Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-generatedPipeline-generatedprecheck pass
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Finite aggregation AMG preserves the SPD matrix class and returns a status

Statement

For every admissible input to Finite strength-graph aggregation and Galerkin hierarchy with explicit statuses, each successful aggregation partitions the current indices into nonempty disjoint sets. Its indicator prolongation has full column rank. Every successful Galerkin product Aℓ+1=PℓTAℓPℓ is symmetric positive definite with nonpositive off-diagonal entries. The setup procedure terminates after at most ⌊L⌋ coarsening attempts and returns exactly one of coarse-reached, level-cap, or coarsening-stalled. These structural properties do not imply multigrid convergence.

Facts & Assumptions

Given: The admissible real symmetric positive-definite matrix A0 with nonpositive off-diagonal entries, 0<θ<1, nmin⁡≥1, and real finite cap L∈R≥0.

[F1]

Finite strength-graph aggregation and Galerkin hierarchy with explicit statuses: each aggregate begins with the smallest unassigned vertex and removes that vertex together with some of its still-unassigned neighbours; the output uses Pir=1 exactly on aggregate membership and the Galerkin product. Before each attempt, the procedure returns level-cap if ℓ+1>L.

[F2]

The Galerkin coarse correction is an energy-orthogonal projector: if a real SPD matrix is compressed by a full-column-rank prolongation, the Galerkin coarse matrix is SPD.

[F3]

Hermitian positive-definite matrices and Cholesky factorisation A = LL* with positive diagonal: positive definite in the real case means symmetric and strictly positive quadratic form on every nonzero vector.

Proof

1.1F1chooseconstruct

At any aggregation pass the unassigned set U is finite and nonempty. The selected smallest vertex i belongs to the new aggregate, so at least one vertex is removed. No previously removed vertex can reappear because every neighbour is intersected with U. Thus the aggregates are pairwise disjoint and, when the finite loop ends at U=∅, cover all current indices. Each aggregate is nonempty. If Pz=0, choose any row index in aggregate r; its row has a single 1 in column r, so that component of Pz is zr=0. This holds for every r, hence P has full column rank.

2.1F1F2F3step 1.1algebra

By [F2] and step 1.1, Aℓ+1=PℓTAℓPℓ is SPD. For distinct aggregate columns r≠s, disjointness gives (Aℓ+1)rs=∑i∈Cr∑j∈Csaij(ℓ)≤0, since i≠j in every summand and the fine matrix has nonpositive off-diagonal entries. Symmetry follows from symmetry of Aℓ. Induction over successful levels proves the same matrix class at each returned level.

2.2F1step 1.1choosealgebra

Each aggregation pass is finite by step 1.1. A pass is attempted only when ℓ+1≤L, so the number of attempts is an integer at most ⌊L⌋. At each outer iteration, step 1 returns coarse-reached when nℓ≤nmin⁡; otherwise the cap test in [F1] returns level-cap when ℓ+1>L. If neither branch applies, a pass is performed and either nℓ+1≥nℓ returns coarsening-stalled, or the procedure advances to the next level. These ordered branches exhaust the procedure, so it terminates with exactly one listed status.

3.1step 1.1step 2.1step 2.2∎

The preceding steps establish the partition, rank, matrix-class and status claims. No step asserts a contraction factor.

Depends on

Used by

Nothing in the library uses this result yet.

Cited to discharge well-definedness by Finite strength-graph aggregation and Galerkin hierarchy with explicit statuses.

Dependency tree · two levels

12 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources