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3D Vector Space Simulator
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NoVectDB · Mathematical Foundation
Knowledge Object
K = (G, T, V, S)
G: geodesic coordinate (manifold)
T: type signature
V: vector embedding ∈ ℝⁿ
S: sheaf section
Composite Distance (Def 3.4)
d(Kₐ,K_b) =
α·d_geo(a,b)
+ β·(1 − TVS(Tₐ,T_b))
+ γ·‖Sₐ ∘_π S_b‖
α,β,γ ≥ 0 are weighting coefficients. When the sheaf is globally consistent, this is a true metric space (ε = 0).
Live Coefficients (α+β+γ = 1)
α 0.60
β 0.25
γ 0.15
λ 2.5
Last query:
d_geo =
TVS =
sheaf=
Chip Assignment (Voronoi)
chip(q) = argmin_c ‖q − μ_c‖₂
q is assigned to the chip whose centroid μ_c minimises Euclidean distance — the Voronoi cell.
Cosine Similarity (Crumb Rank)
sim(a,b) = (a·b)/(‖a‖·‖b‖) ∈ [−1,1]
Within a chip's Voronoi cell, crumbs are ranked by cosine similarity to the query vector.
Variance Threshold (Auto-Split)
Var(c) = (1/|c|)Σᵢ‖xᵢ−μ_c‖² > σ²_max
→ bisecting k-means split
Expected Complexity
T(n) = O(log n) + O(|c|)
At K = √n → O(√n)
O(log n) for chip navigation (HNSW). O(|c|) for linear scan within the Voronoi cell.
chip_00
chip_01
chip_02
chip_03
chip_04
chip_05
HNSW edge
query point
k-NN result
crumbs: 0
chips (K): 6
query:
nearest:
d_geo:
formula: d(Kₐ,K_b) = α·d_geo + β·(1−TVS) + γ·‖S∘S‖
sim live