Research notes on every problem, and a library of the papers behind them. Built from the open erdos repository.
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Statement
Use , admissible paths, heavy pairs, and from good paths. Let have vertices and maximum degree at most an integer . Let and be integers, and suppose
If , there are a vertex , a neighbor of , distinct neighbors of different from , and a family of admissible -paths starting at , such that
and every endpoint of a path in is heavy-adjacent at length to every . No claim that the members of are mutually disjoint is made or needed.
Proof
Fix . For each let be the number of good -paths from to , and put
The good-fiber and walk bounds give
Each bad admissible path has a first vertex , a second vertex , and a good tail from to its last vertex , with . This encoding is injective. Its reverse need not be admissible, so the valid conclusion is . The assumed excess yields some with .
Discard from the sum the vertices with . By (3), this costs at most . Thus
Since , some has a set satisfying
For , set and let . Then and , since and are heavy-adjacent. Write and . Combining (3)–(4) gives
By the threshold recurrence and (1), . Since , this implies
Multiplying (5) by and using therefore gives
Apply the weighted common-neighborhood lemma from finite selection with ambient set , neighborhoods , and target weight . It yields distinct and total common weight greater than that target. Every differs from because it lies in for at least one positive-weight common neighbor.
Let be all admissible -paths from to those common neighbors in . Fibers for different final vertices are disjoint, so their sizes sum to precisely that common weight, proving (2). The defining membership of each in proves every required heavy adjacency.
Source and scope
Complete reconstruction of FiniteDenseWeightedLink.select,
WeightedAdmissibleSelection.select, AdmissibleHeavyLinks.bad_le_mass
and dense_fan, and AdmissibleHeavyCommon.local_select and global,
pinned Lean lines 7174–7415 and 9532–9637. The
exposition, p. 5, states the pruning
mechanism without this weighted calculation. Both strict inequalities and
the loss of one neighbor when deleting are retained here.
Used by. Uniform heavy-path pruning.
Bears on. #571.