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.
Adaptive finite-element methods
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Absolute Continuity and the Sharp Fundamental Theorem of Calculus
- Areas of Elementary Plane Figures
- Banach Valued Integration and the Radon Nikodym Property
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Bounded Variation and the Riemann–Stieltjes Integral
- Céa and Aubin–Nitsche error estimates
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Complex Norms and Realification
- Complex Subspace Realification
- Complexification, Realification and Real Structures
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Convexity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Differentiation of Monotone Functions and the Vitali Covering Theorem
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces Adjoint Operators and Annihilators
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Euclidean Surface Measure, Divergence, and Green Identities
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Dimensional Normed Spaces and Riesz Lemma
- Finite-element meshes and interpolation
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Hausdorff via the Diagonal
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lax--Milgram and Weak Elliptic Solutions
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Outer Measure and the Caratheodory Extension Theorem
- Pointwise Extended-Real Function Products
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Radon Measures and the Riesz Markov Kakutani Theorem
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Schwartz Space and the Plancherel Theorem
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Smooth Approximation and Sobolev Extension
- Smooth Manifolds and Smooth Maps
- Smooth Partitions of Unity and Exhaustions
- Sobolev Poincare and Morrey Inequalities
- Sobolev Traces and Zero Boundary Values
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tangent Cotangent and the Differential
- The Analytic Hahn Banach Theorem
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Exponential Function
- The Inverse and Implicit Function Theorems
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Radon Nikodym Theorem and Lebesgue Decomposition
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Weak Derivatives and Sobolev Spaces
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 . 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
Weak well-posedness for constant divergence-free convection
Statement
Assume Countable Choice as in the cited Sobolev and Lax–Milgram suppliers. Let be a bounded polygon, constant, and . Here is the zero-boundary closure of Zero-boundary Sobolev space as a norm closure. There is a unique real-valued satisfying No regularity is asserted.
Facts & Assumptions
Countable Choice is assumed for the cited Sobolev, Poincare and Lax–Milgram interfaces (The Axiom of Countable Choice ()).
Given: Countable Choice, a bounded polygon , constant , , and the real Hilbert space .
On a domain bounded in one direction, for every ; the supplier assumes Countable Choice (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction, The Axiom of Countable Choice ()).
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 ()).
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 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
A bounded polygon lies in a finite-width slab, so [F1] applies. Define . Cauchy–Schwarz and [F1] give ; also is linear and . The gradient norm is complete on by [F3], since Poincare makes it equivalent to the complete inherited norm.
For , by compact support and constant . Approximation in extends this identity to every , because is continuous in the norm and compactly supported smooth functions are dense by [F3]. Hence , so is coercive with constant in the gradient norm.
Apply [F2] to the real Hilbert space equipped with inner product , the bounded form from step 1.1, and its coercivity from step 1.2. This gives a unique satisfying for all . 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.
A local moment interpolant for conforming P1 meshes
Definition
Assume Countable Choice for the convention of The Axiom of Countable Choice ().
Fix a finite conforming triangular mesh . For each interior vertex , choose the incident triangle with least fixed mesh index and denote it . On the reference triangle , let be its barycentric coordinates. The Gram matrix is positive definite because for every nonzero . Thus there are unique dual affine polynomials with . Pull them to by the affine map using the normalized measure so for its three local nodal hats.
For set at interior vertices and at boundary vertices. Define where 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.
Compatible 2D newest-vertex-bisection meshes
Definition
A compatible labeled initial mesh is a finite matching affine simplicial triangulation of a polygon in as in Matching affine simplicial meshes and shape regularity, equipped with labels on its edges such that each triangle has one edge labeled and two labeled , 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 , its three edge labels, in any order, are . The unique edge labeled is its reference edge.
To bisect , join the midpoint of its reference edge to the opposite vertex. The two resulting triangles have generation . In each child, the two new half-edges and the bisector receive label ; the one inherited nonreference edge retains label 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 consists of the matching conforming leaf triangulations generated by these compatible bisections. A refinement means every cell of lies in a cell of .
For deterministic operational ordering, fix a finite starting mesh in this family and a total order of its cells. Enumerate those operational roots as in that order; this starting mesh may already be a geometric descendant of , and operational numbering does not reset its generations or edge labels. Give root identifier and order its three vertices lexicographically by their two real coordinates. If a parent has identifier , with a finite binary word, let be the earlier endpoint of its labeled reference edge in its stored vertex list, let be the other endpoint, let be the opposite vertex, and let . Its children with vertex sets and receive identifiers and , respectively. Each child's stored vertex list is the parent list restricted to its two retained vertices, in their previous order, followed by . 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 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.
Residual indicators and data oscillation for P1 AFEM
Definition
Assume Countable Choice for the and Sobolev conventions of The Axiom of Countable Choice ().
All functions and data are real-valued. Let be a bounded polygon and let be a finite conforming matching triangulation by nondegenerate affine triangles, with maximum shape-regularity constant . Write and . Let be the continuous, piecewise-affine zero-boundary subspace of Broken and conforming polynomial spaces on a matching mesh, which lies in 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 The weak form is for every . The case is the symmetric Laplace model. Given , its cell residual is ; this is because on each cell. For an interior edge define the outward flux jump where are the unit outward normals. Set and for . The factor assigns each interior-edge contribution once globally. Let be the projection onto constants. The cell data oscillation is Since is constant on , this oscillation equals .
For a separate definitional interface, consider the symmetric diffusion model , where 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 is , and its outward conormal-flux jump is the sum of from the two incident cells. Let be the projection onto constants. The projected edge term records nonconstant conormal flux. The reliability, contraction, and complexity results authored here concern only; this extension supplies notation and no coefficient-dependent theorem.
Prerequisite interface
The matching affine mesh and continuous broken-polynomial conventions are those of Matching affine simplicial meshes and shape regularity and Broken and conforming polynomial spaces on a matching mesh. The proof of the weak representation uses Sobolev face traces and Gauss–Green on a reference simplex and Interior facet orientations cancel in a matching mesh.
Uniform Poincare inequalities on vertex and cell patches
Statement
Assume Countable Choice, as in the reference-simplex trace and Poincare suppliers.
Let be a conforming shape-regular triangular mesh. For an interior vertex , let be the union of its incident triangles; for a boundary vertex use the same patch. There is a constant depending only on the shape-regularity bound such that, at an interior vertex, every satisfies where is the patch mean and . On a boundary vertex patch, every satisfies For a cell , define , where is its set of three vertices. If does not meet , the corresponding mean-zero estimate holds on with scale ; if meets and , then
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, a conforming triangular mesh with shape-regularity bound , an interior or boundary vertex , and respectively or .
On a reference simplex, mean-zero functions satisfy Poincaré's inequality and the trace is bounded by the 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).
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
Scaling [F1] to each triangle gives and for every edge . Shape regularity makes comparable to . If share , their traces of agree, so Using for cells in one shape-regular vertex star bounds the difference of neighboring means by the two gradient norms.
The star has at most cells, and its dual edge graph is connected. Join each cell to a fixed cell by a graph path of length at most and apply step 1.1 along that path. The cell Poincaré bound from step 1.1 then gives . Since , replacing by the patch mean proves the interior estimate.
For a boundary vertex patch choose one boundary edge . By the definition of as the -closure of compactly supported smooth functions, and the continuous local trace bound in [F1], the trace of is zero on . The trace inequality in step 1.1 therefore gives for the incident cell . The same bounded-path comparison of cell means from step 2.1 controls every cell mean in the star by . Summing the cell Poincaré bounds proves the boundary estimate.
For a cell patch , the three vertex stars are edge-connected because they all contain , 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 . The mean-zero estimate follows by applying the cell-mean comparison of step 2.1 over this connected finite graph. If meets the boundary, 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.
Dorfler marking and conforming newest-vertex refinement
Definition
Input: a finite labeled conforming mesh , exact nonnegative arrays and , where is the cell estimator contribution and the cell data-oscillation contribution, bulk-fraction parameters , a per-call total bisection budget , 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 and , sort by decreasing and then increasing identifier. If , return the empty set. Otherwise return the shortest initial segment whose sum is at least . Thus these parameters are fractions of the squared contributions (the square-root convention for the usual estimator-norm parameter). Call the resulting sets and set .
Before modifying the mesh, form the original edge-neighbor request set Thus and their union remain the bulk marks; is the larger refinement request, with and because a triangle has at most three edge neighbors. For , also . Set a remaining-generation flag on each cell in and 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 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 when and otherwise . Thus conformity splits may propagate without scheduling extra uniform generations, while every originally requested cell in 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 . 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 , 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 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.
The P1 AFEM approximation class
Definition
Assume Countable Choice. The space is the closure of in the norm, as in Zero-boundary Sobolev space as a norm closure and The Axiom of Countable Choice ().
Fix a compatible initial triangulation , its 2D NVB family from Compatible 2D newest-vertex-bisection meshes, and a weak solution of the symmetric , model in Residual indicators and data oscillation for P1 AFEM. For a conforming refinement , let be its continuous P1 zero-boundary space and define For , the approximation seminorm and class are The infimum is over a nonempty finite-budget set because 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 .
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.
Quasi-orthogonality for constant convection on a fine initial mesh
Statement
Assume Countable Choice, as in the zero-boundary Sobolev convention.
Let be nested conforming meshes and let be exact P1 Galerkin solutions for the constant-convection model of Residual indicators and data oscillation for P1 AFEM. Write and . For , For constant , assume the explicit dual-pickup bound for the nested sequence, with , where , and put . Then The dual-pickup bound is an additional hypothesis. It is not asserted for every polygon or mesh.
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, nested conforming P1 spaces, exact Galerkin solutions, constant , and in the nonsymmetric case the stated dual-pickup bound.
Galerkin orthogonality says for every ; nestedness puts in the fine space (Galerkin orthogonality for conforming approximations).
is the closure of compactly supported smooth functions in ; 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
If , [F1] with gives . Since , expanding the squared norm yields . Rearrangement is the symmetric identity.
For constant , [F1] gives . By [F2], . Expanding therefore gives The sign in this identity follows directly from the preceding orthogonality equation.
By the assumed dual-pickup estimate and Cauchy–Schwarz, . Using this in step 1.2 gives . Divide by to obtain the stated estimate.
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 with reference edge . are the midpoints of the three original sides; is the midpoint of median and is interior; are the midpoints of . The eight leaves and their coordinates are verified in proof step 2.1. The dashed original edge is the reference edge. The picture fixes the point conventions only; no proof relies on it.
Facts & Assumptions
Given: A finite shape-regular conforming triangular initial mesh with compatible edge labels as in Compatible 2D newest-vertex-bisection meshes.
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
Write the parent vertices as , with reference edge , midpoint , and squared side lengths , , . The two first children have edge-length squares and , where by expanding the squared norm. The four labeled types have squared edge lists , , , and . In type 1 the reference side has square , and the new median square is ; its children therefore have side lists and , which are a quarter-scale type 0 and type 3. The type 2 calculation interchanges . In type 3 the reference side has square , and its median square is ; 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.
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.
After the first generation the midpoint of is present. The second generation bisects and , adding their midpoints and . The four second-generation triangles have reference edges on the segments ; the third generation bisects those segments, in particular , adding its midpoint in the interior of . The eight leaves have vertex triples , where and . Subtracting these vertex coordinates shows that each leaf side is an original side divided by , the median divided by , or the reference side divided by . Since lies on , convexity of the norm gives . Thus every leaf side, and hence every leaf diameter, is at most half the parent diameter.
Element and edge residual representation for P1 Galerkin errors
Statement
Assume Countable Choice, as in the Sobolev and simplex trace suppliers.
Let be a matching triangular mesh, , and solve the weak model from Residual indicators and data oscillation for P1 AFEM. For every ,
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, the weak equation, matching affine triangles, continuous P1 function , and .
On an affine simplex, Green's identity holds for the polynomial vector field 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).
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
For smooth compactly supported , integrate on every cell using [F1]. Since is affine, . The sum of boundary integrals on each interior edge is , and boundary-edge terms vanish because is compactly supported.
The weak residual is . Substituting step 1.1 gives cell integrands and the negative of the summed outward flux jumps. This is the displayed formula for smooth compactly supported .
Smooth compactly supported functions are dense in by its definition. Every term in the identity is continuous in the norm: volume terms use , and edge terms use the trace inequality from [F1] on the finite mesh. Passing to the limit extends step 2.1 to all .
Local approximation and reproduction of the P1 moment interpolant
Statement
Assume Countable Choice, as in the Sobolev, affine-scaling and trace suppliers.
Let be a shape-regular conforming triangular mesh and let be the moment interpolant from A local moment interpolant for conforming P1 meshes. For each cell , let be the union of vertex stars of its vertices. There is a constant depending only on shape regularity such that for every , and, for every interior edge , where is the other incident cell. The operator maps into and reproduces every member of .
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, a shape-regular conforming triangular mesh, , 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.
On each reference triangle, the three barycentric coordinates form a basis of 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).
Matching continuous piecewise-affine functions belong to , and a continuous piecewise-affine function with zero boundary nodal values belongs to (Continuous matching piecewise polynomials belong to W1p, Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare).
Vertex stars have bounded overlap and uniformly bounded valence on a shape-regular conforming mesh (Uniform Poincare inequalities on vertex and cell patches).
Proof
The definition gives finitely many coefficients, each an integral against a bounded affine polynomial, hence a linear functional on ; the resulting finite sum is continuous piecewise affine. Its boundary nodal coefficients are zero, so [F2] places it in . If , then on the selected cell its affine restriction is a linear combination of the three local hats. The dual moment identities recover its nodal coefficient at , so at every interior vertex; at boundary vertices both the coefficient and the P1 trace value are zero. Therefore .
For a cell not meeting the boundary, set ; for a boundary cell set . The patch Poincaré estimate gives . For each interior vertex of , put ; this equality follows from the dual identities, which give . These are local integrals of an function, with no application of to . The scaled dual bound gives , since and its diameter is comparable to . At a boundary vertex of , necessarily and the corresponding coefficient difference is zero. The three barycentric hats on sum to one, so . Each hat has norm at most and gradient norm at most . Thus and . The patch inequality and prove the first two bounds. This argument uses only that each selected is incident to , so its constants are uniform over all such selections.
Apply the scaled trace inequality to on . The first two bounds from step 1.2 control the cell term and its gradient; the neighboring patch gives the same estimates on . Since and are comparable by shape regularity, this yields the asserted edge bound.
Common NVB refinement and overlay cardinality
Statement
For two compatible conforming NVB descendants of the same initial mesh , the union of their bisection forests defines a smallest common conforming overlay and
Facts & Assumptions
Given: A fixed compatible labeled initial triangulation and two of its finite conforming bisection forests.
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
Let be the finite binary forest for . Their node union 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 consequently form a matching conforming triangulation refining both and . Any common refinement must contain every node split in either forest, so it contains and refines its leaf partition. Thus this is the smallest common conforming overlay.
For each initial root, a finite full binary tree with internal nodes has leaves; induction on proves this because splitting one leaf increases the leaf count by one. The internal nodes of are the union of the internal nodes of , so Summing the leaf identity over the roots gives and the same identity for the overlay. Substitution proves the inequality.
Data oscillation reduction under three-generation refinement
Statement
Assume Countable Choice for the projection convention.
Suppose the three-generation marked refinement call completes and returns , and let . For a Dörfler set with parameter ,
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, , nested matching cells, P0 projections, and a three-generation refinement of every .
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).
The Dörfler set satisfies by its construction (Dorfler marking and conforming newest-vertex refinement).
Proof
For each parent , let range over its descendants in , including if it is unrefined. Nestedness of the piecewise-constant spaces gives Indeed, the childwise projection space contains the parent constant space, and the orthogonal projection minimizes squared error. If , the completed call supplies three generations, so [F1] gives and the sum of descendant oscillations is at most one quarter of the parent oscillation. For every other parent, containment gives , so its descendant oscillations sum to at most its original contribution. An unrefined cell retains its contribution exactly.
Summing step 1.1 over refined parents gives Apply the bulk inequality [F2] to obtain the stated . If all oscillations vanish, both sides are zero and the same inequality holds.
Localized energy estimate for nested Galerkin solutions
Statement
Assume Countable Choice, as in the Sobolev interpolation suppliers.
Let be conforming P1 meshes with exact Galerkin solutions . Let and let be the union of the vertex stars of cells in . Then where depends on shape regularity, , and the local interpolant constants.
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, a nested matching refinement, exact conforming P1 Galerkin solutions, and the constant-convection model.
The coarse residual pairs the weak error with any function as the cell residual sum minus the outward flux jump sum (Element and edge residual representation for P1 Galerkin errors).
The local moment interpolant is P1-reproducing and satisfies local volume, gradient and edge estimates (Local approximation and reproduction of the P1 moment interpolant).
Galerkin orthogonality holds on both nested conforming spaces (Galerkin orthogonality for conforming approximations).
Proof
Define an auxiliary coarse moment map for this nested pair. At each interior vertex , choose the least-index incident coarse cell if one exists, otherwise the original selected cell , and use its dual affine moment ; at boundary vertices use zero. Set . The same conforming zero-boundary membership argument as in [F2] applies. Its bounds are uniform: on a cell use the patch mean when misses the boundary and otherwise. Then for interior vertices, while boundary coefficient differences are zero. Because and , the scaled dual bound gives . The hat bounds and patch Poincaré argument in the proof of [F2] therefore give and . Applying the same scaled trace inequality as in [F2] gives its edge bound as well. All these operations have input ; shifted functions enter only the local integrals.
Put . The fine Galerkin equation and coarse equation imply and . Since is constant and , , so . Also because and fine orthogonality kills the latter term paired with . Hence .
If , then is affine on . At every interior vertex of , the selected is also unchanged, so is affine and its dual moment equals the common nodal value ; boundary coefficients equal . Consequently on every unchanged cell. The trace of also vanishes on every edge incident to an unchanged cell. Thus [F1] applied to step 2.1 contains only volume residuals on and interior edges with both incident cells in . Use the volume and edge estimates proved in step 1.1. The surviving squared residual weights are bounded by , 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 , giving . If this gradient norm is zero the claim is immediate; otherwise divide by it and square.
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 , with three uniform generations requested on each cell of , there is a constant depending only on the initial mesh such that For the algorithm Dorfler marking and conforming newest-vertex refinement, keep as the bulk-marked set and use its original edge-neighbor request set . Then , so with , 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 , bulk sets when using patch expansion, and the recursive closure rule of Dorfler marking and conforming newest-vertex refinement.
In every descendant, edge labels have the generation pattern , the reference edge has label , and bisection uses midpoint subdivision (Compatible 2D newest-vertex-bisection meshes).
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
For a current cell , follow its interior reference-edge neighbor. The common label is ; by [F1] the neighbor either has the same generation, giving a compatibly divisible pair, or has generation . 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 . These are children or grandchildren of a chain cell ; for a coarser chain cell , so their generations are at most . The terminal partner and 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.
Let denote generation. Each bisection halves area, and [F2] gives constants depending only on the finitely many initial shapes such that and . 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 upward is at most with . Every created cell is a child of or its terminal same-generation partner, or a child or grandchild of a strictly coarser chain cell. Step 1.1 therefore gives . For a created cell within an original chain cell , the portion of the chain between and has its lowest generation ; summing its diameters gives with . The chain is finite by the integer generation drop, and these estimates supply the geometric radius used below.
First consider one-generation requests in a finite sequence and let be the union of all requested cells. For a final cell and marked cell define a nonnegative allocation where for , for , , , and , with from step 2.1. The series for is geometric with ratio , and because tends to infinity.
Fix with generation . At a fixed generation , cells with nonzero allocation lie in a ball of radius about . Each has area at least by step 2.1, while that ball enlarged by one cell diameter has area at most . Since cell interiors are disjoint, their number is at most a constant independent of , and the final level. Summing weights over generations therefore gives
Fix a new cell 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 ending at an initial cell. Step 2.1 gives and, for each consecutive pair in the sequence, . Let be the first index with . The prefix whose links join to is ; each of its generations is for some . The triangle inequality for set distances includes the diameters of the intervening cells. Steps 2.1 and the diameter bound control the sum by times the corresponding generation sum; leaves strict slack. Consequently, if this prefix has at most cells at every generation , then Thus the terminal requested cell lies in the allocation radius and contributes . Otherwise let be the first prefix with more than cells at some generation . Every earlier link prefix satisfies the displayed distance bound. If , since is new and , at least one other cell of that generation is a marked cell and contributes . If , all cells of that generation in the prefix are marked; each lies within the allocation radius and contributes . In this case their total is greater than . Hence every new cell receives at least allocation.
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 For three requested generations, view each parent in as successive one-generation requests. There are at most virtual requests at stage , even if closure performs some requested splits before their scheduled turn. The total is at most , giving . For the algorithm, every original triangle has at most three edge neighbors, so ; hence 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.
Residual reliability and local efficiency for P1 AFEM
Statement
Assume Countable Choice, as in the Sobolev trace and inverse-estimate suppliers.
Let be a conforming shape-regular triangular mesh, let solve the model of Residual indicators and data oscillation for P1 AFEM, and let be its exact P1 Galerkin solution. There are constants depending only on the shape bound and such that and for every , where is the union of and its edge neighbors. If contains the uniform three-generation subdivision of every cell in the original edge-neighbor patch of (in particular, every complete call of Dorfler marking and conforming newest-vertex refinement has this property) and is the exact fine Galerkin solution, then with the union of edge-neighbor patches of marked cells. All constants are independent of the refinement level.
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
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.
The error pairs with an arbitrary test function as the sum of cell residuals and negative outward flux jumps (Element and edge residual representation for P1 Galerkin errors).
The moment interpolant has local , 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).
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).
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).
Continuous matching piecewise polynomials with zero boundary trace belong to (Continuous matching piecewise polynomials belong to W1p, Zero-boundary conforming polynomials lie in W0 1p and satisfy Poincare).
Proof
Put and write . By the exact Galerkin equation, for every ; subtracting from the weak equation gives . For , constancy of gives . The map is continuous in , so density extends this identity to all . Hence and, since , . Apply [F1] to . Cauchy–Schwarz, the cell and edge interpolation bounds [F2], and finite overlap of vertex patches give If reliability is immediate; otherwise divide by it and square. This proves the global upper bound.
For each cell let , and let be its barycentric coordinates. The polynomial , extended by zero outside , has zero trace on , satisfies , and has . Thus is an admissible test by [F5]. By affine scaling and [F3], and . The residual identity has no edge term for this test, so . The left side is at least , while the two terms on the right are bounded by and , respectively. If , division and multiplication by give ; if it is zero, the same bound for follows from . Hence in all cases .
On an interior edge write , and let be the barycentric coordinates of its endpoints on the two incident cells. Define on , on , and zero outside their union. These traces agree on , vanish on the other edges of the patch, and satisfy , , and by [F3]. The function is an admissible test by [F5]. Put , which is constant for P1 with , and test [F1] with . All edge terms other than the one on vanish. Its magnitude is . The cell terms are bounded by , and the form term by . Use step 1.2, , and the definitions of the oscillations to obtain ; the bound is trivial if . Since , summing with bounded patch overlap and the cell estimate of step 1.2 proves the local efficiency assertion.
Set . For every original cell in , use its fixed uniform-three-generation pattern from [F4]. Its P1 hat at the interior median midpoint is zero on . Exactly four of the eight equal-area leaves meet that midpoint, so . Reference scaling gives and . Extend by zero and prolong to : containment of the fixed pattern makes this a fine P1 function even after arbitrary additional closure or refinement. For every fine test , fine Galerkin orthogonality gives . Testing with , where , yields the cell estimate by exactly the residual splitting and zero-mean remainder argument of step 1.2, now with : The case uses only the oscillation remainder, so no zero quantity is divided by. This bound is now available on every neighbor needed below.
For each interior edge incident to a cell of , both original incident cells belong to . Define a common trace tent on : 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 at nodes on and zero at every pattern node off , then interpolate P1. In particular any quarter points on a reference edge have value , 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 supported on , zero on its boundary, with Indeed each cell uses eight fixed-shape leaves, nodal values in , and affine scaling; shape regularity gives for the two cells. Prolong these reference functions to , retaining their values, support, integrals and bounds; do not replace them by nodal hats on the possibly much finer actual mesh. For , test with . The only original edge term is , so the residual identity and local form bound give For this is immediate. Applying step 2.2 on both incident cells yields the desired edge estimate in terms of correction energy and oscillation on . Summing squared cell and edge estimates over has bounded overlap: each triangle belongs to at most its own and its three neighbors' patches. This proves the marked estimate with precisely on the right and constants independent of all extra refinement.
Dorfler marking is cardinality-optimal up to mesh closure
Statement
Assume Countable Choice for the Sobolev and residual-estimator suppliers.
Assume , is constant on each initial cell, and is a conforming descendant. Let and be the exact P1 Galerkin energy error and residual estimator. Let be another conforming NVB descendant of with exact Galerkin solution . If for some , then the cells subdivided in the overlay form a Dörfler set with parameter where is the localized refinement constant and the global efficiency constant. Consequently the deterministic smallest-cardinality Dörfler set for any fixed has cardinality at most .
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, the symmetric Laplace problem, piecewise constant on , conforming P1 Galerkin solutions on nested meshes, and the comparison error decrease.
If is P0 on , then its projection oscillation vanishes on every descendant; global efficiency and reliability give (Residual indicators and data oscillation for P1 AFEM, Residual reliability and local efficiency for P1 AFEM).
The energy errors of nested symmetric Galerkin solutions satisfy Pythagorean orthogonality (Quasi-orthogonality for constant convection on a fine initial mesh).
A nested refinement localizes the Galerkin correction to the estimator on the coarse cells it subdivides (Localized energy estimate for nested Galerkin solutions).
The overlay is the smallest common conforming refinement and has the cardinality bound (Common NVB refinement and overlay cardinality).
Proof
Let and let be the exact Galerkin solutions. Best approximation on the overlay gives . By [F2], By [F3], this correction square is at most , where is the set of coarse cells subdivided in . By [F1], . Combining proves . If , then the comparison condition and all indicators are zero and the empty set is Dörfler.
The bulk algorithm sorts nonnegative weights in decreasing order. Among all sets of a fixed size , the first 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 has minimum cardinality among all Dörfler sets. Since is such a set whenever , . The overlay cardinality bound [F4] gives .
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 and every cell in the Dörfler estimator set receives three generations of refinement, with exact Galerkin solutions . For every , The constant depends only on and the uniform shape bound.
Facts & Assumptions
Countable Choice is assumed in the cited Sobolev and reference-simplex suppliers (The Axiom of Countable Choice ()).
Given: Countable Choice, the P1 residual estimator with , the exact Galerkin solutions, a conforming three-generation refinement of the bulk set, and .
Cell and edge residuals are and the outward flux jumps; their estimator weights are and (Residual indicators and data oscillation for P1 AFEM).
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).
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
Write . On a fine child , . Young's inequality gives 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 times the old volume sum minus of its marked volume sum, plus .
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 ; Young's inequality and [F3] give a remainder at most . 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 ; absorb the remaining nonnegative reduction into the left inequality to obtain the displayed bound.
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 be generated by exact P1 Galerkin solves and the three-generation algorithm with , 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 , and . On the symmetric branch , 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 . Define In the convection branch assume , so that is defined and the quasi-orthogonality estimate applies, and assume . Then there are and , depending only on the displayed constants and marking parameters, such that
Moreover, after possibly reducing a positive weight , there are and such that 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
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 ()).
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.
Reliability gives , and marked local efficiency gives (Residual reliability and local efficiency for P1 AFEM).
The energy error satisfies exact symmetric orthogonality for and the stated quasi-orthogonality inequality for constant (Quasi-orthogonality for constant convection on a fine initial mesh).
Data oscillation contracts by , where (Data oscillation reduction under three-generation refinement).
The residual estimator satisfies the reduction inequality after marked refinement, with a correction term proportional to (Reduction of the P1 residual estimator after marked refinement).
Under the stated choice assumptions, weak Dirichlet Poisson has a unique solution (Existence and uniqueness for the weak Dirichlet Poisson problem).
Constant-convection weak Dirichlet Poisson has a unique weak solution under the same choice assumptions (Weak well-posedness for constant divergence-free convection).
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
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 . The completed algorithm refines every original edge neighbor of through three generations, so the marked-correction premise in [F1] holds, including its adjacent-cell tests. By [F1] and the Dörfler property, Thus . By [F2], , where in the symmetric case and otherwise. Consequently
Combine step 1.1 with [F3]: Choose . Then both coefficients and are strictly less than one. Their maximum is a valid , proving the first contraction.
Set in [F4]. Dörfler marking gives where is finite. Also [F2] implies . Choose so . Adding times this estimator inequality to the error and oscillation bounds gives coefficients strictly below one on and . Choose large enough that the coefficient on , divided by , is below one; this is possible by . The maximum of the three resulting coefficients is , which proves the second inequality. The case of zero error or zero oscillation satisfies the same inequalities without division.
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 be a bounded polygon, a compatible shape-regular 2D NVB mesh, and solve with piecewise constant on . Run the exact P1 algorithm with three-generation refinement; assume each per-call budget suffices for every refinement through iteration . Write for the unique exact P1 Galerkin solution on , estimator bulk parameter for a fixed , as in Dorfler marking is cardinality-optimal up to mesh closure, and any fixed oscillation parameter . If from The P1 AFEM approximation class for , then where 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
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 ()).
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.
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).
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).
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).
The approximation seminorm bounds the best error over every finite mesh budget (The P1 AFEM approximation class).
Under the Axiom of Choice and Countable Choice, weak Dirichlet Poisson on a bounded polygon has a unique solution for (Existence and uniqueness for the weak Dirichlet Poisson problem).
Exact conforming Galerkin solutions satisfy for every (Galerkin orthogonality for conforming approximations).
Proof
By [F5] the weak solution exists uniquely under the stated choice assumptions. Since is piecewise constant on , every descendant cell has . By [F1] there are and such that ; hence, with , for . If , then and all nested Galerkin errors vanish. Assume .
For each with , put for the fixed in the statement. By [F4], if , then : this follows directly from and . By the definition of an infimum there is a conforming comparison mesh with at most added cells and best-approximation error at most . For a symmetric Galerkin solution, [F6] and expansion of show its exact Galerkin error is the best error, so this comparison mesh reduces the Galerkin error to at most . If , the target conclusion is already true.
The comparison mesh from step 1.2 reduces the error by the factor . By [F2], the marked set therefore satisfies Here because the initial P0 data have zero oscillation, so . The actual refinement request is its edge-neighbor set , whose cardinality is at most ; [F3] already absorbs this factor in . Summing and applying [F3] gives The additive is absorbed into the right side because by [F4] at .
Geometric contraction from step 1.1 implies for . Thus the sum in step 2.1 is at most , a finite geometric series. Rearranging yields whenever the added-cell count is positive. If it is zero, [F4] at gives . Enlarging replaces the count by .
5 · Examples, counterexamples and false statements
None yet.
Sources
- Ricardo H. Nochetto, Adaptive Finite Element Methods, Lecture 3
- Cascón, Kreuzer, Nochetto & Siebert, Quasi-optimal convergence rate for an AFEM
- Bonito, Canuto, Nochetto & Veeser, Adaptive Finite Element Methods (2024)
- Ricardo H. Nochetto, Adaptive Finite Element Methods, Lecture 1
- Ricardo H. Nochetto, Adaptive Finite Element Methods, Lecture 2
- Ricardo H. Nochetto, Adaptive Finite Element Methods, Lecture 4