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The comment combines memory, an attention-like exponential, and a time integral. The body instead computes a mean unity score across family activations, builds Qᵢ=aᵢcos phaseᵢ and Kᵢ=aᵢsin phaseᵢ, and multiplies mean(V) by min(exp(Q·K/√d),10¹⁰) and that score. It never reads Memory or TimeSteps, has no temporal quadrature, and does not apply softmax normalization; the displayed integral is therefore not implemented by this helper.
Terms & definitions
| Term | Meaning in this source |
|---|---|
| Phi | Mean unity score over family activations |
| Q | Activation times cosine phase |
| K | Activation times sine phase |
| V | Activation vector |
| M | Documented memory field, unused in this method |
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Original context
Read the surrounding source passage
Key: make([]float64, dim),
Value: make([]float64, dim),
DimK: math.Sqrt(float64(dim)),
TimeSteps: 100,
}
}
// Integrate computes T = Φ · ∫[M(t')·exp((QK^T/√d_k)V)] dt'
func (ct *CompleteThought) Integrate(familyNetwork *FamilyNetwork) float64 {
// Update Phi from family network coherence
ct.Phi = 0.0
for i := 0; i < NumStrands; i++ {
ct.Phi += 1.0 / (1.0 + math.Abs(familyNetwork.States[i].Activation-1.0))
}
ct.Phi /= NumStrands
// Build Q, K, V from family activations
for i := 0; i < len(ct.Query) && i < NumStrands; i++ {Exact original notation
Integrate computes T = Φ · ∫[M(t')·exp((QK^T/√d_k)V)] dt'