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Overlapping Schwarz and stable subspace decompositions — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Absolute Values Completions and P Adic Numbers
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Conjugate Gradients, MINRES and Preconditioning
- 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
- Decomposition Inertia and Frobenius
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Direct Matrix Factorisations: LU, Cholesky and QR
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- 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
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- 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 finite elements and Stokes stability
- 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
- Multigrid methods and complexity
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Overlapping Schwarz and stable subspace decompositions
- 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
- 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
- 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
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tangent Cotangent and the Differential
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- 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 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 examples compute the exact condition number of one-level point-patch Schwarz on a uniform 1D Poisson mesh, show a two-level coarse correction with a uniform finite-dimensional bound, and distinguish deterioration of a sufficient overlap estimate from a claim about actual conditioning. The graph counterexample shows that a one-node coarse space can miss a high-conductance channel despite a fixed overlap graph. The inexact example computes how local spectral-equivalence constants enter the additive bound. The overlap-shrinking example assumes Countable Choice, matching the structured stable-decomposition theorem it uses.
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The two grounding edges have conductance and the connecting edge has conductance , giving the matrix in A one-node coarse space misses a high-conductance channel. The diagram records the graph used in the exact calculation; the counterexample proof is algebraic.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The stable-splitting guarantee worsens as overlap shrinks
Example
Assume Countable Choice. For any admissible overlap radius in the structured family of Stable two-level P1 decomposition for structured Poisson meshes, put . Substitution into the proved stable-decomposition guarantee gives Along admissible families with , this upper-bound formula grows. This substitution does not assert that the actual stable constant or condition number must diverge.
Facts & Assumptions
Given: Countable Choice and a member of the structured P1 Poisson family of Stable two-level P1 decomposition for structured Poisson meshes and its admissible overlap radius .
The theorem proves , with independent of , , and (Stable two-level P1 decomposition for structured Poisson meshes).
Verification
Put . Substituting into [F1] gives .
To exhibit admissible radii with , fix , put , choose , and take as with . Then , and . The right side of the one-sided upper-bound formula grows; it supplies no lower estimate on the actual stable constant or condition number.
One-level point-patch Schwarz loses uniformity on 1D Poisson
Example
For the uniform -interval P1 discretization of the Dirichlet Poisson problem on , one-level exact point-patch additive Schwarz has The patches are the supports of the interior nodal hats; they overlap with their neighbors and have bounded multiplicity. Nevertheless the condition number diverges with the number of local spaces.
Facts & Assumptions
Given: An integer , , the fine-grid P1 basis with , and the explicitly defined Dirichlet matrix , whose diagonal entries are and whose first off-diagonal entries are .
Finite-dimensional Schwarz subspace-correction data: for injections and SPD local matrices , the exact one-level additive preconditioner is .
Verification
Direct expansion gives with . It is positive for every nonzero vector because vanishing of all successive differences and forces every . For the point-patch injection , the local matrix is . Thus [F1] gives . Each corresponding nodal hat is supported on two adjacent mesh intervals, so neighboring local supports overlap and at most three closed supports meet at a point.
For , set for . The endpoints vanish. With , the identity gives These eigenvalues are distinct because cosine is strictly decreasing on . Since is symmetric, eigenvectors for distinct eigenvalues are orthogonal: for , . The vectors are nonzero, so the orthogonal vectors form a basis of . Multiplication by gives eigenvalues for .
The smallest and largest values occur at and , respectively. Therefore As the numerator tends to and the positive denominator tends to , so the condition numbers diverge.
A one-node coarse space misses a high-conductance channel
Statement refuted
A bounded-size one-node coarse space, together with bounded-overlap exact local solves, guarantees an additive Schwarz condition number uniform in every positive diffusion contrast.
Facts & Assumptions
Given: A contrast parameter , global space , a coarse space , and one local space .
For full-column-rank prolongations, the exact additive preconditioner is with (Finite-dimensional Schwarz subspace-correction data).
Counterexample
The grounded two-node graph with unit conductance from each node to ground and conductance between the nodes has matrix For , , so is SPD. The coarse and local injections are and , hence . The additive preconditioner from [F1] is therefore . There is one local subspace, so its pairwise overlap matrix is the fixed matrix , independent of .
The vectors and are eigenvectors of with eigenvalues and . Thus has eigenvalues and , so . The low-energy channel vector is not in the one-node coarse space , and the growing condition number disproves the claim.
A uniform two-level 1D Poisson correction bound
Example
Let with on the uniform fine P1 Dirichlet mesh of . Take the coarse P1 space on the even nodes and one local space for each odd node. The exact two-level additive Schwarz operator has , , and hence , independently of .
Facts & Assumptions
Given: The uniform mesh with step , the fine stiffness energy with , the coarse space through the even nodes, and odd-node local spaces.
The additive Schwarz condition theorem gives for the stable and synthesis constants of the chosen subspaces (Additive Schwarz condition bound from stable decomposition and synthesis).
Finite-dimensional Schwarz subspace-correction data: a subspace prolongation has local energy matrix and exact additive preconditioner .
Verification
Given a fine vector , let be its coarse nodal interpolant: and . Define and . Nodal values give .
On each fine interval, at most one odd nodal hat has nonzero derivative. Thus only the coarse derivative and at most one local derivative can be nonzero there. The elementary inequality , which follows from , and integration give Hence .
On each pair of fine intervals set and . The coarse energy on that coarse interval is , exactly its fine energy contribution. Summing over gives .
Since and , the local energy is . Summing gives . The decomposition in step 1.1 therefore has total energy at most , so .
Apply [F1] to the exact Schwarz data [F2] with and to obtain . This finite one-dimensional split has a global coarse space; higher-dimensional overlap estimates are handled separately on the A page.
Inexact local solves enter through spectral-equivalence constants
Example
Take and the two coordinate subspaces. Exact local matrices are , so the exact preconditioner is and its condition number is . Choose inexact local matrices and . They satisfy , while and . The theorem's bound is .
Facts & Assumptions
Given: , for , and the inexact local matrices above.
The additive Schwarz theorem gives under (Additive Schwarz condition bound from stable decomposition and synthesis).
The Schwarz definition gives and (Finite-dimensional Schwarz subspace-correction data).
Verification
The coordinate decomposition is stable with , and its synthesis bound is because . Exact local matrices equal , so [F2] gives and condition number .
The inexact local inverses are and , so [F2] gives . Its eigenvalues are and , hence . The choices and satisfy the local order bounds.
Substitution of , , and into [F1] gives the rigorous upper bound , which contains the directly computed value .