Counting the number of spanning tree Pied Piper Department of - - PowerPoint PPT Presentation

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Counting the number of spanning tree Pied Piper Department of - - PowerPoint PPT Presentation

Counting the number of spanning tree Pied Piper Department of Computer Science and Engineering Shanghai Jiao Tong University Contents Co Comp mplet lete e Gr Grap aph 1 2 Proof of the Lemma Arbitrary Graph 3 4 Proof with


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Counting the number of spanning tree

Pied Piper Department of Computer Science and Engineering Shanghai Jiao Tong University

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目录 Contents 1

Co Comp mplet lete e Gr Grap aph

2

Proof of the Lemma

3

Arbitrary Graph

4

Proof with Matrics

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Kn : a complete graph with n vertices

Fo For each r each n n ≥2, th the num e number of s ber of spanning panning tr tree ees of s of Kn Kn eq equals n uals nn-2

Cayley’s formula

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vertebrates

De Defini nition ion: Kn : A spanning tree of the complete graph Kn ver erte tebr brate ate : consider a Kn , mark one vertex by a circle, one vertex by a square . : the set of all vertebrates (consider value of n) Ch Chor

  • rd : a unique path connect and .

A vertebrate on 19 vertices

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From each given spanning tree, we can create n2 vertebrates. Therefore the number of all spanning trees equals

Lem emma.

  • a. There exists a bijection F between the of all vertebrates

and the set of all mappings of the vertex V to itself.

Since = all mappings of an n-element set to itself = according to the lemma, therefore the number of spanning trees is

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Pr Proo

  • of of th

f of the lemm e lemma. a.

St Starts rts fr from

  • m W

W

Vertices of the chord

  • rdered by magnitude :

3 4 7 8 9 14 15 as they appeared in chord: 8 4 14 9 3 7 15 1st

st st

step ep ---

  • -- define graph P : we make an directed edge from each vertex in 1st line

to the vertex below it in the 2nd line. Vertebrate W 1st step

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2nd

nd st

step ep ---

  • -- we remove the edges of the chord from W, it splits into components.

Vertebrate W 2nd step

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3rd

rd st

step ep ---

  • -- we direct the edges of the components point to the vertex of the chord.

Vertebrate W 3rd step

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4th

th st

step ep ---

  • -- define a graph G : with vertex set V, its edges are all directed edges of

the components, plus the edges of the graph P. Step 4 --- graph G

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the resulting directed graph G, is a graph of a mapping: For each , we set , where there exists an edge { i, j } in G. graph G

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Starts from mapping f

A mapping f 1st

st st

step ep --- draw f into a directed graph( may be disjoint ), for each components, there must exists exactly one circle. Proof : For each vertex in a mapping, there is exactly 1 edges going from it. situation A : if there exists 2 or more circles, at least 1 vertex have more than 1 edges going from it, which is not possible in a mapping. Situation B : if the component is acyclic, at least 1 vertex does not have an edge going from it.

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2nd

nd st

step ep --- we extract each circle from components, and for the vertices related to the circles, we write them in order of magnitude, and write the vertex it maps below it.

  • rdered by magnitude :

3 4 7 8 9 14 15 Vertices they map to: 8 4 14 9 3 7 15 A mapping f

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  • rdered by magnitude :

3 4 7 8 9 14 15 Vertices they map to: 8 4 14 9 3 7 15 3rd

rd st

step ep --- define a undirected graph P P (a path) : with the vertices mentioned in 2nd step, and in order of 2nd line. A mapping f 3rd step

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4th

th st

step ep --- we add the rest vertices and edges of the mapping into P, change the direct edges into undirected ones.

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目录 Contents 1

Complete Graph

2

Proof of the Lemma

3

Ar Arbi bitr trar ary Gr y Grap aph

4

Proof of the theorem

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▪ What’s the number of spanning trees of an arbitrary graph?

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▪ Let G be an arbitrary graph with vertices 1, 2, …, n, n >= 2, and with edges 𝑓1, 𝑓2, …, 𝑓𝑛. ▪ We introduce an n*n matrix Q, called the Laplace matrix of the graph G, whose elements 𝑟𝑗𝑘 are determined by the following formula:

Laplace matrix

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Laplace matrix

3 1 2 2 Graph G Laplace matrix 1 2 3 4 1 2 3 4

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Laplace matrix

3 −1 −1 1 −1 −1 −1 −1 2 −1 −1 2 Graph G Laplace matrix Q 1 2 3 4 1 2 3 4 Ob Obse servat ation ion Th The e su sum m of

  • f t

the ro e rows s of

  • f th

the L e Lap aplace ace mat atrix ix is s the zer e zero

  • vec

ector

  • r
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▪ Definition

▪ Let 𝑅𝑗𝑘 denote the (n - 1) * (n - 1) matrix arising from the laplace matrix Q by deleting the 𝑗𝑢ℎ row and the 𝑘𝑢ℎ column.

Laplace matrix

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▪ Definition

▪ Let 𝑅𝑗𝑘 denote the (n - 1) * (n - 1) matrix arising from the Laplace matrix Q by deleting the 𝑗𝑢ℎ row and the 𝑘𝑢ℎ column.

Laplace matrix

3 −1 −1 1 −1 −1 −1 −1 2 −1 −1 2 1 2 −1 −1 2 3 −1 −1 −1 −1 −1 2 𝑅 𝑅23 𝑅11

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▪ Theorem

▪ 𝑈 𝐻 is the number of spanning tree in graph G. ▪ For every graph G, we have 𝑈 𝐻 = det 𝑅11

#Spanning Tree

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▪ Theorem ▪ For every graph G, we have 𝑼 𝑯 = 𝐞𝐟𝐮 𝑹𝟐𝟐

▪ 𝐵𝑑𝑢𝑣𝑏𝑚𝑚𝑧, 𝑈 𝐻 = | det 𝑅𝑗𝑘| holds for any 𝑗, 𝑘 ∈ {1, 2, … , 𝑜}. (won’t prove here)

#Spanning Tree

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▪ Theorem ▪ For every graph G, we have 𝑼 𝑯 = 𝐞𝐟𝐮 𝑹𝟐𝟐

▪ 𝑈 𝐻 = | det 𝑅𝑗𝑘| holds for any two indices 𝑗, 𝑘 ∈ {1, 2, … , 𝑜}. (won’t prove here)

▪ Take the figure before as an example

#Spanning Tree

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#Spanning Tree

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#Spanning Tree

3

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#Spanning Tree

3 −1 −1 1 −1 −1 −1 −1 2 −1 −1 2 Q:

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#Spanning Tree

3 −1 −1 1 −1 −1 −1 −1 2 −1 −1 2 𝑅 1 2 −1 −1 2 𝑅11

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#Spanning Tree

3 −1 −1 1 −1 −1 −1 −1 2 −1 −1 2 1 2 −1 −1 2 𝑅11 𝑅 det 𝑅11 = 1 ∗ 2 ∗ 2 − −1 ∗ −1 − 0 + 0 = 3

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目录 Contents 1

Complete Graph

2

Proof of the Lemma

3

Arbitrary Graph

4

Pr Proo

  • of of th

f of the theo e theorem rem

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Proofs working with determinants

  • We proceed by induction. To make proofs work, we strengthen the inductive

hypothesis and show that the theorem also holds for multigraphs. What does the Laplacian of a multigraph look like?

  • If two vertices u and w are joined by m edges, then quv = −m.
  • quu is the degree of the vertex u,
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Proofs working with determinants

▪ New formula to be relied on:

Le Lemma1 a1: T(G) = T(G − e) + T(G : e)

▪ where e is an arbitrary edge of the graph G.

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Proofs working with determinants

▪ New formula to be relied on:

Le Lemma1 a1: T(G) = T(G − e) + T(G : e)

▪ where e is an arbitrary edge of the graph G. ▪ G − e denotes the graph obtained by deleting that edge e in G.

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Proofs working with determinants

▪ New formula to be relied on:

Le Lemma1 a1: T(G) = T(G − e) + T(G : e)

▪ where e is an arbitrary edge of the graph G. ▪ G − e denotes the graph obtained by deleting that edge e in G. ▪ G : e the one obtained by contracting the edge e.

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Proofs working with determinants

▪ New formula to be relied on:

Le Lemma1 a1: T(G) = T(G − e) + T(G : e)

▪ where e is an arbitrary edge of the graph G. ▪ G − e denotes the graph obtained by deleting that edge. ▪ G : e the one obtained by contracting the edge e.

3 4 5 {1, 2}

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Proofs working with determinants

▪ In order to see why the Lemma holds, we divide the spanning trees of G into two classes. Remember the Lemma1: T(G) = T(G − e) + T(G : e)

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Proofs working with determinants

▪ In order to see why the Lemma holds, we divide the spanning trees of G into two classes. ▪ The spanning trees that do not contain the edge e. (exactly the spanning trees of the graph G−e, T(G−e).) Remember the Lemma1: T(G) = T(G − e) + T(G : e)

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Proofs working with determinants

▪ In order to see why the Lemma holds, we divide the spanning trees of G into two classes. ▪ The spanning trees that do not contain the edge e. (exactly the spanning trees of the graph G−e, T(G−e).) ▪ The spanning trees that do contain the edge e. (one-to-one correspondence with the spanning trees of G : e, as indicated in the following picture, T(G : e) .) Remember the Lemma1: T(G) = T(G − e) + T(G : e)

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Proofs working with determinants

▪ Here we give some symbols and their meaning: ▪ Q′ : the Laplacian of G−e. ▪ Q′ ′: the Laplacian of G : e ▪ Q11 : the (n − 1) × (n − 1) matrix arising from the matrix Q by deleting the first row and the first column. ▪ Q′ 11 : the (n − 1) × (n − 1) matrix arising from the matrix Q ′ by deleting the first row and the first column. ▪ Q11,22 : the (n − 2) × (n − 2) matrix arising from the matrix Q by deleting the first and second row and the first and second column. ▪ Q ′ ′11 : the (n − 2) × (n − 2) matrix arising from the matrix Q′ ′ by deleting the first row and the first column.

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Proofs working with determinants

▪ Ob Obse serva rvation1 tion1: Q′ 11 arises from Q11 by subtracting 1 from the element in the upper left corner. ▪ Ob Obse serva rvation2 tion2: Q′ ′11 = Q11,22 Assume edge e has endvertices 1 and 2

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Proofs working with determinants

= 𝑅′11 = 𝑅′′11 , , , ,

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Proofs working with determinants

▪ Now we are ready to show by induction on m that T(G) = detQ11 holds for every multigraph G with at most m edges.

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Proofs working with determinants

▪ If in a multigraph G the vertex number 1 is not incident to any edge, then we have T(G) = 0.

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Proofs working with determinants

▪ If in a multigraph G the vertex number 1 is not incident to any edge, then we have T(G) = 0. ▪ And detQ11=0

2 −1 −1 −1 −1 2 −1 −1 2 2 −1 −1 −1 2 −1 −1 −1 2 𝑅11 𝑅

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Proofs working with determinants

▪ If in a multigraph G the vertex number 1 is not incident to any edge, then we have T(G) = 0. ▪ And detQ11=0

2 −1 −1 −1 −1 2 −1 −1 2 2 −1 −1 −1 2 −1 −1 −1 2 𝑅11 𝑅 Sum Sum

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Proofs working with determinants

▪ If in a multigraph G the vertex number 1 is not incident to any edge, then we have T(G) = 0. ▪ And detQ11=0

2 −1 −1 −1 2 −1 −1 −1 2 𝑅11 Sum

detQ11=0 T(G) = detQ11=0

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Proofs working with determinants

▪ If in a multigraph G the vertex number 1 is not incident to any edge, then we have T(G) = 0. ▪ (In In pa partic icula lar, r, wh when m = 0 , theorem holds, this is our base case.).

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Proofs working with determinants

▪ If the vertex number 1 is incident to at least one edge, then we fix

  • ne such edge, let us call it e, Assume e has endvertices 1 and 2 .
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Proofs working with determinants

▪ If the vertex number 1 is incident to at least one edge, then we fix one such edge, call it e. Assume e has endvertices 1 and 2 . ▪ According to Observation2, we have the following formula : Remember the Observation2 : Q′ ′11 = Q11,22

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Proofs working with determinants

▪ If the vertex number 1 is incident to at least one edge, then we fix one such edge, call it e. Assume e has endvertices 1 and 2 . ▪ According to Observation2, we have the following formula: ▪ the matrix Q’11 arises from Q 11 by adding the vector e1 = (1, 0, 0, . . . , 0) to the first row. Remember the Observation2 : Q′ ′11 = Q11,22 R: vertor e1 as it’s first row, the remaning part agrees with Q11

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Proofs working with determinants

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Proofs working with determinants

▪ From the three formula above, hence

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Proofs working with determinants

▪ From the three formula above, hence ▪ This completes the inductive step and hence we proof it.

  • So we have 𝑼 𝑯 = 𝐞𝐟𝐮 𝑹𝟐𝟐
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谢谢!

Q & A