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Let G=(V,E) be an undirected graph. Prove that if all its edge weights are distinct, then it has a unique minimum spanning tree

Short Answer

Expert verified

Here, we get undirected graph G. Given here to prove non - negative real edge weights, and presume that even if you calculated a minimal spanning tree of G and the short distance for that kind of node, it accepts particular nodesV.

Step by step solution

01

Two alternative shortest path trees

If most of the parameters associated in such an undirected graph disagree, the graph has a single minimal spanning tree.

• Assume there are two alternative shortest path trees inside of an undirected graph, including such T1andT2.

• Let e1seems to be the minimal side weight which relates to a few of the trees, for example. e1T1.

• Including the side role="math" localid="1658904910955" e1into the tree T2making of cycle. The cycle includes the edge of role="math" localid="1658904901130" e2in tree T2, any one is bigger than e1.

• This seems to be an inconsistency for which an indifference curve has two distinct minimum spanning trees.

02

Proof of theoem.

Using the cut property, find the minimal spanning tree based on the graph's topology and edge weight order.

The minimal side value is already on the lowest spanning tree for each and every cut.

• Since all of the respect to the weights inside a graph are different, then all of the cuts are unique.

• If all of the edge weights in a graph are the same, the outcome may be unclear.

If all the edge weights of a graph are distinct, the smallest spanning tree is unique.

For example:

Consider the undirected graph G = (V, E) is given below:

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Most popular questions from this chapter

Let T be an MST of graph G. Given a connected subgraph H of G, show that TH is contained in some MST of H

The following table gives the frequencies of the letters of the English language (including the blank for separating words) in a particular corpus.

blank

18.3%

r

4.8%

y

1.6%

e

10.2%

d

3.5%

p

1.6%

t

7.7%

l

3.4%

b

1.3%

a

6.8%

c

2.6%

v

0.9%

o

5.9%

u

2.4%

k

0.6%

i

5.8%

m

2.1%

j

0.2%

n

5.5%

w

1.9%

x

0.2%

s

5.1%

f

1.8%

q

0.1%

h

4.9%

g

1.7%

z

0.1%

  1. What is the optimum Huffman encoding of this alphabet?
  2. What is the expected number of bits per letter?
  3. Suppose now that we calculate the entropy of these frequencies

H=t=026ptlog1pt

(see the box in page 143). Would you expect it to be larger or smaller than your answer above? Explain.

d. Do you think that this is the limit of how much English text can be compressed? What features of the English language, besides letters and their frequencies, should a better compression scheme take into account?

Suppose you are given a weighted graph G=(V,E) with a distinguished vertex s and where all edge weights are positive and distinct. Is it possible for a tree of shortest paths from s and a minimum spanning tree in G to not share any edges? If so, give an example. If not, give a reason.

Show how to find the maximum spanning tree of a graph, that is , the spanning tree of largest total weight.

Give You are given a graphG=(V,E)with positive edge weights, and a minimum spanning tree T=(V,E)with respect to these weights; you may assume GandTare given as adjacency lists. Now suppose the weight of a particular edge eE'is modified fromw(e)to a new value w'(e). You wish to quickly update the minimum spanning tree T to reflect this change, without recomputing the entire tree from scratch. There are four cases. In each case give a linear-time algorithm for updating the tree.

(a) eE'and w'(e)>w(e) .

(b) role="math" localid="1658907878059" eE'and w'(e)>w(e) .

(c) role="math" localid="1658907882667" eE'and w'(e)>w(e) .

(d) role="math" localid="1658907887400" eE'and w'(e)>w(e) .

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