Product constructions #
This file begins the deterministic part of the upper-bound proof. The main result here is the slice simulation lemma: a pebbling sequence in one factor of a Cartesian product can be executed inside a fixed slice of the product.
Cartesian product of simple graphs.
Equations
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A product distribution assembled from first-factor fibers indexed by the
second factor. The value at (x, z) is the value of the z-fiber at x.
Equations
- PebblingLean.Pebbling.fibersDistribution F p = F p.2 p.1
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Replace one first-factor fiber in a family of fibers.
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The family obtained by replacing all fibers in s by their target fibers.
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A distribution supported in the slice {x} × W, with profile E in the
second coordinate.
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One move in the first factor can be replayed inside a fixed fiber of the Cartesian product, leaving all other fibers unchanged.
A pebbling sequence in the first factor can be replayed inside a fixed fiber of the product.
Independent first-factor preparations in every fiber can be composed into one product pebbling sequence.
One move in the second factor can be replayed inside a fixed product slice.
A pebbling sequence in the second factor can be replayed inside a fixed slice of the product.
If E solves a target in the second factor, then the corresponding slice
distribution solves the corresponding product target.
Once a product distribution dominates a prepared slice, any target reachable from the slice is also reachable from the product distribution.
Composition bridge for the deterministic product step: if a first phase
reaches a distribution dominating the prepared slice {x} × W, then a solution
inside the W factor can be appended to solve the product target.
If every fiber can prepare the number of pebbles prescribed by E at the
same first-coordinate target x, then the product distribution can be moved to
a distribution dominating the slice {x} × W with profile E.
Deterministic product step. If E solves H, and each z-fiber has
enough demand-solvability in G to prepare E z pebbles at any chosen
first-coordinate target, then the assembled product distribution solves
G □ H.
Costed form of the deterministic product step, matching the recursive
upper-bound bookkeeping: only occupied vertices of E need nonzero demand
distributions in the first factor.