction as part of the usual AFEM quasi-error. Constants and smallness hypotheses belong to the chosen marking and the stated dual-pickup bound.

Facts & Assumptions

[A1]

The Axiom of Choice and Countable Choice are assumed for the weak-solution suppliers and Sobolev spaces (The Axiom of Choice, The Axiom of Countable Choice (ACω)).

Given: The Axiom of Choice, Countable Choice, exact weak and Galerkin solutions, reliability and marked local efficiency, bulk estimator and oscillation sets, three-generation refinement, and in the convection case the stated dual-pickup bound.

[F1]

Reliability gives ek2≤Crelηk2, and marked local efficiency gives ηk(ME)2≤Ceff(∥∇(Uk+1−Uk)∥22+osc⁡k2) (Residual reliability and local efficiency for P1 AFEM).

[F2]

The energy error satisfies exact symmetric orthogonality for b=0 and the stated quasi-orthogonality inequality for constant b (Quasi-orthogonality for constant convection on a fine initial mesh).

[F3]

Data oscillation contracts by osc⁡k+12≤γOosc⁡k2, where γO=1−34θO<1 (Data oscillation reduction under three-generation refinement).

[F4]

The residual estimator satisfies the reduction inequality after marked refinement, with a correction term proportional to ∥∇(Uk+1−Uk)∥22 (Reduction of the P1 residual estimator after marked refinement).

[F5]

Under the stated choice assumptions, weak Dirichlet Poisson has a unique solution (Existence and uniqueness for the weak Dirichlet Poisson problem).

[F6]

Constant-convection weak Dirichlet Poisson has a unique weak solution under the same choice assumptions (Weak well-posedness for constant divergence-free convection).

[F7]

Under Countable Choice, every finite-dimensional conforming subspace has a unique exact Galerkin solution for the bounded coercive form (Céa quasi-optimality for coercive conforming Galerkin problems).

Proof

1.1A1F1F2F5F6F7givenalgebra

By [A1, F5] or [A1, F6], as appropriate to the chosen branch, the weak solution exists uniquely under the stated choice assumptions. By [F7], the finite-dimensional P1 Galerkin solution on each mesh also exists uniquely. Write dk=Uk+1−Uk. The completed algorithm refines every original edge neighbor of ME through three generations, so the marked-correction premise in [F1] holds, including its adjacent-cell tests. By [F1] and the Dörfler property, θEηk2≤ηk(ME)2≤Ceff(∥∇dk∥22+osc⁡k2),ηk2≥ek2/Crel. Thus ∥∇dk∥22≥κek2−osc⁡k2. By [F2], ek+12≤(1+ν)ek2−∥∇dk∥22, where ν=0 in the symmetric case and ν=μ/(1−μ) otherwise. Consequently ek+12≤(1−δ)ek2+osc⁡k2,δ=κ−ν>0.

2.1A1F3step 1.1algebra

Combine step 1.1 with [F3]: ek+12+βosc⁡k+12≤(1−δ)ek2+(1+βγO)osc⁡k2. Choose β>1/(1−γO). Then both coefficients 1−δ and γO+1/β are strictly less than one. Their maximum is a valid α<1, proving the first contraction.

3.1A1F2F3F4step 1.1algebra∎

Set ε=θE/4 in [F4]. Dörfler marking gives ηk+12≤ρEηk2+CE∥∇dk∥22,ρE=1+ε−12θE=1−14θE<1, where CE is finite. Also [F2] implies ∥∇dk∥22≤(1+ν)ek2. Choose σ>0 so σCE(1+ν)<δ/2. Adding σ times this estimator inequality to the error and oscillation bounds gives coefficients strictly below one on ek2 and ηk2. Choose β′ large enough that the coefficient on osc⁡k2, divided by β′, is below one; this is possible by γO<1. The maximum of the three resulting coefficients is α′<1, which proves the second inequality. The case of zero error or zero oscillation satisfies the same inequalities without division.

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Optimal P1 AFEM complexity for the Laplacian

Statement

Assume the Axiom of Choice and Countable Choice used by the weak Dirichlet Poisson existence supplier. Let Ω be a bounded polygon, T0 a compatible shape-regular 2D NVB mesh, and u∈H01(Ω) solve −Δu=f with f piecewise constant on T0. Run the exact P1 algorithm with three-generation refinement; assume each per-call budget suffices for every refinement through iteration k. Write Uk for the unique exact P1 Galerkin solution on Tk, estimator bulk parameter 0<θE≤min⁡(1,(1−λ2)/(ClocCeff)) for a fixed 0<λ<1, as in Dorfler marking is cardinality-optimal up to mesh closure, and any fixed oscillation parameter θO∈(0,1]. If u∈As from The P1 AFEM approximation class for 0<s≤12, then ∥∇(u−Uk)∥2≤C∣u∣As(1+#Tk−#T0)−s, where C depends on the initial mesh, marking parameters and estimator constants. This is an optimal-complexity theorem only for the Laplacian and P0 initial data.

Facts & Assumptions

[A1]

The Axiom of Choice and Countable Choice are used by the weak Dirichlet Poisson existence theorem (The Axiom of Choice, The Axiom of Countable Choice (ACω)).

Given: The Axiom of Choice, Countable Choice, the symmetric Laplace weak solution, P0 initial data, compatible 2D NVB meshes, the stated approximation-class bound, and exact Galerkin solutions.

[F1]

The AFEM energy and oscillation contract; here oscillation is identically zero, so the energy error contracts geometrically (Linear contraction of AFEM energy error and oscillation).

[F2]

A comparison mesh reducing energy error by a fixed factor yields a Dörfler set no larger than its added-cell count (Dorfler marking is cardinality-optimal up to mesh closure).

[F3]

The sum of added cells over the adaptive sequence is bounded by a constant times the sum of marked-cell counts (Termination and cumulative complexity of NVB conformity closure).

[F4]

The approximation seminorm bounds the best error over every finite mesh budget (The P1 AFEM approximation class).

[F5]

Under the Axiom of Choice and Countable Choice, weak Dirichlet Poisson on a bounded polygon has a unique H01 solution for f∈L2 (Existence and uniqueness for the weak Dirichlet Poisson problem).

[F6]

Exact conforming Galerkin solutions satisfy a(u−UT,vT)=0 for every vT∈V(T) (Galerkin orthogonality for conforming approximations).

Proof

1.1A1F1F5givenalgebra

By [F5] the weak solution exists uniquely under the stated choice assumptions. Since f is piecewise constant on T0, every descendant cell has osc⁡K=0. By [F1] there are 0<α<1 and C0 such that ek+12≤αek2; hence, with q=α<1, ej≤qj−kek for j≥k. If ∣u∣As=0, then E0(u)=0 and all nested Galerkin errors vanish. Assume ∣u∣As>0.

1.2F4F6givenchoosealgebra

For each k with ek>0, put ϵk=λek for the fixed λ∈(0,1) in the statement. By [F4], if Nk=⌈(2∣u∣As/ϵk)1/s⌉, then ENk(u)≤ϵk/2: this follows directly from (Nk+1)sENk≤∣u∣As and Nk+1≥(2∣u∣As/ϵk)1/s. By the definition of an infimum there is a conforming comparison mesh with at most Nk added cells and best-approximation error at most ϵk. For a symmetric Galerkin solution, [F6] and expansion of ∥∇(u−vT)∥22=∥∇(u−UT)∥22+∥∇(UT−vT)∥22 show its exact Galerkin error is the best error, so this comparison mesh reduces the Galerkin error to at most ϵk. If ek=0, the target conclusion is already true.

2.1F2F3F4F6step 1.2algebra

The comparison mesh from step 1.2 reduces the error by the factor λ. By [F2], the marked set therefore satisfies #Mk≤Nk≤1+(2/λ)1/s∣u∣As1/sek−1/s. Here MO=∅ because the initial P0 data have zero oscillation, so Mk=ME,k. The actual refinement request is its edge-neighbor set Qk, whose cardinality is at most 4#Mk; [F3] already absorbs this factor in Ccl. Summing and applying [F3] gives #Tn−#T0≤C∑k=0n−1#Mk≤C′ ∣u∣As1/s∑k=0n−1ek−1/s. The additive 1 is absorbed into the right side because ek≤e0=E(T0;u)≤∣u∣As by [F4] at N=0.

3.1F4step 1.1step 2.1algebra∎

Geometric contraction from step 1.1 implies ek−1/s≤q(n−k)/sen−1/s for k<n. Thus the sum in step 2.1 is at most en−1/s∑j≥1qj/s, a finite geometric series. Rearranging yields en≤C′′∣u∣As(#Tn−#T0)−s whenever the added-cell count is positive. If it is zero, [F4] at N=0 gives en=e0≤∣u∣As. Enlarging C′′ replaces the count by 1+#Tn−#T0.

5 · Examples, counterexamples and false statements

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