Consumption of the reset path by Σ0(a5)
If the connected reset path retains a useful simplification, it should appear in the exact a5[22] mask or in the four low lanes of Σ0(a5) for the actual survivors.
Diagnostic work, exact algebra and local capabilities are not treated as end-to-end mining advantage.
What was tested?
If the connected reset path retains a useful simplification, it should appear in the exact a5[22] mask or in the four low lanes of Σ0(a5) for the actual survivors.
Why the test is meaningful
Rotations redistribute state-bit dependencies rather than erase them. Algebraic normal form (ANF) gives a unique representation over GF(2), allowing complexity to be compared by nonlinear monomial support while exact mask semantics remain the primary gate.
Σ0(a5)=ROTR²(a5)⊕ROTR¹³(a5)⊕ROTR²²(a5)f(x)=⊕_{S⊆{0,1,2,3}} α_S ∏_{i∈S}x_inonlinear support N(f)={S:α_S=1, |S|≥2}How it was tested
Compose the V29 carry masks into exact a5 bit 22 and Σ0(a5).low4 truth masks. Compare nonlinear support between connected survivors and non-survivors in the 1,361-record original cohort, then repeat on 300 fresh records without converting group contrasts into selectors.
What happened
Semantic errors were zero. Original mean Σ0 low4 nonlinear support was 9.951 for non-survivors and 9.910 for survivors; fresh means were 10.063 and 10.099, reversing the small difference. At lane 0, every fresh mask was unique within its group.
Exactness and statistical controls
Every ANF was derived from an exact truth mask. The decisive comparison was replication of direction: the small original low4 simplification did not replicate in the fresh cohort. Therefore no survivor simplification was promoted.
What the result means
By the first connected Σ0 consumer, the reset-derived signal is attenuated to small, unstable group contrasts. V30 is a scientifically useful non-promotion result, not a failed exact computation.
Limitations
- ANF monomial count is a representation metric, not native circuit cost.
- Survivor groups are fixed observed groups, not predictive selectors.
- Small differences require independent replication and uncertainty-aware interpretation.
Evidence trail
Reconstruct exact truth masks, apply a Möbius transform to obtain ANF coefficients, preserve the registered survivor split and repeat all contrasts on the untouched fresh cohort.
Canonical variants
SUBENGINE-V30ASUBENGINE-V30BSUBENGINE-V30CSource: internally audited canonical reports. Local filesystem structure, private headers and operational identifiers are excluded from publication.