Degree Distance Calculator

vertex degree × distance sum

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About Degree Distance Calculator

A degree distance calculator computing DD(G) = Σ d(v)·D(v) where D(v) = Σ dist(v,u). Equivalent to Schultz index. Dobrynin-Kochetova (1994). Vertex-centric formulation. DD predicts molecular properties combining connectivity and topology. Client-side.

Degree Distance Calculator Features

  • DD(G)
  • d(v)·D(v)
  • Vertex-centric
  • ≡ Schultz
  • Common graphs
Degree distance DD(G) = Σ d(v)·D(v) where D(v) = distance sum of vertex v. Vertex-centric version of Schultz index. DD = S (they're the same!). Dobrynin-Kochetova (1994). Clean vertex-centric formulation enables faster computation.

How to Use

Select graph:

  • DD: Degree distance
  • d·D: Per vertex
  • D(v): Dist. sum

Vertex-Centric View

For each vertex v: contribution = d(v)·D(v). Hub with many distant vertices: large contribution. Isolated leaf: small. This formulation reveals which vertices drive the index value.

DD ≡ Schultz

DD(G) = Σ_v d(v)·D(v) = Σ_{i

Step-by-Step Instructions

  1. 1Select graph.
  2. 2For each vertex: d(v)·D(v).
  3. 3Sum contributions.
  4. 4Identify top contributors.
  5. 5Compare with Schultz.

Degree Distance Calculator — Frequently Asked Questions

If DD = Schultz, why have both?+

Different perspectives! DD is vertex-centric: which vertices contribute most? Schultz is pair-centric: which pairs contribute most? Same total but different analytical insights.

What does D(v) tell us?+

D(v) = Σ dist(v,u) is the total distance of vertex v: how 'central' it is. Low D(v) = central. High D(v) = peripheral. DD weights this by degree, so central hubs dominate.

Computation advantage?+

DD = Σ d(v)·D(v) needs one BFS per vertex to find D(v), then O(n) multiplication. More cache-friendly than pairwise computation. Same complexity but better constants.

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