2501.02023
From Data to Combinatorial Multivector field Through an Optimization-Based Framework
Dominic Desjardins Côté, Donald Woukeng
correcthigh confidence
- Category
- Not specified
- Journal tier
- Specialist/Solid
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
Both the paper and the candidate solution prove that any 0–1 assignment z(σ,τ) satisfying constraints (13) partitions K by toplex and that each block is convex. The paper’s Theorem 3.6 defines V_τ := {σ ≤ τ : z(σ,τ)=1} ∪ {τ}, shows these sets form a partition by uniqueness-of-toplex assignment, and proves convexity by propagating z=1 along immediate face–coface steps and then along chains, exactly as the candidate does. The core steps—(i) uniqueness of assignment for non-toplexes, (ii) disjointness of toplex-containing sets, and (iii) upward-closure/convexity via the z(σ_i,τ) ≤ z(σ_j,τ) constraint—align one-for-one with the model’s argument. See the paper’s statement of (13) and its proof of Theorem 3.6 (definition of V_τ, partition, and convexity) in the provided PDF .
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} specialist/solid \textbf{Justification:} The main theorem is proved correctly and efficiently. The constraints are well-chosen so that feasibility implies convex multivectors, and the construction V\_τ is standard. Minor terminological and notational clarifications would strengthen the presentation but do not affect correctness.