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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

Short Answer

Expert verified

Here, there will be MST base graph through it proves that T is sign with H and contained in some of MST. Which is related to H. But there will be is H connected with G. So, we can conclude or can say that T is graph of G.

Step by step solution

01

Verification for   is controlled in Smallest Spanning Tree(H):

When explore together all nodes of a graph, a minimal spanning tree travels the all edges which do not create a cycle. Together all edges of T that do not make a cycle in T are included in an MST T of a graph G. A cycle may not even exist in a G sub-graph.

02

H includes cycles

• Whenever H has a cycle, there would be a lot of MST of H. For each MST of H , an unique smallest node will be excluded. Once there is n nodes within and H and k cycles in H, there can be n-k edges in THbecause T visits all nodes in T that do not form a cycle.

• Because T has no cycle, the intersecting of H plus T will not have a cycle, omitting just those nodes of H that contribute to the creation of a cycle. As per definition of H, TH is an as it is containing all edges except the edge which is creating cycle. When THis itself an MST, then it is obvious that it is contained in itself.

Hence, it is proved that if H contains a cycle, then TH is contained in some MST of H.

03

H does not contain a cycle

• H is indeed an MST when it does not include a cycle. T is now an MST, thus, TH would then include all of H's nodes., TH=H. Whenever T & H both are equal to each other then THis also an MST.

• Whenever TH is MST, Then it would be evident that it's self-contained.

As a result, it can be demonstrated that if H does not include a cycle, then TH is contained in some MST of H.

04

Conclusion

THis H. occurs in some MST The evidence is demonstrated in the next section. Assume the graph G in Figure 1 is correct.

Figure 1

The MST of the graph will be as shown in Figure 2.

Figure 2

Figure 3 is a subgraph H of graph G .

Figure 3

The MST of this graph will be as shown in Figure 4.

Figure 4

THT with H's shared edges will be contained. Figure 4 is role="math" localid="1658914214466" TH. Thus, TH=MSTH.If somehow the weight for ED in Figure 1 was 6, then the weight of ED in Figure 2 would be 6. But there would have been two MST of H, one with the ED edge and the other with the EF edge. However, there'd have been two MST of G as well. In either scenario, every MST of H would contain the crossover of any T with H.

As a result, is always present in some H MST.

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Most popular questions from this chapter

A prefix-free encoding of a finite alphabet Γ assigns each symbol in Γ a binary codeword, such that no codeword is a prefix of another codeword. A prefix-free encoding is minimal if it is not possible to arrive at another prefix-free encoding (of the same symbols) by contracting some of the keywords. For instance, the encoding {0,101} is not minimal since the codeword 101 can be contracted to 1 while still maintaining the prefix-free property.

Show that a minimal prefix-free encoding can be represented by a full binary tree in which each leaf corresponds to a unique element of Γ, whose codeword is generated by the path from the root to that leaf (interpreting a left branch as 0 and a right branch as 1 ).

In this problem, we will develop a new algorithm for finding minimum spanning trees. It is based upon the following property:

Pick any cycle in the graph, and let e be the heaviest edge in that cycle. Then there is a minimum spanning tree that does not contain e.

(a) Prove this property carefully.

(b) Here is the new MST algorithm. The input is some undirected graph G=(V,E) (in adjacency list format) with edge weights {we}.sort the edges according to their weights for each edge eE, in decreasing order of we:

if e is part of a cycle of G:

G = G - e (that is, remove e from G )

return G , Prove that this algorithm is correct.

(c) On each iteration, the algorithm must check whether there is a cycle containing a specific edge . Give a linear-time algorithm for this task, and justify its correctness.

(d) What is the overall time taken by this algorithm, in terms of |E|? Explain your answer.

The basic intuition behind Huffman’s algorithm, that frequent blocks should have short encodings and infrequent blocks should have long encodings, is also at work in English, where typical words like I, you, is, and, to, from, and so on are short, and rarely used words like velociraptor are longer.

However, words like fire!, help!, and run! are short not because they are frequent, but perhaps because time is precious in situations where they are used.

To make things theoretical, suppose we have a file composed of m different words, with frequencies f1,...,fm. Suppose also that for the ithword, the cost per bit of encoding is ci. Thus, if we find a prefix-free code where the ithword has a codeword of length Ii, then the total cost of the encoding will be localid="1659078764835" fi·ci·li.

Show how to modify Huffman’s algorithm to find the prefix-free encoding of minimum total cost.

Under a Huffman encoding of symbols with frequenciesf1,f2,.....,fn , what is the longest a codeword could possibly be? Give an example set of frequencies that would produce this case.

We use Huffman's algorithm to obtain an encoding of alphabet {a,b,c}with frequencies fa,fb,fc. In each of the following cases, either give an example of frequencies (fa,fb,fc)that would yield the specified code, or explain why the code cannot possibly be obtained (no matter what the frequencies are).

(a) Code:{0,10,11}

(b) Code:{0,1,00}

(c) Code:{10,01,00}

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