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Distinct Edge Weights

Explore the concept of distinct edge weights and how they ensure the uniqueness of minimum spanning trees in connected weighted graphs. Understand the proof using greedy exchange and learn a tie-breaking method for edges with equal weights. This lesson helps you implement reliable algorithms for finding minimum spanning trees in Python.

Suppose we are given a connected, undirected, weighted graph. This is a graph G=(V,E)G = (V, E) together with a function w:ERw: E \rightarrow \mathbb{R} that assigns a real weight w(e)w(e) to each edge ee, which may be positive, negative, or zero. This chapter describes several algorithms to find the minimum spanning tree of G\bold{G}, that is, the spanning tree T that minimizes the function

w(T):=e ε Tw(e).w(T):=\underset{e \space\varepsilon\space T}{\sum}w(e).

Distinct edge weights

An annoying subtlety in the problem statement is that weighted graphs can have more than one spanning tree with the same minimum weight; in particular, if every edge in GG ...