Shannon Bounds #
For N ≥ 6, there exists a Boolean function on N inputs that cannot be
computed by any fan-in-2 AND/OR circuit with fewer than 2^N / (5N) gates.
The proof proceeds by a counting (pigeonhole) argument: the number of distinct circuits of a given size is strictly less than the number of Boolean functions, so some function must be hard.
Main results #
The main theorem is shannon_lower_bound_circuit:
theorem shannon_lower_bound_circuit (N : Nat) [NeZero N] (hN : 6 ≤ N) :
∃ f : BitString N → Bool,
∀ G (c : Circuit Basis.andOr2 N 1 G),
c.size ≤ 2 ^ N / (5 * N) →
(fun x => (c.eval x) 0) ≠ f
The statement uses the library's total Circuit.size; for a single-output
circuit this is G + 1.
When Basis.andOr2 is known to be complete, this yields a
sizeComplexity bound via shannon_sizeComplexity.
shannon_upper_bound— for sufficiently largeN, every Boolean function onNinputs hassizeComplexityat most18 · 2^N / N.
Together these establish that worst-case circuit complexity is Θ(2^N / N).
Shannon lower bound for circuits: for N ≥ 6, there exists a Boolean
function on N inputs that cannot be computed by any fan-in-two AND/OR
circuit of total size at most 2^N / (5N).
For a single-output circuit, c.size = G + 1.
Shannon lower bound in terms of sizeComplexity: for N ≥ 6,
there exists a Boolean function whose fan-in-2 AND/OR circuit complexity
exceeds 2^N / (5N).
Shannon upper bound: for N ≥ 16, every Boolean function on N
inputs has fan-in-2 AND/OR circuit complexity at most 18 · 2^N / N.
Combined with shannon_sizeComplexity, this gives Θ(2^N / N).
This is the full-column-library variant (C = 18). The tighter
(1 + o(1)) · 2^N / N bound due to Lupanov (1958) uses column
grouping and is not yet formalized.