Research notes on every problem, and a library of the papers behind them. Built from the open erdos repository.
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Transversal equality
Proved, but not a solution of the remaining core problem. This checks Appendix E of the independent input and records its precise conditional consequence.
Equality classification
Let be disjoint nonempty parts, , and let contain only edges between parts. Put and . If has no independent transversal, then
Indeed, the number of edges in a uniformly random transversal is always at least one and has expectation .
Equality holds if and only if there is a central part and a map such that the entire edge set consists, for each , of all edges from to .
To prove necessity, equality implies that every transversal contains exactly one edge, since every transversal has positive probability. Thus two edges cannot occur together in a transversal. In the graph on part indices recording which pairs support edges, any two edges must intersect. Such a family of pairs is a star or is contained in a triangle. If all three pairs occur, then within each part the vertices used toward the two other parts are disjoint: otherwise two edges could occur together. Choose an -incident vertex in , a -incident vertex in , and a -incident vertex in . They are pairwise nonadjacent. No further supported pair can meet all three triangle pairs unless it belongs to the triangle. Arbitrary choices in the other parts therefore give an independent transversal, a contradiction.
Hence all supported pairs share a central index . A fixed has neighbors in at most one other part, again because two edges cannot occur together. It must have neighbors in some part, and must be complete to that part: otherwise a transversal through with a nonneighbor there has no edge. This proves the description. Conversely the described graph gives exactly one edge in every transversal, proving sufficiency.
For equal part sizes , this classifies precisely the obstructions with cross edges.
Conditional clique merging
Suppose the are cliques of a graph and records all its cross edges. Under the equality hypothesis define . Then
partitions the union of the parts into cliques. In particular, if , then
If and every , these are disjoint 's. This is an exact-equality conclusion, not a method to complete the near-full cliques currently available.
That special configuration cannot occur in an actual counterexample for . Its union has vertices, leaving vertices. The remaining set contains a target-nonadjacent pair , since is forbidden. Each has at most one neighbor in every merged . Thus each of the peripheral parts , , retains at least vertices avoiding both. These peripheral parts have no target cross edges; their representatives together with give an independent -set.
What equality does not establish
The global stability partition allows cross edges and substantial list-size variation after neighborhoods are removed. Neither large-clique clusters nor hereditary span forces in its surviving parameter range.
Even arbitrarily small positive slack does not give the exact classification. On three parts of size , take all edges between and one further edge between . There is no independent transversal and , but the graph is not an equality system. This is only a transversal example, not a coloring counterexample or a disproof of an approximate stability theorem. No such stability theorem is proved here.
The matching-conflict theorem in Packing tools has a different extremal regime. If all parts have size at least two and every pair of parts is joined by a matching, an equality system is impossible: its central vertex would have to dominate a nonsingleton part. In the rigid system of parts of size , the normalized cross-edge count is .
Finally, summing a separate conflict lower bound for every exception is unjustified without controlling reuse of edges. If many exceptions have the same available lists, one cross edge appears in every one of their obstruction counts. The independent input's failed additive charge is therefore a real limitation, not a missing arithmetic estimate. The weighted inequalities in Two-supported private cliques retain the exceptional-edge terms instead of discarding them.