Vertex arboricity of cographs
Pith reviewed 2026-05-24 20:34 UTC · model grok-4.3
The pith
Cographs admit a polynomial-time dynamic programming algorithm to decide partitions into p forests and q independent sets.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
We give a polynomial-time dynamic programming algorithm for deciding whether a given cograph admits a vertex partition into p forests and q independent sets; the algorithm also solves maximum q-colourable subgraph, maximum subgraph of arboricity p, minimum vertex feedback set, and minimum q of a q-colourable vertex feedback set.
What carries the argument
Dynamic programming over the cotree whose nodes are disjoint-union or join operations, with states that track feasible assignments of each subtree's vertices to the p forests and q independent sets.
If this is right
- For any fixed p and q the decision problem is solvable in polynomial time on cographs.
- The same procedure yields polynomial-time solutions for maximum q-colourable subgraph and maximum arboricity-p subgraph on cographs.
- Minimum feedback vertex set and minimum q-colourable feedback vertex set are polynomial-time solvable on cographs.
- When p equals 2 there exists a finite list of minimal cograph obstructions to arboricity 2.
- For larger p the number of minimal obstructions grows exponentially while their size and cotree height remain bounded.
Where Pith is reading between the lines
- The same state-combination technique could be reused for other partition problems into bounded-density subgraphs on cographs.
- Exact arboricity computation on cographs becomes polynomial-time for every fixed target value.
- Obstruction sets for related parameters such as linear arboricity may admit similar exponential-size but bounded-height descriptions.
Load-bearing premise
The number of states needed to combine solutions at each cotree node stays polynomial in the fixed parameters p and q.
What would settle it
A concrete cograph together with specific p and q where running the described dynamic program on its cotree produces a yes/no answer that differs from the true existence of such a partition.
read the original abstract
Arboricity is a graph parameter akin to chromatic number, in that it seeks to partition the vertices into the smallest number of sparse subgraphs. Where for the chromatic number we are partitioning the vertices into independent sets, for the arboricity we want to partition the vertices into cycle-free subsets (i.e., forests). Arboricity is NP-hard in general, and our focus is on the arboricity of cographs. For arboricity two, we obtain the complete list of minimal cograph obstructions. These minimal obstructions do generalize to higher arboricities; however, we no longer have a complete list, and in fact, the number of minimal cograph obstructions grows exponentially with arboricity. We obtain bounds on their size and the height of their cotrees. More generally, we consider the following common generalization of colouring and partition into forests: given non-negative integers $p$ and $q$, we ask if a given cograph $G$ admits a vertex partition into $p$ forests and $q$ independent sets. We give a polynomial-time dynamic programming algorithm for this problem. In fact, the algorithm solves a more general problem which also includes several other problems such as finding a maximum $q$-colourable subgraph, maximum subgraph of arboricity-$p$, minimum vertex feedback set and minimum $q$ of a $q$-colourable vertex feedback set.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper claims a polynomial-time dynamic programming algorithm on cotrees to decide if a cograph admits a partition of its vertices into p forests and q independent sets; the same algorithm solves maximum q-colourable subgraph, maximum arboricity-p subgraph, minimum vertex feedback set, and minimum q of a q-colourable feedback set. It also enumerates the complete list of minimal cograph obstructions for arboricity 2 and gives bounds on the number, size, and cotree height of minimal obstructions for higher arboricity.
Significance. If the central claims hold, the work supplies an explicit, polynomial-time solution for a natural common generalization of colouring and arboricity on cographs, together with a concrete obstruction list for the arboricity-2 case. The DP construction and the enumeration result are both contributions that can be directly used or extended in the study of sparse partitions on perfect graphs.
minor comments (2)
- The abstract states that the DP state cardinality is polynomial in p and q; the main text should include a short explicit count of the states (or a reference to the precise recurrence) so that the polynomial bound is immediately verifiable without reconstructing the full table.
- For the arboricity-2 obstruction list, a brief indication of how the enumeration was performed (e.g., by exhaustive generation up to a size bound derived from the cotree height) would strengthen the completeness claim.
Simulated Author's Rebuttal
We thank the referee for the positive assessment of our manuscript and the recommendation to accept. The report accurately summarizes the main contributions regarding the polynomial-time DP algorithm for (p,q)-forest-coloring on cographs and the enumeration of minimal obstructions for arboricity 2.
Circularity Check
No significant circularity; explicit DP algorithm on cotrees
full rationale
The paper's central contribution is an explicit polynomial-time dynamic programming algorithm on the cotree representation of cographs that tracks vertex counts for p forests and q independent sets, with additive merging at union nodes and cross-edge restrictions at join nodes. The state space is stated to remain polynomial in p and q, and the recurrences are defined directly from the cotree operations without any reduction to fitted parameters, self-citations, or renamed empirical patterns. The enumeration of minimal obstructions for arboricity 2 and the size/height bounds for higher values are obtained by exhaustive structural analysis of the same cotree model rather than by any self-referential construction. No load-bearing step collapses to a definition or prior self-citation; the derivation is self-contained.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption Every cograph has a cotree representation using only disjoint-union and join nodes.
Lean theorems connected to this paper
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IndisputableMonolith/Foundation/AbsoluteFloorClosure.leanreality_from_one_distinction unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
We give a polynomial-time dynamic programming algorithm for deciding whether a given cograph admits a vertex partition into p forests and q independent sets
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
discussion (0)
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