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Article

Finding the Number of Spanning Trees in Specific Graph Sequences Generated by a Johnson Skeleton Graph

1
Department of Mathematics, Applied College at Mahail Aseer, King Khalid University, Abha 61421, Saudi Arabia
2
Department of Mathematics, Faculty of Science, Taibah University, Al-Madinah Al-Nunawara 41411, Saudi Arabia
3
Department of Mathematics and Computer Sciences, Faculty of Science, Menoufia University, Shebin El Kom 32511, Egypt
*
Author to whom correspondence should be addressed.
Mathematics 2025, 13(18), 3036; https://doi.org/10.3390/math13183036
Submission received: 7 August 2025 / Revised: 13 September 2025 / Accepted: 17 September 2025 / Published: 20 September 2025

Abstract

Using equivalent transformations, complicated circuits in physics that need numerous mathematical operations to analyze can be broken down into simpler equivalent circuits. It is also possible to determine the number of spanning trees—graph families in particular—using these adjustments and utilizing our knowledge of difference equations, electrically equivalent transformations, and weighted generating function rules. In this paper, we derive the exact formulas for the number of spanning trees of sequences of new graph families created by a Johnson skeleton graph 63 and a few of its related graphs. Lastly, a comparison is made between our graphs’ entropy and other graphs of average degree four.

1. Introduction

A spanning tree is a subgraph of an undirected, connected graph that has every vertex in the main graph G but only employs the fewest required edges to construct a tree structure (i.e., no cycles). It essentially connects every node in a network without generating unnecessary loops.
These days, physics has a function τ where the number of spanning trees τ ( G ) is employed as an invariant to calculate the entropy of certain networks associated with physical processes [1,2,3]. In the discipline of network analysis [4,5,6], τ is also used in relation to other metrics that show how reliable a network is when represented by graph G . Furthermore, there are numerous mathematical uses for the number of spanning trees τ(G). The current fastest approach, for instance, employs the scaling factor of the coordinate system to embed a three-connected planar graph as a 3 D polytope. There are many subgraphs within a fixed graph G . A graph with E ( G ) edges can actually have 2 E ( G ) different subgraphs. Some of these subgraphs are obviously trees. We are especially interested in a subset of these trees known as spanning trees. The practice of counting the number of spanning trees τ ( G ) of a graph G dates to 1842, when German mathematician Gustav Kirchhoff [7] established a connection between the number of spanning trees of a graph G and the determinant of a particular submatrix that is connected to it as follows:
For a connected graph G = ( V , E ) with n vertices, the Kirchhoff matrix L is an n × n characteristic matrix L = D A , where A is the adjacency matrix of G , and D is the diagonal matrix of the degrees of G , such that L = [ a i j ] is defined as follows:
L = [ a i j ] = deg ( v i ) i f i = j 1 i f ( v i , v j ) E ( G ) 0 i f ( v i , v j ) E ( G )
The number of spanning trees in a graph G is equal to each co-factor of L .
For big graphs, this approach is not practical. Because of this, people have devised ways to overcome challenges and have focused more on obtaining clear and straightforward formulas for certain classes of graphs. See [8,9,10]. Daoud [11] developed this technique and derived the explicit formula for counting the number of spanning trees of cartesian and composition products of complete and complete bipartite and tripartite graphs as well as the explicit formula for counting the number of spanning trees of classes of pyramid graphs generated by wheel and gear graphs [12].
Feussner’s recursive formula [13,14], the fundamental combinatorial concept for counting τ ( G ) in a graph G , is very simple to understand. Let e be any edge of an undirected simple graph G . Each spanning tree in G can be divided into two sections: all spanning trees without e as a tree edge are included in one section, and all spanning trees with e as a tree edge are included in the other.
The subgraph G e that results from taking a graph G and removing an edge e while leaving all other edges and vertices intact is represented by the first section, which has the same number of spanning trees as the graph. In the second section, the graph G . e (not a subgraph) is created by compressing the edge e = { u , v } until the two vertices u and v meet, and it has the same number of spanning trees as the graph. This new vertex is identified by u v .
Compared to G , both G e and G . e have fewer edges. Thus, it is possible to count the number of spanning trees in G in a recursive manner. Assume now that T ( G ) represents the collection of all spanning trees of G ; thus τ ( G ) = T ( G ) . This set consequently broke down into two disjoint sets T 1   and   T 2 , one of which T 1 consists of trees containing selected edge e E ( G ) , while the other T 2 consists of trees that do not contain e . It is evident that T 1 = T ( G . e ) since every edge of them matches a spanning tree of G . e and T 2 = T ( G e ) , because every one of its edges is a spanning tree of G e and inversely, τ ( G ) = τ ( G e ) + τ ( G . e ) . In 1889, British mathematician A. Cayley [15] determined how many spanning trees there are in a full graph: τ ( K n ) = n n 2 . It was demonstrated using a variety of methods, including some combinatorial techniques [16]. The explicit formula for calculating the number of spanning trees of chain graphs and wheel-related graphs was derived by Daoud [17,18] using this technique.

2. Electrically Equivalent Transformations

Kirchhoff was inspired to study electrical networks through the idea that an edge-weighted graph, with weights representing the conductance of the corresponding edges, may be considered an electrical network. The effect conductance between two vertices u , v can be expressed as the quotient of the (weighted) number of spanning trees and the (weighted) number of so-called thickets, spanning forests with exactly two components and the property that each component contains precisely one of the vertices u , v [19,20]. Using this technique, Daoud [21] has determined the number of spanning trees for certain pyramid graphs based on Fritsch graphs.
A few simple changes and their effects on the number of spanning trees are listed below. Here, τ G indicates the weighted number of spanning trees G . Let G be an edge-weighted graph and Γ the electrically equivalent graph that goes with it.
  • Parallel edges: The number of spanning trees in Γ , τ ( Γ ) , stays the same when two parallel edges in G with conductances u and v are combined into a single edge in Γ with a conductance of u + v .
  • Serial edges: The number of spanning trees in Γ , τ ( Γ ) , can be computed as ( 1 / ( u + v ) multiplied by τ ( G ) if two serial edges in G with conductances u and v are joined to form a single edge in Γ with a conductance of u v / ( u + v ) .
  • Δ-Y Transformation: The number of spanning trees in Γ , τ ( Γ ) , can be calculated as ( uv + vw + wu ) 2 / u v w multiplied by τ ( G ) , when a triangle in G with conductances u , v and w is converted into an electrically equivalent star graph in Γ with conductances x = ( uv + vw + w u ) / u , y = ( uv + vw + w u ) / v , and z = ( uv + vw + wu ) / w .
  • Y-Δ Transformation: The number of spanning trees in Γ , τ ( Γ ) , can be calculated as 1 / ( u + v + w ) multiplied by τ ( G ) . when a star graph in G , with conductances u , v and w , is converted into an electrically equivalent triangle in Γ with conductances x = v w / ( u + v + w ) , y = u w / ( u + v + w ) , and z = u v / ( u + v + w ) .

3. Main Results

A Johnson graph is a specific kind of undirected graph that is defined using systems of sets. Two vertices (subsets) are close when they meet and contain ( k 1 ) -elements. The k   element subsets of an n   element collection are the vertices of the Johnson graph J ( n , k ) . In other words, the Johnson graph J ( n , k ) has vertices given by the k-subsets of { 1,2 , , n } , with two vertices connected if and only if their intersection has size k 1 . The Johnson skeleton graph 63 is a minimal unit-distance forbidden graph.
This study will identify the number of spanning trees in the graph sequences, J S n , generated by the Johnson skeleton graph 63 and two related graph sequences, R 1 J S n and R 2 J S n , generated by two graphs associated with Johnson skeleton graph 63; these are defined as follows:
The first Johnson-skeleton-related graph is a graph that is produced by replacing the internal triangle of Johnson skeleton graph 63 with a star (3,3)-gon graph. See Figure 1b.
The second Johnson-skeleton-related graph is a graph that is produced by replacing the internal triangle of Johnson skeleton graph 63 with another Johnson skeleton graph 63. See Figure 1c.

3.1. The Number of Spanning Trees in the Graph Sequence J S n

The graph sequence J S 1 , J S 2 , , J S n is a recursive definition using the graphs J S 2 and J S 1 (triangle or K 3 ): A replica of J S 2 is used in place of the middle triangle of J S 2 to create the graph J S 3 . The central triangle in the graph J S n 1 is typically swapped out for J S 2 to make J S n as shown in Figure 2. V ( J S n ) = 27 n 24 and E ( J S n ) = 54 n 51 , n = 1,2 , are the total vertices and edges of J S n , respectively. According to this architecture in the large n limit, the average degree of J S n is 4.
Theorem 1.
For n 1 , the number of spanning trees in the graph sequence J S n  is determined by
3 × 5984 n 1 70841449 + 738172 9210 34969 n 1 19080 + 199 9210 11 60 9210 15 70841449 + 738172 9210 34969 n 1 1349 + 14 9210 1815 2
12463 2 + 79739 15 614 2 5953 + 62 9210 n 2 + 12463 2 79739 15 614 2 5953 62 9210 n 2 2
Proof. 
We convert J S i to J S i 1 using the electrically equivalent transformation. The process of change from J S 2 to J S 1 is depicted in Figure 3.
When the ten adjustments listed above are combined, we obtain
τ ( J S 2 ) = 1 9 4 a × 4 9 × ( 3 a + 1 ) 3 × ( 11 4 ) 9 × ( ( 9 a + 2 ) ( 3 a + 1 ) ) 3 × ( 18 11 ) 3 × 18 a ( 9 a + 2 ) × ( 99 a + 22 ) 9 ( 208 a + 45 ) × ( 930 a + 203 99 a + 22 ) 3 × 306 ( 208 a + 45 ) 11 ( 930 a + 203 ) τ ( J S 1 )
Thus
τ ( J S 2 ) = 5984 ( 10230 P 2 + 2233 ) 2   τ ( J S 1 ) .
Further
τ J S n = i = 2 n 5984 ( 10230 P i + 2233 ) 2 τ ( J S 1 ) ,   = 3 × 598 4 n 1 P 1 2 [   i = 2 n ( 10230 P i + 2233 ) ] 2
where p i 1 = 9673 p i + 2108 10230 p i + 2233 , i = 2,3 , , n . The characteristic equation for this is like 10230 r 2 7440 r 2108 = 0 with roots r 1 = 60 9210 165 and r 2 = 60 + 9210 165 . When two roots are subtracted from both sides of p i 1 = 9673 p i + 2108 10230 p i + 2233 , we get
p i 1 60 9210 165 = 9673 p i + 2108 10230 p i + 2233 60 9210 165 = ( 5953 + 62 9210 ) . p i ( 60 9210 165 ) 10230 p i + 2233
p i 1 60 + 9210 165 = 9673 p i + 2108 10230 p i + 2233 60 + 9210 165 = ( 5953 62 9210 ) . p i ( 60 + 9210 165 ) 10230 p i + 2233
Let q i = p i 60 9210 165 p i 60 + 9210 165 . Then, by Equations (3) and (4), we get q i 1 = ( 70841449 + 738172 9210 34969 ) q i and q i 1 = ( 70841449 + 738172 9210 34969 ) n i q n . Therefore, p i = ( 70841449 + 73817 9210 34969 ) n i ( 60 + 9210 165 ) q n 60 9210 165 ( 70841449 + 73817 9210 34969 ) n i q n 1 . Thus
p 1 = ( 70841449 + 73817 9210 34969 ) n 1 ( 60 + 9210 165 ) q n 60 9210 165 ( 70841449 + 73817 9210 34969 ) n 1 q n 1 .
Using the formula p n 1 = 9673 p n + 2108 10230 x n + 2233 and denoting the coefficients of 9673 p n + 2108 and 10230 p n + 2233 as δ n and σ n , we have
10230 p n + 2233 = δ 0 ( 9673 p n + 2108 ) + σ 0 ( 10230 p n + 2233 ) , 10230 p n 1 + 2233   = δ 1 ( 9673 p n + 2108 ) + σ 1 ( 10230 p n + 2233 ) δ 0 ( 9673 p n + 2108 ) + σ 0 ( 10230 p n + 2233 ) , 10230 p n 2 + 2233 = δ 2 ( 9673 p n + 2108 ) + σ 2 ( 10230 p n + 2233 ) δ 1 ( 9673 p n + 2108 ) + σ 1 ( 10230 p n + 2233 ) , 10230 p n i + 2233 = δ i ( 9673 p n + 2108 ) + σ i ( 10230 p n + 2233 ) δ i 1 ( 9673 p n + 2108 ) + σ i 1 ( 10230 p n + 2233 ) ,
10230 p n ( i + 1 ) + 2233 = δ i + 1 ( 9673 p n + 2108 ) + σ i + 1 ( 10230 p n + 2233 ) δ i ( 9673 p n + 2108 ) + σ i ( 10230 p n + 2233 ) , 10230 p 2 + 2233 = δ n 2 ( 9673 p n + 2108 ) + σ n 2 ( 10230 p n + 2233 ) δ n 3 ( 9673 p n + 2108 ) + σ n 3 ( 10230 p n + 2233 ) ,
Thus, we get
τ ( J S n ) = 3 × 598 4 n 1 p 1 2 [ δ n 2 ( 9673 p n + 2108 ) + σ n 2 ( 10230 p n + 2233 ) ] 2
where δ 0 = 0 , σ 0 = 1 and δ 1 = 10230 , σ 1 = 2233 . By the expression p n 1 = 9673 p n + 2108 10230 p n + 2233 and using Equations (6) and (7), we have
δ i + 1 = 26 δ i δ i 1 ;   σ i + 1 = 26 σ i σ i 1
Equation (9) has a characteristic equation of t 2 11906 t + 34969 = 0 with roots t 1 = 5953 + 62 9210 and t 2 = 5953 62 9210 . The general solutions of Equation (9) are δ i = a 1 t 1 i + a 2 t 2 i ;   σ i = b 1 t 1 i + b 2 t 2 i . Using the initial conditions δ 0 = 0 , σ 0 = 1 and δ 1 = 10230 , σ 1 = 2233 , yields
δ i = 11 9210 1228 ( 5953 + 62 9210 ) i 11 9210 1228 ( 5953 62 9210 ) i ; σ i = ( 307 2 9210 614 ) ( 5953 + 62 9210 ) i + ( 307 + 2 9210 614 ) ( 5953 62 9210 ) i
Should p n = 1 ,   J S n is devoid of any electrically equivalent transformation. Entering (10) into Equation (8), we get
τ J S n = 3 × 5984 n 1   p 1 2 12463 2 + 79739 15 614 2 5953 + 62 9210 n 2 + 12463 2 79739 15 614 2 5953 62 9210 n 2 2 , n 2
When n = 1 , τ ( J S 1 ) = 3 , which satisfies Equation (11). Therefore, the number of spanning trees in the sequence of the graph J S n is given by
τ J S n = 3 × 5984 n 1   p 1 2 12463 2 + 79739 15 614 2 5953 + 62 9210 n 2 + 12463 2 79739 15 614 2 5953 62 9210 n 2 2 , n 1
where
p 1 = ( 70841449 + 738172 9210 34969 ) n 1 ( 19080 + 199 9210 ) 11 ( 60 9210 ) 15 ( 70841449 + 738172 9210 34969 ) n 1 ( 1349 + 14 9210 ) 1815 , n 1
Equation (13) is inserted into Equation (12), yielding the desired result. □

3.2. The Number of Spanning Trees in the Graph Sequence R 1 J S n

The graph sequence R 1 J S 1 , R 1 J S 2 , , R 1 J S n is a recursive definition using the graphs R 1 J S 2 and R 1 J S 1 (triangle or K 3 ): A replica of R 1 J S 2 is used in place of the middle triangle of R 1 J S 2 to create the graph R 1 J S 3 . The central triangle in the graph R 1 J S n 1 is typically swapped out for R 1 J S 2 to make R 1 J S n , as shown in Figure 4. V ( R 1 J S n ) = 39 n 36 and E ( R 1 J S n ) = 78 n 75 , n = 1,2 , are the total vertices and edges of R 1 J S n , respectively. According to this architecture in the large n limit, the average degree of R 1 J S n is 4 .
Theorem 2.
For n 1 , the number of spanning trees in the sequence of the graph R 1 J S n  is given by 3 × 9718272 n 1
11480479303 + 151532 5739992547 494209 n 1 1944411145 + 25706 5739992547 1517 20488 5739992547 11480479303 + 151532 5739992547 494209 n 1 2068303018 + 27223 5739992547 154972169 2
157435 2 + 3975908667 3 1913330849 2 75766 + 5739992547 n 2 + 157435 2 3975908667 3 1913330849 2 75766 5739992547 n 2 2
Proof. 
We convert R 1 J S i to R 1 J S i 1 using the electrically equivalent transformation. The process of change from R 1 J S 2 to R 1 J S 1 is depicted in Figure 5.
When the sixteen modifications mentioned above are combined, the result is:
τ R 1 J S 2 = 3 12 × a 3 9 9 2 a + 1 6 × 6 9 × 4 a + 2 3 × 11 3 9 × 8 a + 3 3 a 3 × 2 3 3 11 × 2 2 a + 1 × 111 22 9 × 2 a + 1 24 a + 13 16 a + 6 3 × 54 37 3 × 36 a + 18 24 a + 13 × 888 a + 481 9 1849 a + 1000 × 8283 a + 4482 888 a + 481 3 × 342 1849 a + 1000 37 2761 a + 1494 τ ( R 1 J S 1 )
Thus, we have
τ ( R 1 J S 2 ) = 9718272 ( 102157 P 2 + 55278 ) 2 τ ( R 1 J S 1 ) .
Further
τ ( R 1 J S n ) = i = 2 n 9718272 ( 102157 P i + 55278 ) 2 τ ( R 1 J S n ) = 3 × 71827 2 n 1 P 1 2 [   i = 2 n ( 102157 P i + 55278 ) ] 2
where p i 1 = 96254 p i + 52079 102127 p i + 55278 , i = 2,3 , , n . Its characteristic equation is 102157   r 2 40976   r 52079 = 0 with roots r 1 = 20488 5739992547 102157 and r 2 = 20488 5739992547 102157 . Subtracting these two roots into both sides of p i 1 = 96254 p i + 52079 102127 p i + 55278 , we get
p i 1 20488 5739992547 102157 = 96254 p i + 52079 102127 p i + 55278 20488 5739992547 102157 = ( 75766 + 5739992547 ) . p i 20488 5739992547 102157 102157 ( 10257 p i + 55278 )
p i 1 20488 + 5739992547 102157 = 96254 p i + 52079 102127 p i + 55278 20488 + 5739992547 102157 = ( 75766 5739992547 ) . p i   20488 + 5739992547 102157 102157 ( 10257 p i + 55278 )
Let q i = p i 20488 5739992547 102157 p i 20488 + 5739992547 102157 . Then by Equations (16) and (17), we get q i 1 = ( 11480479303 + 151532 5739992547 494209 ) q i and q i 1 = ( 11480479303 + 151532 5739992547 494209 ) n i q n .
Therefore
p i = ( 11480479303 + 151532 5739992547 494209 ) n i ( 20488 + 5739992547 102157 ) q n 20488 5739992547 102157 ( 11480479303 + 151532 5739992547 494209 ) n i q n 1
Thus
p 1 = ( 11480479303 + 151532 5739992547 494209 ) n 1 ( 20488 + 5739992547 102157 ) q n 20488 5739992547 102157 ( 11480479303 + 151532 5739992547 494209 ) n 1 q n 1
Using the expression p n 1 = 96254 p n + 52079 102157 x n + 55278 and denoting the coefficients of 96254 p n + 52079 and 102157 p n + 55278 as δ n and σ n , we have
102157 p n + 55278 = δ 0 ( 96254 p n + 52079 ) + σ 0 ( 102157 p n + 55278 ) , 102157 p n 1 + 55278 = δ 1 ( 96254 p n + 52079 ) + σ 1 ( 102157 p n + 55278 ) δ 0 ( 96254 p n + 52079 ) + σ 0 ( 102157 p n + 55278 ) , 102157 p n 2 + 55278 = δ 2 ( 96254 p n + 52079 ) + σ 2 ( 102157 p n + 55278 ) δ 1 ( 96254 p n + 52079 ) + σ 1 ( 102157 p n + 55278 ) ,
102157 p n i + 55278 = δ i ( 96254 p n + 52079 ) + σ i ( 102157 p n + 55278 ) δ i 1 ( 96254 p n + 52079 ) + σ i 1 ( 102157 p n + 55278 ) ,
102157 p n ( i + 1 ) + 55278 = δ i + 1 ( 96254 p n + 52079 ) + σ i + 1 ( 102157 p n + 55278 ) δ i ( 96254 p n + 52079 ) + σ i ( 102157 p n + 55278 ) , 102157 p 2 + 55278 = δ n 2 ( 96254 p n + 52079 ) + σ n 2 ( 102157 p n + 55278 ) δ n 3 ( 96254 p n + 52079 ) + σ n 3 ( 102157 p n + 55278 ) ,
Thus, we obtain
τ ( R 1 J S n ) = 3 × 971827 2 n 1 p 1 2 [ δ n 2 ( 96254 p n + 52079 ) + σ n 2 ( 102157 p n + 55278 ) ] 2
where δ 0 = 0 , σ 0 = 1 and δ 1 = 102157 , σ 1 = 55278 . By the expression p n 1 = 96254 p n + 52079 102157 p n + 55278 and using Equations (19) and (20), we have
δ i + 1 = 151532 δ i 494209 δ i 1 ; σ i + 1 = 151532 σ i 494209 σ i 1
The characteristic equation of Equation (22) is t 2 151532 t + 494209 = 0 with roots t 1 = 75766 + 5739992547 and t 2 = 75766 5739992547 . The general solutions of Equation (22) are δ i = a 1 t 1 i + a 2 t 2 i ;   σ i = b 1 t 1 i + b 2 t 2 i . Using the initial conditions δ 0 = 0 , σ 0 = 1 and δ 1 = 102157 , σ 1 = 55278 , yields
δ i = 102157 5739992547 11479985094 ( 75766 + 5739992547 ) i 102157 5739992547 11479985094 ( 75766 5739992547 ) i ; σ i = ( 5739992547 20488 5739992547 11479985094 ) ( 75766 + 5739992547 ) i + ( 5739992547 + 20488 5739992547 11479985094 ) ( 75766 5739992547 ) i
If p n = 1 , it means that R 1 J S n is without any electrically equivalent transformation. Plugging Equation (23) into Equation (21), we have
τ R 1 J S n = 3 × ( 9718272 ) n 1   p 1 2 ( 157435 2 + 3975908667 3 1913330849 2 ) ( 75766 + 5739992547 ) n 2 + ( 157435 2 3975908667 3 1913330849 2 ) ( 75766 5739992547 ) n 2 2 , n 2
When n = 1 , τ ( R 1 J S 1 ) = 3 , which satisfies Equation (24). Therefore, the number of spanning trees in the sequence of the graph R 1 J S n is given by
R 1 J S n = 3 × ( 9718272 ) n 1   p 1 2 ( 157435 2 + 3975908667 3 1913330849 2 ) ( 75766 + 5739992547 ) n 2 + ( 157435 2 3975908667 3 1913330849 2 ) ( 75766 5739992547 ) n 2 2 , n 1
where
p 1 = ( 11480479303 + 151532 5739992547 494209 ) n 1 ( 1944411145 + 25706 5739992547 ) 1517 ( 20488 5739992547 ) ( 11480479303 + 151532 5739992547 494209 ) n 1 ( 2068303018 + 27223 5739992547 ) 154972169 ,   n 1
Equation (26) is inserted into Equation (25), yielding the desired outcome. □

3.3. The Number of Spanning Trees in the Graph Sequence R 2 J S n

The graph sequence R 2 J S 1 , R 2 J S 2 , , R 2 J S n is a recursive definition using the graphs R 2 J S 2 and R 2 J S 1 (triangle or K 3 ): A replica of R 2 J S 2 is used in place of the middle triangle of R 2 J S 2 to create the graph R 2 J S 3 . The central triangle in the graph R 2 J S n 1 is typically swapped out for R 2 J S 2 to make R 2 J S n , as shown in Figure 6. V (   R 2 J S n ) = 51 n 48 and E (   R 2 J S n ) = 90 n 87 , n = 1,2 , are the total vertices and edges of R 2 J S n , respectively. According to this architecture in the large n limit, the average degree of R 2 J S n is 3.53 .
Theorem 3.
For n 1 , the number of spanning trees in the graph sequence R 2 J S n  is given by
3 × 40974336 n 1 × ( 1682323726009 + 115437539 212385577 17570592 ) n 1 × 1748546196125 + 120105233 212385577 180183255712 830867 89 212385577 2260088 ( 1682323726009 + 115437539 212385577 17570592 ) n 1 ( 1862489411129 + 127200669 212385577 180183255712 ) 1 2
( 681568 + 884019670672 89 212385577 ) ( 1297051 + 89 212385577 2 ) n 2 + ( 681568 884019670672 89 212385577 ) ( 1297051 89 212385577 2 ) n 2 2
Proof. 
We convert R 2 J S i to R 2 J S i 1 using the electrically equivalent transformation. The process of change from R 2 J S 2 to R 2 J S 1 is depicted in Figure 7.
When the seventeen modifications mentioned above are combined, the result is:
τ ( R 2 J S 2 ) = [ 1 9 4 a × ( 4 ) 9 × ( 3 a + 1 ) 3 × ( 11 4 ) 9 × ( 9 a + 2 3 a + 1 ) 3 × ( 18 11 ) 3 × ( 18 a 9 a + 2 ) × 11 3 9 4 × 6 3 × ( 9 a + 2 5 a + 1 ) × ( 29 11 ) 9 × ( 24 a + 5 9 a + 2 ) 3 × ( 76 29 ) 9 × ( 13 + 63 a 24 a + 5 ) 3 × ( 27 19 ) 3 × ( 6 ( 15 a + 3 ) 63 a + 13 ) × 1 9 ( 4788 a + 988 9955 a + 2053 )       × ( 44607 a + 9201 76 ( 63 a + 13 ) ) 3 × ( 351 ( 9955 a + 2053 ) 38 ( 14869 a + 3067 ) ) ] τ ( R 2 J S 1 )
Thus, we have
τ ( R 2 J S 2 ) = 40974336 ( 1130044 P 2 + 233092 ) 2 τ ( R 2 J S 1 ) .
Further
τ ( R 2 J S n ) = i = 2 n 40974336 ( 1130044 P i + 233092 ) 2 τ ( R 2 J S 1 ) = 3 × 4097433 6 n 1 P 1 2 [ i = 2 n ( 1130044 P i + 233092 ) ] 2 ,
where p i 1 = 1063959 p i + 219453 1130044 p i + 233092 , i = 2,3 , , n . Its characteristic equation is 1130044 r 2 830867 r 219453 = 0 with roots are r 1 = 830867 89 212385577 22690088 and r 2 = 830867 + 89 212385577 2260088 . Subtracting these two roots into both sides of p i 1 = 1063959 p i + 219453 1130044 p i + 233092 , we get
p i 1 830867 89 212385577 2260088 = 1063959 p i + 219453 1130044 p i + 233092 830867 89 212385577 2260088 = ( 1297051 + 89 212385577 ) . p i 830867 89 212385577 2260088 2 ( 1130044 p i + 233092 )
p i 1 830867 + 89 212385577 2260088 = 1063959 p i + 219453 1130044 p i + 233092 830867 + 89 212385577 2260088 = ( 1297051 89 212385577 ) . p i 830867 + 89 212385577 2260088 2 ( 1130044 p i + 233092 )
Let q i = p i 830867 89 212385577 2260088 p i 830867 + 89 212385577 2260088 . Then, by Equations (29) and (30), we get
q i 1 = ( 1682323726009 + 115437539 212385577 17570592 ) q i
And
q i 1 = ( 1682323726009 + 115437539 212385577 17570592 ) n i q n
Therefore
p i = ( 1682323726009 + 115437539 212385577 17570592 ) n i ( 830867 + 89 212385577 2260088 ) q n 830867 89 212385577 2260088 ( 1682323726009 + 115437539 212385577 17570592 ) n i   q n 1 .
Thus
p 1 = ( 1682323726009 + 115437539 212385577 17570592 ) n 1 ( 830867 + 89 212385577 2260088 )   q n 830867 89 212385577 2260088 ( 1682323726009 + 115437539 212385577 17570592 ) n 1   q n 1
Using the expression p i 1 = 1063959 p i + 219453 1130044 p i + 233092 and denoting the coefficients of 1063959 p n + 219453 and 1130044 p n + 233092 as δ n and σ n , we have
1130044 p n + 233092 = δ 0 1063959 p n + 219453 + σ 0 1130044 p n + 233092 , 1130044 p n 1 + 233092 = δ 1 1063959 p n + 219453 + σ 1 1130044 p n + 233092 δ 0 1063959 p n + 219453 + σ 0 1130044 p n + 233092 , 1130044 p n 2 + 233092 = δ 2 1063959 p n + 219453 + σ 2 1130044 p n + 233092 δ 1 1063959 p n + 219453 + σ 1 1130044 p n + 233092 , 1130044 p n i + 233092 = δ i ( 1063959 p n + 219453 ) + σ i ( 1130044 p n + 233092 ) δ i 1 ( 1063959 p n + 219453 ) + σ i 1 ( 1130044 p n + 233092 ) ,
1130044 p n ( i + 1 ) + 233092 = δ i + 1 ( 1063959 p n + 219453 ) + σ i + 1 ( 1130044 p n + 233092 ) δ i ( 1063959 p n + 219453 ) + σ i ( 1130044 p n + 233092 ) , 1130044 p 2 + 233092 = δ n 2 ( 1063959 p n + 219453 ) + σ n 2 ( 1130044 p n + 233092 ) δ n 3 ( 1063959 p n + 219453 ) + σ n 3 ( 1130044 p n + 233092 ) ,
Thus, we obtain
τ R 2 J S n = 3 × 4097433 6 n 1 p 1 2 × [ δ n 2 ( 1063959 p n + 219453 ) + σ n 2 ( 1130044 p n + 233092 ) ] 2
where δ 0 = 0 , σ 0 = 1 and δ 1 = 1130044 , σ 1 = 233092 . By the expression p n 1 = 1063959 p n + 219453 1130044 p n + 233092 and using Equations (32) and (33), we have
δ i + 1 = 1297051 δ i 8785296 δ i 1 ; σ i + 1 = 1297051 σ i 8785296 σ i 1
The characteristic equation of Equation (35) is t 2 1297051 t + 8785296 = 0 with roots t 1 = 1297051 + 89 212385577 2 and t 2 = 1297051 89 212385577 2 . The general solutions of Equation (35) are δ i = a 1 t 1 i + a 2 t 2 i ; σ i = b 1 t 1 i + b 2 t 2 i . Using the initial conditions δ 0 = 0 , σ 0 = 1 and δ 1 = 1130044 , σ 1 = 233092 , yields
δ i = 1130044 212385577 18902316353 ( 1297051 + 89 212385577 2 ) i 1130044 212385577 18902316353 ( 1297051 89 212385577 2 ) i ; σ i = ( 18902316353 830867 212385577 37804632706 ) ( 1297051 + 89 212385577 2 ) i + ( 18902316353 + 830867 212385577 37804632706 ) ( 1297051 89 212385577 2 ) i
If p n = 1 , it means that R 2 J S n is without any electrically equivalent transformation. Plugging Equation (36) into Equation (34), we have
τ R 2 J S n = 3 × 40974336 n 1   p 1 2 × ( 681568 + 884019670672 89 212385577 ) ( 1297051 + 89 212385577 2 ) n 2 + ( 681568 884019670672 89 212385577 ) ( 1297051 89 212385577 2 ) n 2 2 , n 2
When n = 1 , τ ( R 2 J S 1 ) = 3 , which satisfies Equation (37). Therefore, the number of spanning trees in the sequence of the graph R 2 J S n is given by
τ R 2 J S n = 3 × 40974336 n 1 p 1 2 × ( 681568 + 884019670672 89 212385577 ) ( 1297051 + 89 212385577 2 ) n 2 + ( 681568 884019670672 89 212385577 ) ( 1297051 89 212385577 2 ) n 2 2 , n 1
where
p 1 = ( 1682323726009 + 115437539 212385577 17570592 ) n 1 × 1748546196125 + 120105233 212385577 180183255712 830867 89 212385577 2260088 ( 1682323726009 + 115437539 212385577 17570592 ) n 1 ( 1862489411129 + 127200669 212385577 180183255712 ) 1 n 1
Equation (39) can be inserted into Equation (38), yielding the desired result. □

4. Numerical Results

The values of the number of spanning trees in the sequence graphs J S n , R 1 J S n , and R 2 J S n are shown in the following Table 1, Table 2 and Table 3:

5. Spanning Tree Entropy

Once we have exact formulas for the number of spanning trees of the three sequence graphs J S n , R 1 J S n , and R 2 J S n , we can compute the spanning tree entropy Z, a finite number, and an interesting metric defining the network topology. In [10,22], this is explained as follows: Regarding graph G ,
Z ( G ) = l i m n ln τ ( G ) V ( G ) .
Z J S n = 1 27   l n 5984 + 2 l n 5953 + 62 9210   = 1.01726 , Z R 1 J S n = 1 39   l n 9718272 + 2 l n 75766 + 5739992547   = 1.02427 , Z R 2 J S n = 1 51 (   l n [ 54618462093312 ] + 2 l n 1297051 + 89 212385577   ) = 1.19949 .
We now compare our sequence graphs’ entropy values to those of other graphs. It is evident that the R 2 J S n graph has a higher entropy than the other two graphs, whereas the J S n graph has a lower entropy. Furthermore, the entropy of the two-dimensional Sierpinski gasket [23] and the fractal scale free lattice [20] both have entropies of 1.166 and 1.040 and are of the same average degree 4, respectively, while the entropy of the R 2 J S n graph is greater than that of the fractal scale free lattice and lower than that of the two dimensional Sierpinski gasket.

6. Conclusions

In this study, we used electrically equivalent transformations to determine the number of spanning trees of sequence graphs produced from the Johnson skeleton graph and other related graphs. This technique’s strength is its ability to avoid the laborious computation of Laplacian spectra, which is a requirement for a general approach to spanning tree determination. Furthermore, our findings indicate a relationship between the entropy and the graph’s average degree.

Author Contributions

Conceptualization, A.A.; Methodology, A.A. and S.N.D.; Software, A.A. and S.N.D.; Validation, A.A. and S.N.D.; Formal analysis, A.A. and S.N.D.; Investigation, A.A. and S.N.D.; Resources, A.A. and S.N.D.; Data curation, A.A. and S.N.D.; Writing—original draft, A.A. and S.N.D.; Writing—review & editing, A.A. and S.N.D.; Visualization, A.A. and S.N.D.; Supervision, A.A. and S.N.D.; Project administration, A.A. and S.N.D.; Funding acquisition, A.A. All authors have read and agreed to the published version of the manuscript.

Funding

Deanship of Scientific Research at King Khalid University. (Project under grant number (RGP.2/372/45).

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Larg Groups. (Project under grant number (RGP.2/372/45)). The authors wish to extend their gratitude to the anonymous editors and referees for their valuable feedback, which significantly enhanced the quality of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Johnson Skeleton graph 63 and two related graphs.
Figure 1. Johnson Skeleton graph 63 and two related graphs.
Mathematics 13 03036 g001
Figure 2. The graph J S 2 .
Figure 2. The graph J S 2 .
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Figure 3. The transformations from JS2 to JS1. (a) The graph J S 2 . (b) The graph Γ 1 . By applying the rule of Δ-Y transformation, we arrive at τ ( Γ 1 ) = 9 4   p 2 τ ( J S 2 ) . (c) The graph Γ 2 . By using the serial edges rule, we arrive at: τ Γ 2 = 1 4 9 1 3 p 2 + 1 3 τ ( Γ 1 ) . (d) The graph Γ 2 . Utilizing the Y-Δ transformation rule, we get: τ Γ 3 = 4 11 9 3 p 2 + 1 9 p 2 + 2 3 τ ( Γ 2 ) . (e) The graph Γ 4 . Using the rule of parallel edges, we get: τ ( Γ 4 ) = τ ( Γ 3 ) . (f) The graph Γ 5 . Applying the rule of Y-Δ transformation, we obtain: τ ( Γ 5 ) = 11 18 3 9 p 2 + 2 18 p 2 τ ( Γ 4 ) . (g) The graph Γ 6 . Using the rule of parallel edges, we get: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . With the use of the Δ-Y transformation rule, we get: τ ( Γ 7 ) = 9 208 p 2 + 45 99 p 2 + 22 τ ( Γ 6 ) . (i) The graph Γ 8 . Utilizing the Y-Δ rule, we arrive at: τ ( Γ 8 ) = ( 99 p 2 + 22 930 p 2 + 203 ) 3   τ ( Γ 7 ) . (j) The graph Γ 9 . Using the rule of parallel edges, we get: τ ( Γ 9 ) = τ ( Γ 8 ) . (k) The graph Γ 10 . When we use the Y-Δ rule, we get: τ ( Γ 10 ) = 11 ( 930 p 2 + 203 ) 306 ( 208 p 2 + 45 ) τ ( Γ 9 ) . (l) The graph Γ 11 = J S 1 . Using the rule of parallel edges, we get: τ ( Γ 11 ) = τ ( Γ 10 ) .
Figure 3. The transformations from JS2 to JS1. (a) The graph J S 2 . (b) The graph Γ 1 . By applying the rule of Δ-Y transformation, we arrive at τ ( Γ 1 ) = 9 4   p 2 τ ( J S 2 ) . (c) The graph Γ 2 . By using the serial edges rule, we arrive at: τ Γ 2 = 1 4 9 1 3 p 2 + 1 3 τ ( Γ 1 ) . (d) The graph Γ 2 . Utilizing the Y-Δ transformation rule, we get: τ Γ 3 = 4 11 9 3 p 2 + 1 9 p 2 + 2 3 τ ( Γ 2 ) . (e) The graph Γ 4 . Using the rule of parallel edges, we get: τ ( Γ 4 ) = τ ( Γ 3 ) . (f) The graph Γ 5 . Applying the rule of Y-Δ transformation, we obtain: τ ( Γ 5 ) = 11 18 3 9 p 2 + 2 18 p 2 τ ( Γ 4 ) . (g) The graph Γ 6 . Using the rule of parallel edges, we get: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . With the use of the Δ-Y transformation rule, we get: τ ( Γ 7 ) = 9 208 p 2 + 45 99 p 2 + 22 τ ( Γ 6 ) . (i) The graph Γ 8 . Utilizing the Y-Δ rule, we arrive at: τ ( Γ 8 ) = ( 99 p 2 + 22 930 p 2 + 203 ) 3   τ ( Γ 7 ) . (j) The graph Γ 9 . Using the rule of parallel edges, we get: τ ( Γ 9 ) = τ ( Γ 8 ) . (k) The graph Γ 10 . When we use the Y-Δ rule, we get: τ ( Γ 10 ) = 11 ( 930 p 2 + 203 ) 306 ( 208 p 2 + 45 ) τ ( Γ 9 ) . (l) The graph Γ 11 = J S 1 . Using the rule of parallel edges, we get: τ ( Γ 11 ) = τ ( Γ 10 ) .
Mathematics 13 03036 g003aMathematics 13 03036 g003bMathematics 13 03036 g003cMathematics 13 03036 g003dMathematics 13 03036 g003e
Figure 4. The graph R 1 J S 2 .
Figure 4. The graph R 1 J S 2 .
Mathematics 13 03036 g004
Figure 5. The transformations from R 1 J S 2 to R 1 J S 2 . (a) The graph R 1 J S 2 . (b) The graph Γ 1 . Applying the Y-Δ rule yields: τ Γ 1 = 1 3 12 τ R 1 J S 2 . (c) The graph Γ 2 . By applying the parallel edge rule, we obtain: τ ( Γ 2 ) = τ ( Γ 1 ) . (d) The graph Γ 3 . When the Δ-Y transformation rule is applied, we obtain: τ Γ 3 = 9 9 2 p 2 + 1 2 p 2 3 τ Γ 2 . (e) The graph Γ 4 . Using the rule of serial edges, we get: τ Γ 4 =   1 6   9 1 4 p 2 + 2 3 τ ( Γ 3 ) . (f) The graph Γ 5 . Applying the Y-Δ transformation rule yields the following results: τ Γ 5 = 3 11 9 3 p 2 8 p 2 + 3 3 τ ( Γ 4 ) . (g) The graph Γ 6 . Utilizing the parallel edge rule, we arrive at: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . Upon applying the Δ-Y transformation rule, we get: τ ( Γ 7 ) = 9 3 2 3 9 2 p 2 + 1 2 τ ( Γ 6 ) . (i) The graph Γ 8 . According to the Y-Δ transformation rule, we get:   τ Γ 8 = 22 111 9 16 p 2 + 6 2 p 2 + 1 24 p 2 + 13 3 τ ( Γ 7 ) . (j) The graph Γ 9 . Applying the rule of parallel edges, we arrive at:   τ ( Γ 9 ) = τ ( Γ 8 ) . (k) The graph Γ 10 . Using the Y-Δ transformation rule, we obtain: τ ( Γ 10 ) =   37 54   3   24 p 2 + 13 36 p 2 + 18   τ ( Γ 9 ) . (l) The graph Γ 11 . The rule of parallel edges is applied, and we get: τ ( Γ 11 ) = τ ( Γ 10 ) . (m) The graph Γ 12 . The Δ-Y transformation rule gives us: τ ( Γ 12 ) = 9 1849 p 2 + 1000 888 p 2 + 481 τ ( Γ 11 ) . (n) The graph Γ 13 . By applying the Y-Δ transformation rule, we arrive at: τ ( Γ 13 ) = ( 888 p 2 + 481 8283 p 2 + 4482 ) 3   τ ( Γ 12 ) . (o) The graph Γ 14 . When we apply the rule of parallel edges, we obtain:   τ ( Γ 14 ) = τ ( Γ 13 ) . (p) The graph Γ 15 . When we use the Y-Δ transformation rule, we get: τ Γ 15 = 37 2761 p 2 + 1494 342 1849 p 2 + 1000 τ ( Γ 14 ) . (q) The graph Γ 16 = R 1 J S 1 . Applying the parallel edge rule yields the following results: τ ( Γ 16 ) = τ ( Γ 15 ) .
Figure 5. The transformations from R 1 J S 2 to R 1 J S 2 . (a) The graph R 1 J S 2 . (b) The graph Γ 1 . Applying the Y-Δ rule yields: τ Γ 1 = 1 3 12 τ R 1 J S 2 . (c) The graph Γ 2 . By applying the parallel edge rule, we obtain: τ ( Γ 2 ) = τ ( Γ 1 ) . (d) The graph Γ 3 . When the Δ-Y transformation rule is applied, we obtain: τ Γ 3 = 9 9 2 p 2 + 1 2 p 2 3 τ Γ 2 . (e) The graph Γ 4 . Using the rule of serial edges, we get: τ Γ 4 =   1 6   9 1 4 p 2 + 2 3 τ ( Γ 3 ) . (f) The graph Γ 5 . Applying the Y-Δ transformation rule yields the following results: τ Γ 5 = 3 11 9 3 p 2 8 p 2 + 3 3 τ ( Γ 4 ) . (g) The graph Γ 6 . Utilizing the parallel edge rule, we arrive at: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . Upon applying the Δ-Y transformation rule, we get: τ ( Γ 7 ) = 9 3 2 3 9 2 p 2 + 1 2 τ ( Γ 6 ) . (i) The graph Γ 8 . According to the Y-Δ transformation rule, we get:   τ Γ 8 = 22 111 9 16 p 2 + 6 2 p 2 + 1 24 p 2 + 13 3 τ ( Γ 7 ) . (j) The graph Γ 9 . Applying the rule of parallel edges, we arrive at:   τ ( Γ 9 ) = τ ( Γ 8 ) . (k) The graph Γ 10 . Using the Y-Δ transformation rule, we obtain: τ ( Γ 10 ) =   37 54   3   24 p 2 + 13 36 p 2 + 18   τ ( Γ 9 ) . (l) The graph Γ 11 . The rule of parallel edges is applied, and we get: τ ( Γ 11 ) = τ ( Γ 10 ) . (m) The graph Γ 12 . The Δ-Y transformation rule gives us: τ ( Γ 12 ) = 9 1849 p 2 + 1000 888 p 2 + 481 τ ( Γ 11 ) . (n) The graph Γ 13 . By applying the Y-Δ transformation rule, we arrive at: τ ( Γ 13 ) = ( 888 p 2 + 481 8283 p 2 + 4482 ) 3   τ ( Γ 12 ) . (o) The graph Γ 14 . When we apply the rule of parallel edges, we obtain:   τ ( Γ 14 ) = τ ( Γ 13 ) . (p) The graph Γ 15 . When we use the Y-Δ transformation rule, we get: τ Γ 15 = 37 2761 p 2 + 1494 342 1849 p 2 + 1000 τ ( Γ 14 ) . (q) The graph Γ 16 = R 1 J S 1 . Applying the parallel edge rule yields the following results: τ ( Γ 16 ) = τ ( Γ 15 ) .
Mathematics 13 03036 g005aMathematics 13 03036 g005bMathematics 13 03036 g005cMathematics 13 03036 g005dMathematics 13 03036 g005eMathematics 13 03036 g005fMathematics 13 03036 g005gMathematics 13 03036 g005hMathematics 13 03036 g005i
Figure 6. The graph R 2 J S 2 .
Figure 6. The graph R 2 J S 2 .
Mathematics 13 03036 g006
Figure 7. The transformations from   R 2 J S 2 to R 2 J S 1 .(a) The graph R 2 J S 2 . (b) The graph Γ 1 . When we use the Δ-Y transformation rule, we get: τ Γ 1 = 9 4 p 2   τ ( R 2 J S 2 ) . (c) The graph Γ 2 . By applying the serial edge rule, we obtain: τ Γ 2 = 1 4 9 × 1 3 p 2 + 1 3 τ ( Γ 1 ) . (d) The graph Γ 3 . Upon applying the Y-Δ transformation rule, we obtain: τ Γ 3 = 4 11 9 × 3 p 2 + 1 9 p 2 + 2 3 τ ( Γ 2 ) . (e) The graph Γ 4 . The parallel edge rule is used to get: τ ( Γ 4 ) = τ ( Γ 3 ) . (f) The graph Γ 5 . Using the Y-Δ transformation rule, we get: τ ( Γ 5 ) = 11 18 3 × 9 p 2 + 2 18 p 2 τ ( Γ 4 ) . (g) The graph Γ 6 . By applying the parallel edge rule, one can obtain: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . Applying the rule of Δ-Y transformation, we obtain: τ ( Γ 7 ) = 9 6 11 3 × 9 5 p 2 + 1 9 p 2 + 2 τ ( Γ 6 ) . (i) The graph Γ 8 . The serial edge rule is applied, and the result is: τ Γ 8 = 11 29 9 × 9 p 2 + 2 24 p 2 + 5 3 τ ( Γ 7 ) . (j) The graph Γ 9 . Applying the rule of Y-Δ transformation, we obtain: τ Γ 9 = 29 76 9 × 24 p 2 + 5 63 p 2 + 13 3 τ ( Γ 8 ) . (k) The graph Γ 10 . The parallel edge rule can be used to get: τ ( Γ 10 ) = τ ( Γ 9 ) . (l) The graph Γ 11 . By using the Y-Δ transformation rule, we get: τ ( Γ 11 ) = 19 27 3 × 63 p 2 + 13 6 15 p 2 + 3 τ ( Γ 10 ) . (m) The graph Γ 12 . Using the parallel edge rule, one can obtain: τ ( Γ 12 ) = τ ( Γ 11 ) . (n) The graph Γ 13 . Using the rule of Δ-Y transformation, we obtain: τ ( Γ 13 ) = 9 9955 p 2 + 2053 4788 p 2 + 988 τ ( Γ 12 ) . (o) The graph Γ 14 . When the Y-Δ transformation rule is used, we obtain: τ Γ 14 = 76 63 p 2 + 13 44607 p 2 + 9201 3 τ ( Γ 13 ) . (p) The graph Γ 15 . By applying the rule of parallel edges, one can get: τ ( Γ 15 ) = τ ( Γ 14 ) . (q) The graph Γ 16 . Applying the Y-Δ transformation rule yields: τ Γ 16 = 38 14869 p 2 + 3067 351 9955 p 2 + 2053   τ ( Γ 15 ) . (r) The graph Γ 17 = R 2 J S 1 . The rule of parallel edges can be used to obtain: τ ( Γ 17 ) = τ ( Γ 16 ) .
Figure 7. The transformations from   R 2 J S 2 to R 2 J S 1 .(a) The graph R 2 J S 2 . (b) The graph Γ 1 . When we use the Δ-Y transformation rule, we get: τ Γ 1 = 9 4 p 2   τ ( R 2 J S 2 ) . (c) The graph Γ 2 . By applying the serial edge rule, we obtain: τ Γ 2 = 1 4 9 × 1 3 p 2 + 1 3 τ ( Γ 1 ) . (d) The graph Γ 3 . Upon applying the Y-Δ transformation rule, we obtain: τ Γ 3 = 4 11 9 × 3 p 2 + 1 9 p 2 + 2 3 τ ( Γ 2 ) . (e) The graph Γ 4 . The parallel edge rule is used to get: τ ( Γ 4 ) = τ ( Γ 3 ) . (f) The graph Γ 5 . Using the Y-Δ transformation rule, we get: τ ( Γ 5 ) = 11 18 3 × 9 p 2 + 2 18 p 2 τ ( Γ 4 ) . (g) The graph Γ 6 . By applying the parallel edge rule, one can obtain: τ ( Γ 6 ) = τ ( Γ 5 ) . (h) The graph Γ 7 . Applying the rule of Δ-Y transformation, we obtain: τ ( Γ 7 ) = 9 6 11 3 × 9 5 p 2 + 1 9 p 2 + 2 τ ( Γ 6 ) . (i) The graph Γ 8 . The serial edge rule is applied, and the result is: τ Γ 8 = 11 29 9 × 9 p 2 + 2 24 p 2 + 5 3 τ ( Γ 7 ) . (j) The graph Γ 9 . Applying the rule of Y-Δ transformation, we obtain: τ Γ 9 = 29 76 9 × 24 p 2 + 5 63 p 2 + 13 3 τ ( Γ 8 ) . (k) The graph Γ 10 . The parallel edge rule can be used to get: τ ( Γ 10 ) = τ ( Γ 9 ) . (l) The graph Γ 11 . By using the Y-Δ transformation rule, we get: τ ( Γ 11 ) = 19 27 3 × 63 p 2 + 13 6 15 p 2 + 3 τ ( Γ 10 ) . (m) The graph Γ 12 . Using the parallel edge rule, one can obtain: τ ( Γ 12 ) = τ ( Γ 11 ) . (n) The graph Γ 13 . Using the rule of Δ-Y transformation, we obtain: τ ( Γ 13 ) = 9 9955 p 2 + 2053 4788 p 2 + 988 τ ( Γ 12 ) . (o) The graph Γ 14 . When the Y-Δ transformation rule is used, we obtain: τ Γ 14 = 76 63 p 2 + 13 44607 p 2 + 9201 3 τ ( Γ 13 ) . (p) The graph Γ 15 . By applying the rule of parallel edges, one can get: τ ( Γ 15 ) = τ ( Γ 14 ) . (q) The graph Γ 16 . Applying the Y-Δ transformation rule yields: τ Γ 16 = 38 14869 p 2 + 3067 351 9955 p 2 + 2053   τ ( Γ 15 ) . (r) The graph Γ 17 = R 2 J S 1 . The rule of parallel edges can be used to obtain: τ ( Γ 17 ) = τ ( Γ 16 ) .
Mathematics 13 03036 g007aMathematics 13 03036 g007bMathematics 13 03036 g007cMathematics 13 03036 g007dMathematics 13 03036 g007eMathematics 13 03036 g007fMathematics 13 03036 g007gMathematics 13 03036 g007h
Table 1. Some values of the sequence graph J S n .
Table 1. Some values of the sequence graph J S n .
n τ ( J S n )
1 3
2 2491593283872
3 2112437751486969285553152
4 1790988962651356816536555493874761728
5 1518454906483793748865840366762786491366191923200
Table 2. Some values of the sequence graph R 1 J S n .
Table 2. Some values of the sequence graph R 1 J S n .
n τ ( R 1 J S n )
1 3
2 641484054515879424
3 143141158665083478581380003174023168
4 31940638527102636925754646727860195059034384242835456
5 7127260943349184929722120116724599408515777828964115381942103696211968
Table 3. Some values of the sequence graph R 2 J S n .
Table 3. Some values of the sequence graph R 2 J S n .
n τ ( R 2 J S n )
1 3
2 202472185401828605952
3 13956830898768814530639892676989396451328
4 962073629817096776737016091553641615759689294887929803440128
5 66317753357005266372021022857195352821313530548303482328825760901236213921349632
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Asiri, A.; Daoud, S.N. Finding the Number of Spanning Trees in Specific Graph Sequences Generated by a Johnson Skeleton Graph. Mathematics 2025, 13, 3036. https://doi.org/10.3390/math13183036

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Asiri A, Daoud SN. Finding the Number of Spanning Trees in Specific Graph Sequences Generated by a Johnson Skeleton Graph. Mathematics. 2025; 13(18):3036. https://doi.org/10.3390/math13183036

Chicago/Turabian Style

Asiri, Ahmad, and Salama Nagy Daoud. 2025. "Finding the Number of Spanning Trees in Specific Graph Sequences Generated by a Johnson Skeleton Graph" Mathematics 13, no. 18: 3036. https://doi.org/10.3390/math13183036

APA Style

Asiri, A., & Daoud, S. N. (2025). Finding the Number of Spanning Trees in Specific Graph Sequences Generated by a Johnson Skeleton Graph. Mathematics, 13(18), 3036. https://doi.org/10.3390/math13183036

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