2-tone Colorings in Graph Products

Size: px
Start display at page:

Download "2-tone Colorings in Graph Products"

Transcription

1 -tone Colorings in Graph Products Jennifer Loe, Danielle Middlebrooks, Ashley Morris August 13, 013 Abstract A variation of graph coloring known as a t-tone k-coloring assigns a set of t colors to each vertex of a graph from the set 1,, k where the sets of colors assigned to any two vertices distance d apart share fewer than d colors in common. The minimum integer k such that a graph G has a t-tone k-coloring is known as the t-tone chromatic number. We study the -tone chromatic number in three different graph products. In particular, given graphs G and H, we bound the -tone chromatic number for the direct product G H, the Cartesian product G H, and the strong product G H. 1 Introduction Many variations of classic graph k-colorings abound, whereby we take a k-coloring of a graph to mean an assignment of an element from 1,, k, called a color, to each of the vertices of the graph. Gary Chartrand was the first to introduce a t-tone k-coloring, which is an assignment of t elements from the set 1,, k to each vertex such that the sets of colors assigned to any two distinct vertices within distance d share fewer than d colors. This t-tone k-coloring variation can be viewed as a generalization of classic graph coloring since a 1-tone k-coloring of a graph is simply a k-coloring. In an initial investigation of this graph parameter, Fonger, Goss, Phillips, and Segroves [4] determined the exact value for the -tone chromatic number of a tree and a complete multipartite graph. In 011, Bickle and Phillips [] gave general bounds for the t-tone chromatic number of a graph G in terms of the maximum degree of G. Cranston, Kim, and Kinnersley [3] improved upon these bounds shortly thereafter. In [1], the problem of determining bounds of the t-tone chromatic number of the Cartesian product of two graphs is posed. In this paper, we determine bounds on the -tone chromatic number in the direct product, Cartesian product, and the strong product of two graphs. 1

2 1.1 Definitions and Notation An undirected graph G = (V, E) is a set of vertices V (G) together with a set of edges E(G) which are unordered pairs (x, y), or simply xy, of vertices of G. If xy E(G), we say that x and y are adjacent. For the purpose of this paper, we consider only simple undirected graphs, meaning undirected graphs that have no loops. For any vertex x V (G), the open neighborhood of x, denoted N(x), is defined to be the set of all vertices adjacent to x. The closed neighborhood of x is defined to be N[x] = N(x) x. The degree of x, denoted deg G (x), is the cardinality of the open neighborhood of x. We let (G) = max x V (G) deg G (x). A path of length k, denoted P k, in G between two vertices v 0 and v k is a sequence v 0,, v k of k + 1 distinct vertices of G such that for all i 0,, k 1, the edge v i v i+1 E(G). The distance between vertices u and v, denoted d G (u, v) is the smallest length path between u and v. When the context is clear, we use the shorthand notation d(u, v). As stated before, a proper k-coloring of a graph G is an assignment of an element from 1,, k, called a color, to each vertex in V (G) such that no two adjacent vertices are assigned the same color. The chromatic number of G, denoted χ(g), is the minimum number k such that G has a proper k-coloring. We use K n to denote the complete graph on n vertices, which is a graph with n vertices where each vertex has degree n 1. Given a graph G, a clique is any complete subgraph of G, and the clique number of G, denoted ω(g), is the cardinality of the maximum clique of G. For positive integers t and k where t k, we let [k] represent the set 1,, k and denote the family of t-element subsets of [k] by ( ) [k] t. We now give a formal definition of a t-tone k-coloring of a graph. Definition 1. Let G be a graph and let t and k be positive integers such that t k. A t-tone k-coloring of G is a function f : V (G) ( ) [k] t such that f(u) f(v) < dg (u, v) for all distinct vertices u and v. A graph that has a t-tone k-coloring is said to be t-tone k-colorable. The t-tone chromatic number of G, denoted τ t (G), is the minimum k such that G is t-tone k-colorable. Given a t-tone k-coloring f of G, we call f(v) the label of v and the elements of [k] colors. Figure 1 depicts a -tone 5-coloring of P 5 which is, indeed, minimum. 1, 3,4 1,5,4 1,3 Figure 1: A -tone 5-coloring of P 5 In this paper, we focus on -tone k-colorings of three different graph products. First, we consider the direct product. Definition. Given two graphs G and H, the direct product of G and H, denoted G H, is the graph whose vertex set is the Cartesian product V (G) V (H) and whose edge set is E(G H) = (x 1, y 1 )(x, y ) x 1 x E(G) and y 1 y E(H).

3 Figure depicts the direct product of K and K 3. Figure : K K 3 The next graph we consider is the Cartesian product, which is the motivation behind this research. We aim to improve upon the upper bound for the -tone chromatic number of the Cartesian product of two graphs given in [1]. Definition 3. The Cartesian product of graphs G and H, denoted G H, is the graph whose vertex set is V (G) V (H) with edge set E(G H) = (x 1, y 1 )(x, y ) x 1 y 1 E(G) and x = y, or x 1 = y 1 and x y E(H). Figure 3 depicts the Cartesian product of K and K 3. Figure 3: K K 3 The last product we consider is the strong product of two graphs. Definition 4. The strong product of graphs G and H, denoted G H, is the graph whose vertex set is the Cartesian product V (G) V (H) and whose edge set is E(G H) = E(G H) E(G H). Figure 4 depicts the strong product of K and K 3. Previous Results In this section, we state various results that were useful in our research. We give a short proof of any result that will be used in Section 3. The following theorem shows the monotonicity of t-tone colorings. 3

4 Figure 4: K K 3 Theorem 5. [4] If H is a subgraph of G, then τ t (H) τ t (G). Proof. Let f be a proper t-tone τ t (G)-coloring of G. The restriction of f to H must then be a proper t-tone coloring of H. Thus, τ t (H) is no greater than τ t (G). In Section 3, we determine the -tone chromatic number of K m K n for any m, n Z. We shall use the following result to do so. Theorem 6. [4] If G = K n for any positive integer n, then τ t (K n ) = tn. Proof. Notice that each pair of distinct vertices of V (K n ) is adjacent. Therefore, the set of t-element labels of the n vertices of K n must be pairwise disjoint, and we have τ t (K n ) = tn. Recall that a k-partite graph is a graph whose vertices can be partitioned into k disjoint sets, called partite sets, such that no two vertices within the same partite set are adjacent. A complete k-partite graph, denoted K a1,,a k, is a k-partite graph with the additional property that any two distinct vertices contained in different partite sets are adjacent, and whose partite sets are of orders a 1,, a k. Theorem 7. [4] Let G = K a1,a,...,a k denote the complete k-partite graph, with partite sets of orders a 1, a,..., a k. Then k 1 + 8ai + 1 τ (G) =. i=1 Proof. Let G = K a1,a,...,a k and let χ(g) = k. Let A 1,..., A k denote the color classes of G. Let A i = a i, for 1 i k. Now let f be a proper -tone τ (G)-coloring of G. Notice that for any pair of distinct vertices u, v A i, we have d(u, v) =. Hence, f(v) f(u) 1. So the number of colors required for the i th partite set is s i such that ( s i ) ai. Thus, we get that s i = 1+ 8ai +1. Furthermore, since every element in A i is adjacent to every element in A j for all i j with 1 i, j k, they cannot have any colors in common. Therefore, the -tone chromatic number of G is the sum of all such s i, as desired. There is a natural relationship between t-tone colorings and another variation of graph coloring known as a distance (d, k)-coloring. 4

5 Definition 8. A distance (d, k)-coloring of G is a mapping f : V (G) [k] such that if u and v are two distinct vertices of V (G) where d(u, v) d, then f(u) f(v). We use χ d (G) to denote the minimum number k such that G has a proper distance (d, k)-coloring. As stated throughout the literature, determining χ d (G) is equivalent to determining the chromatic number of the d th power of a graph, defined below. Definition 9. Given a graph G, the d th power of G, denoted G d,is defined to be the graph with V (G d ) = V (G), and for any two distinct vertices u, v V (G d ), uv E(G d ) if and only if d G (u, v) d. Since the focus of this paper is on -tone colorings, we will restrict ourselves to distance (, k)- colorings. We now prove equality between χ (G) and χ(g ). Theorem 10. For any graph G, χ (G) = χ(g ). Proof. Assume that f : V (G) 1,..., χ (G) is a proper distance (, χ (G))-coloring of G. If uv E(G ), then d G (u, v) so f(u) f(v). Thus, f is a proper χ (G)-coloring of G, and we have χ(g ) χ (G). In the other direction, assume that g : V (G ) 1,, χ(g ) is a proper χ(g )-coloring of G. If d G (u, v), then uv E(G ) so g(u) g(v). Thus, g is a distance (, χ(g ))-coloring of G, and the result follows. As noted in Fonger, Phillips and Segroves [4], τ (G) is related to both χ(g) and χ(g ) in the following way. Theorem 11. [4] For any graph G, τ (G) χ(g) + χ(g ). Proof. Let f 1 be a chromatic coloring of G using the colors 1,,..., χ(g), and f a chromatic coloring of G using the colors χ(g) + 1,..., χ(g ). Then we define a -tone coloring f of G by setting f(v) = f 1 (v), f (v). Then, if u, v are adjacent in G, we have that f 1 (v), f (v), f 1 (u), and f (u) are four different colors. Similarly, if d(u, v) = for vertices u and v of G, then f (u) f (v), and so the labels on u and v assigned by f are not the same. Therefore, f is a proper -tone coloring of G using χ(g) + χ(g ) colors. Bickle and Phillips give an upper bound for τ (G) in [] based on (G). Theorem 1. [] For any graph G, τ (G) [ (G)] + (G). This bound was improved upon by Cranston, Kim and Kinnersley in [3]. We will reference this result throughout Section 3 as a comparison to our results. Theorem 13. [3] For any graph G, τ (G) ( + ) (G). 5

6 3 New Results 3.1 Direct Product In this section, we focus on the direct product of two graphs. We restate the definition of the direct product for ease of reference. Definition 14. Given two graphs G and H, the direct product of G and H, denoted G H, is the graph whose vertex set is the Cartesian product V (G) V (H) and whose edge set is E(G H) = (x 1, y 1 )(x, y ) x 1 x E(G) and y 1 y E(H). Throughout this section, when we consider the direct product of two graphs G and H where G = m and H = n, we will represent the vertices of G as x 1,, x m and the vertices of H as y 1,, y n. Using this notation, for each i [m] we define a column C i as the set of all vertices with first coordinate x i. Similarly, for each j [n] we define the row R j as the set of all vertices with second coordinate y j. In particular, for i [m], the i th column is C i = (i, j) j [n]. Similarly, for j [n] the j th row is the set R j = (i, j) i [m]. In order to find an upper and lower bound of the -tone chromatic number of the direct product of any two graphs G and H, we first considered the direct product of two complete graphs. The following property follows from the definition of the direct product. Property 15. For any m, n Z V (K m K n ) = (x i, y k ) 1 i m and 1 k n, and E(K m K n ) = (x i, y k )(x j, y l ) i j and k l. Note the following consequence of Property 15. Proposition 16. Let m and n be positive integers such that m and n 3. For any two distinct vertices (x i, y j ) and (x i, y k ) of V (K m K n ), d((x i, y j ), (x i, y k )) =. Proof. Let u, v V (K m K n ) be two distinct vertices, and write u = (x i, y j ) and v = (x i, y k ) for some 1 i m and 1 j < k n. Note that u and v are both contained in column C i. Since m 3, there exists a 1,, m such that a i. Thus, x i x a E(K m ). Moreover, since n 3, there exists b 1,, n such that b j and b k. Therefore, y j y b E(H) and y b y k E(H). So (x i, y j )(x a, y b )(x i, y k ) is a path in K m K n of length. It follows that d(u, v) =. Recall from Section 1 that given a graph G and a t-tone k-coloring f of G, we call f(v) the label of v and the elements of [k] colors. Additionally, for any set of vertices A V (G), we define the set of colors contained in the labels associated with A to be c(a) = c [k] c f(v) for some v A. 6

7 Theorem 17. If m, n N where m n and t = n, then τ (K m K n ) min m t, m + n, m t + n t ( t 1) Proof. First consider the case where m = n =. Since K K = K, τ (K K ) = τ (K ) = 4. One can easily verify that this is the minimum of the three functions. Now consider all other cases where m, n m and n. Let f be a minimum -tone k-coloring of K m K n. For each 1 i m, define A i as the set of all vertices v C i such that for each a f(v), there exists a vertex w C i with w v and a f(v) f(w). Note the following consequence of this partition of each C i. Fix i 1,, m and let v and w be distinct vertices of A i as described above. That is, for some a f(v) we have a f(v) f(w). This implies that for all j 1,, m such that j i and for any u A j, a f(u) since u is adjacent to at least one of v or w by Property 15. Therefore, the set of colors contained in the labels associated with A i is disjoint from the set of colors contained in the labels associated with A j. That is, c(a i ) c(a j ) =. For each 1 i m, let s i = c(a i ). We may assume that min 1 i m s i = s l for some l 1,, m. Thus, the number of distinct colors contained in the labels associated with m i=1a i is at least ms l. Furthermore, for each (x l, y j ) C l \A l, there exists a color a f((x l, y j )) such that a is not contained in any other label associated with C l. So for each 1 i m, a c(a i ) by definition of A i. Since f is a proper -tone k-coloring of K m K n, we know that k ms l + C l \A l. We now determine the minimum k based on the value of C l \A l. Case 1: Assume that C l \A l = n. Thus, A l = and s l = 0. Let j represent the number of columns such that s i > 0 for some i 1,, m. Since s l = 0, m j 1 or equivalently m j + 1. Let A = C i i 1,, m and s i = 0. For indexing purposes, we shall write A = C α(1),, C α(m j) where α(i) 1,, m for 1 i m j. Since m j m n, there exists a set W = v α(1),, v α(m j) such that v α(i) C α(i) for each α(i) and if α(i) α(j), then v α(i) and v α(j) are contained in different rows. This implies that the induced subgraph of W is a clique, and it follows that f(v α(i) ) f(v α(j) ) = 0 when α(i) α(j). Furthermore, the n (m j) remaining vertices (x l, y j ) C l \A l where R j W = contain at least n (m j) colors that are not contained in c(w ). Thus, c(b) (m j) + n (m j). Finally, for each column C i where s i > 0, we know that s i. Thus, k (m j) + n (m j) + j = m + n + j m + n.. Case : Assume that C l \A l = 0. It follows that A l = C l and A l = n. Furthermore, since s l represents the number of distinct colors contained in the labels associated with A l, we know 7

8 that s l. Using the same argument as in Theorem 7 and the fact that any two distinct vertices u, v A l satisfy d(u, v) =, we know that ( s l ) n. Using the quadratic formula, this implies that s l. Consequently, k m n n Case 3: Assume that n > C l \A l > 0. If ( s l ) > n, then clearly k m n ( sl ) n, or equivalently 1+ sl 1+8n implies C l \A l = n A l. As in Case 1, we know ( s l ) Al. Thus, ( ) sl n n A l ( ) sl = n C l \A l. Therefore, ms l + C l \A l ms l + n. So assume. We have n = C l = A l + C l \A l, which ( ) sl = ms l + n s l(s l 1). So we consider the function g(s) = ms + n s(s 1) 1+ over the interval s 1+8n. One can easily verify that g (s) = m s + 1 and g (s) = 1. Thus, g is concave down 1+ for all values of s 1+8n, and over this interval g has a local maximum when s = m + 1. Therefore, the local minimums for g occur when s = and s =. Letting t = n, it follows that k ms l + C l \A l s(s 1) min ms + n s n s.t. s t ( t 1) min m + n 1, m t + n n Since m + n 1 > m + n and f is assumed to be a minimum -tone coloring, we shall take min m + n 1, m t + n t ( t 1) = m t + n t ( t 1). Note that these cases sometimes overlap. For example, ( s ) = n implies that t = t = t and n t ( t 1) = 0, resulting in m t = m t + n t ( t 1). In any case, we have t ( t 1) τ (K m K n ) min m t, m + n, m t + n. 8

9 Theorem 18. If m, n N where m n and t = n, then τ (K m K n ) = min m t, m + n, m t + n t ( t 1) Proof. From Theorem 17, all that remains to be shown is that t ( t 1) τ (K m K n ) min m t, m + n, m t + n. Given m, n N where m n and t = n, we shall construct different -tone colorings which depend on the value of min m t, m + n, m t + n t ( t 1). Case 1: First assume that min m t, m + n, m t + n t ( t 1) = m t. Choose m pairwise disjoint sets each containing t distinct colors, and denote each set of colors S i for 1 i m. Since ( ) t n, for each 1 i m there exist n distinct combinations containing two colors from the set S i. Thus, we may define f : V (K m K n ) ( ) [ t ] to be any mapping such that for each 1 i m the restriction of f to the set of vertices in C i is an injective mapping to the set of combinations containing two colors from the set S i. Figure 5 illustrates this particular -tone coloring for K K 6. To see that f is a proper -tone coloring of K m K n, let u and v be distinct vertices of V (K m K n ). If u and v are not contained in the same column, then f(u) f(v) =. So assume u, v C i for some i 1,, m. Since d(u, v) =, we must show that f(u) f(v) 1. However, this follows from the fact that f does not assign any label to more than one vertex of C i. Therefore, f is a proper -tone coloring.. 3,4 7,8,4 6,8 1,4 5,8 1,3 5,7,3 6,7 1, 5,6 Figure 5: K K 6 9

10 Case : Next, assume that min m t, m + n, m t + n t ( t 1) = m + n. Let f 1 be a proper coloring of K m and f be a proper coloring of K n defined as follows: f 1 : V (K m ) [m] x i i f : V (K n ) m + 1,, m + n y k k + m. Define the following function on V (K m K n ): ( ) [m + n] g : V (K m K n ) (x i, y k ) f 1 (x i ), f (y k ). Figure 6 illustrates a particular -tone coloring of this type for K K 3. 1,4 4,5 1,3 3,5 1,,5 Figure 6: K K 3 We claim g is a proper -tone coloring of K m K n. Clearly g((x, y)) = for all (x, y) V (K m K n ). Let (x i, y k ) and (x j, y l ) be two distinct vertices of V (K m K n ) where 1 i, j m and 1 k, l n. Then g((x i, y k )) = i, k + m and g((x j, y l )) = j, l + m. If (x i, y k ) and (x j, y l ) are adjacent, then i j and k l. Thus, g((x i, y k )) g((x j, y l )) = 0. If d((x i, y k ), (x j, y l )) =, then either i j or k l. In any case, g((x i, y k )) g((x j, y l )) 1. Therefore, g is a proper -tone coloring of K m K n, and we may conclude that τ (K m K n ) m + n. Case 3: Assume that min m t, m + n, m t + n t ( t 1) = m t + n t ( t 1). Note that t = n is the only positive solution to ( ) ( t = n. Therefore, t satisfies t ) ( n. Let s = t ) and consider the subgraph H of K m K n induced by the set (x i, y j ) 1 i m, 1 j s. Thus, H = K m K s. As in Case, choose m pairwise disjoint sets of t distinct colors and denote each set S i for 1 i m. Define f 1 : V (H) ( ) [ t ] to be any mapping such that for 10

11 each 1 i m, the restriction of f 1 to the set of vertices of C i is an injective mapping to the set of combinations containing two colors from the set S i. A similar argument as in Case can be used to show that f 1 is a proper -tone coloring of H. Next, choose n s distinct colors each of which are not contained in the set m i=1s i, and label these colors t s+1,, t n. Additionally, for each i 1,, m, choose one color from the set S i and call it c i. Notice that V (K m K n )\V (H) = (x i, y j ) 1 i m, s + 1 j n. Define ( ) [m + n s] f : V (K m K n )\V (H) (x i, y j ) c i, t j. We claim that f is a proper -tone coloring of (K m K n )\H. To see this, let (x i, y k ) and (x j, y l ) be two distinct vertices of V (K m K n )\V (H) for some 1 i, j m and s + 1 k, l n. If (x i, y k ) and (x j, y l ) are adjacent, then i j and k l. Since S i and S j are two disjoint sets of colors, we know that c i c j. Moreover, we know that t k t l since k l. Thus, f ((x i, y k )) f ((x j, y l )) = 0. If d((x i, y k ), (x j, y l )) =, then either i j or k l. It follows that f ((x i, y k )) f ((x j, y l )) 1. Therefore, f is a proper -tone coloring of (K m K n )\H. ) such that Now define g : V (K m K n ) ( [m t +n s] f 1 (u) g(u) = f (u) if u V (H) otherwise. Figure 7 illustrates a particular -tone coloring of this type for K K 11. To see that g is a proper -tone coloring, we only need to consider when u V (H) and v V (H). Write u = (x i, y k ) and v = (x j, y l ) for some i, j 1,, m, k 1,, s, and l s + 1,, n. By definition g(v) = c j, t l, and we know t l g(u) since u V (H). So if u and v are located in the same column, then g(u) g(v) 1. If u and v are not located in the same column, then i j and c j g(u) since c j S i. It follows that g(u) g(v) = 0. Therefore, g is a proper -tone coloring of K m K n using m t + n ( ) t colors. Using similar ideas found in Theorems 17-18, we can bound the value of τ (G H) given any graphs G and H. We make use of the following general lower bound given in [4]. Theorem 19. [4] Let G be a graph and let (G) = d. Then 8d τ (G). 11

12 1,11 4,5 3,5 3,4,5,4,3 1,5 1,4 1,3 1, 6,11 9,10 8,10 8,9 7,10 7,9 7,8 6,10 6,9 6,8 6,7 Figure 7: K K 11 Theorem 0. Given two graphs G and H, (G) (H) max, τ (K ω(g) K ω(h) ) τ (G H) χ(g ) + χ(h ). Proof. We first show that for any graphs G and H, we have τ (G H) χ(g ) + χ(h ). Assume χ (G) = k 1 and χ (H) = k. Let f 1 : V (G) 1,..., k 1 be a distance- coloring of G, and let f : V (H) k 1 + 1,..., k 1 + k be a distance- coloring of H. Define ( ) [k1 + k ] g : V (G H) such that (x, y) f 1 (x), f (y) for all x V (G) and y V (H). We claim that g is a proper -tone coloring of G H. Clearly g((x, y)) = for all (x, y) V (G H). Let (u, v) and (w, z) be two distinct vertices of V (G H). If (u, v) and (w, z) are adjacent, then uw E(G) and vz E(H). It follows that f 1 (u) f 1 (w) and f (v) f (z). Since the range of f 1 is disjoint from the range of f as mappings, we have g((u, v)) g((w, z)) = 0. If d G H ((u, v), (w, z)) =, then there exists a vertex (x, y) V (G H) such that uxw is a path in G and vyz is a path in H. Since d G (u, w) and d H (v, z), we know that f 1 (u) f 1 (w) and f (v) f (z). Thus, g((u, v)) g((w, z)) = 0, and we may conclude that g is a proper -tone coloring of G H. 1

13 (G) (H) Next, we show that max, τ (K ω(g) K ω(h) ) τ (G H). We shall assume that ω(g) is the clique number of G, and ω(h) is the clique number of H. By definition of the direct product, K ω(g) K ω(h) is a subgraph of G H. Thus, τ (K ω(g) K ω(h) ) τ (G H). On the other hand, we know (G H) = (G) (H). So by Theorem 19, we know that (G) (H) τ (G H). Therefore, max (G) (H), τ (K ω(g) K ω(h) ) τ (G H). It should be noted that there exist graphs G and H such that the upper bound in Theorem 0 is better than applying Theorem 13. For example, consider the graph P 3 P 4 in Figure 8. One can easily verify that the labeling shown in Figure 8 is in fact a -tone coloring. Thus, τ (P 3 P 4 ) 5 which is an improvement from the bound given in Theorem 13 of τ (P 3 P 4 ) ( + ()) (P 3 P 4 ) = ( + )4 = ,4,4 3,4 6 1,6,6 3,6 5 1,5,5 3,5 4 1,4,4 3,4 1 3 Figure 8: A -tone coloring of P 3 P 4 13

14 3. Cartesian Product We now focus on the Cartesian product of two graphs. We restate the definition of this product below for ease of reference. Definition 1. The Cartesian product of graphs G and H, denoted G H, is the graph whose vertex set is V (G) V (H) with edge set E(G H) = (x 1, y 1 )(x, y ) x 1 y 1 E(G) and x = y, or x 1 = y 1 and x y E(H). In this particular product, we have an obvious lower bound for the -tone chromatic number of G H. Theorem. Given two graphs G and H, maxτ (G), τ (H) τ (G H). Proof. This follows from the fact that G and H are both subgraphs of G H. In terms of an upper bound, it is stated in [1] that τ (G H) τ (G)τ (H), but that this bound could be improved. We give an upper bound for τ (G H) in terms of maxχ(g ), χ(h ) depending on the parity of this value. Theorem 3. Given two graphs G and H where maxχ(g ), χ(h ) = χ(g ), χ(g ) if χ(g ) is odd τ (G H) (χ(g ) + 1) otherwise. Proof. Assume that maxχ(g ), χ(h ) = χ(g ). If χ(g ) is an even integer, then we will let k = χ(g ) + 1. Otherwise, we will let k = χ(g ). Let f 1 : V (G) [k] be a proper distance (, k)-coloring of G, and let f : V (H) [k] be a proper distance (, k)-coloring of H. Define g : V (G H) ( ) [k] such that (x, y) f 1 (x) + f (y) (mod k), (f (y) f 1 (x) (mod k)) + k. We will first show that g assigns two distinct colors to each vertex of G H. Let (x, y) V (G H) and write g((x, y)) = a, b. Since a = f 1 (x) + f (y) (mod k), it follows that a [k]. On the other hand, b = (f (y) f 1 (x) (mod k)) + k so b k + 1,, k. Thus, g((x, y)) =. Next, we show that g satisfies the distance criteria for -tone colorings. Let (u, v) and (w, z) be two distinct vertices of V (G H). 14

15 Case 1: Suppose that d G H ((u, v)(w, z)) = 1. Then either u = w and d H (v, z) = 1 or v = z and d G (u, w) = 1. If u = w and d H (v, z) = 1, then we know that f 1 (u) = f 1 (w) and f (v) f (z). This implies that f 1 (u) + f (v) f 1 (w) + f (z) (mod k). Moreover, f (v) f 1 (u) f (z) f 1 (w) (mod k) = (f (v) f 1 (u) (mod k)) + k (f (z) f 1 (w) (mod k)) + k. So g((u, v)) g((w, z)) = 0. A similar argument shows that g((u, v)) g((w, z)) = 0 if v = z and d G (u, w) = 1. Case : Suppose that d G H ((u, v)(w, z)) =. Then exactly one of the following will be true. (a) (b) u = w and d H (v, z) =, or v = z and d G (u, w) =, or (c) d G (u, w) = 1 and d H (v, z) = 1. In the case of either (a) or (b), a similar argument as in Case 1 shows g((u, v)) g((w, z)) = 0. So assume d G (u, w) = 1 and d H (v, z) = 1. It follows that f 1 (u) f 1 (w) and f (v) f (z). If g((u, v)) g((w, z)) 1, we are done. So suppose that g((u, v)) = g((w, z)). Thus, Moreover, (f (v) f 1 (u) (mod k)) + k = (f (z) f 1 (w) (mod k)) + k = f (v) f 1 (u) f (z) f 1 (w) (mod k) = f (v) f (z) f 1 (u) f 1 (w) (mod k). (1) f 1 (u) + f (v) f 1 (w) + f (z) (mod k) = f 1 (u) f 1 (w) f (z) f (v) (mod k) = f (v) f 1 (z) f (z) f (v) (mod k) from (1) = f (v) f (z) (mod k). However, this cannot happen since f (v) f (z) (mod k) and gcd(, k) = 1. Thus, g((u, v)) g((w, z)) 1. Although the upper bound in Theorem 3 does not involve τ (G) or τ (H), it should be noted that there are graphs for which the upper bound is best possible. For example, consider the graph P 3 P 3. We know τ (P 3 ) = 5 and χ(p 3 ) = 3. Moreover, P 3 P 3 contains a cycle of length 4 and since τ (C 4 ) = 6, it must be the case that 6 τ (P 3 P 3 ). Figure 9 shows a proper -tone coloring using only 6 colors. Thus, τ (P 3 P 3 ) = χ(g ) = 6. 15

16 3,5 3,4 1,6 1,4,6 3,5 1 3,6 1,5,4 1 3 Figure 9: A -tone coloring of P 3 P Strong Product The last graph product that we consider is the strong product G H. We restate the definition of this product below for ease of reference. Definition 4. The strong product of graphs G and H, denoted G H, is the graph whose vertex set is the Cartesian product V (G) V (H) and whose edge set is E(G H) = E(G H) E(G H). Using similar ideas to those found in Sections 3.1 and 3., we have the following upper and lower bounds for τ (G H). Theorem 5. Given two graphs G and H, maxτ (G H), τ (G H) τ (G H) minτ (G)χ(H ), χ(g )τ (H). Proof. Note that G H and G H are both subgraphs of G H. Thus, maxτ (G H), τ (G H) τ (G H) by Theorem 5. Next, we will prove that τ (G H) minτ (G)χ(H ), χ(g )τ (H). Without loss of generality, we may assume τ (G)χ(H ) χ(g )τ (H). Let f 1 be a proper -tone coloring of G using the colors 1,,...τ (G). Let f be a proper distance (, k)-coloring of H using the colors 1, τ (G) + 1, τ (G) + 1,..., (k 1)τ (G) + 1 where k = χ(h ). Define g : V (G H) ( [kτ ) (G)+1] such that for each (x, y) V (G H) and for each c f 1 (x), we have c + f (y) g((x, y)). We show that g is a proper -tone coloring of G H. V (G H). 16 Let (u, v) and (w, z) be vertices of

17 Case 1: Assume that d G H ((u, v), (w, z)) = 1. By definition of the strong product, exactly one of the following will be true. 1) d G (u, w) = 1 and v = z, ) u = w and d H (v, z) = 1, or 3) d G (u, w) = 1 and d H (v, z) = 1. We show that g((u, v)) g((w, z)) = 0 in each of the above cases. 1) Assume d G (u, w) = 1 and v = z. Since f 1 is a proper -tone coloring of G, f 1 (u) f 1 (w) =. Thus, we can write f 1 (u) = c 1, c and f 1 (w) = c 3, c 4 where c i c j for 1 i < j 4. Since f (v) = f (z), we know for i 1, and j 3, 4 that c i + f (v) c j + f (z). Therefore, g((u, v)) g((w, z)) = 0. ) Assume u = w and d H (v, z) = 1. Since f is a proper distance (, k)-coloring of H, f (v) f (z) and we may write f (v) = iτ (G) + 1 and f (z) = jτ (G) + 1 for some 0 i < j k 1. Let f 1 (u) = c 1, c where c 1 c. Thus, g((u, v)) = c 1 + iτ (G) + 1, c + iτ (G) + 1 and g((w, z)) = c 1 + jτ (G) + 1, c + jτ (G) + 1. It is clear that c 1 + iτ (G) + 1 c 1 + jτ (G) + 1 since i < j. Similarly, c + iτ (G) + 1 c + jτ (G) + 1. Note that if c 1 + iτ (G) + 1 = c + jτ (G) + 1, then c 1 c = (j 1)τ (G). We know that c 1 c 0 since i < j. On the other hand, c 1 c cannot be a multiple of τ (G) since 1 c 1, c τ (G). Therefore, and a similar argument shows that Thus, g((u, v)) g((w, z)) = 0. c 1 + iτ (G) + 1 c + jτ (G) + 1, c + iτ (G) + 1 c 1 + jτ (G) ) Assume d G (u, w) = 1 and d H (v, z) = 1. It follows that f 1 (u) f 1 (w) = and f (v) f (z). As before, let f 1 (u) = c 1, c and f 1 (w) = c 3, c 4 where c a c b when 1 a < b 4. Also, write f (v) = iτ (G) + 1 and f (z) = jτ (G) + 1 for some 0 i < j k 1. Thus, g((u, v)) = c 1 + iτ (G) + 1, c + iτ (G) + 1 and g((w, z)) = c 3 + jτ (G) + 1, c 4 + jτ (G)

18 Again, we see that c 1 +iτ (G)+1 c +iτ (G)+1 since c 1 c. Similarly, c 3 +jτ (G)+1 c 4 + jτ (G) + 1 since c 3 c 4. Furthermore, for any a 1, and b 3, 4, we know c a + iτ (G) + 1 c b + jτ (G) + 1 since c a c b cannot be a multiple of τ (G). Therefore, g((u, v)) g((w, z)) = 0. Case : Assume that d G H ((u, v), (w, z)) =. Necessarily, d G (u, w) and d H (v, z). Thus, f 1 (u) f 1 (w) 1 so there exist a f 1 (u) and b f 1 (w) such that a b. Furthermore, since d H (v, z), we may assume there exist 0 i < j k 1 such that f (v) = iτ (G) + 1 and f (z) = jτ (G) + 1. We have already seen that this implies a + iτ (G) + 1 b + jτ (G) + 1 since i < j and 1 a, b τ (G). Therefore, g((u, v)) g((w, z)) 1. Note that for P 3 P 3, we can find a -tone 6-coloring as shown in Figure 10. This coloring is best possible since P 3 P 3 contains C 4 and τ (C 4 ) = 6. However, in this case Theorem 5 gives bounds of 5 = maxτ (P 3 P 3 ), τ (P 3 P 3 ) τ (P 3 P 3 ) minτ (G)χ(H ), χ(g )τ (H) = 15. This alone shows that perhaps a better upper bound exists in terms of other graph properties. On the other hand, K 3 K 3 K 9 so we know τ (K 3 K 3 ) = 18 as seen in Figure 11. In this particular case, we have 6 = minτ (K 3 K 3 ), τ (K 3 K 3 ) τ (K 3 K 3 ) minτ (G)χ(H ), χ(g )τ (H) = 18, which shows the upper bound in Theorem 5 is sharp. References [1] [] A. Bickle and B. Phillips. t-tone Colorings of Graphs (Submitted) [3] D. Cranston, J. Kim, and W. Kinnersley. New Results in t-tone colorings of graphs. preprint, 011. [4] J. Fonger, B. Phillips, and C. Segroves. Math 6450 Final Report

19 1,4,3 5,6 3,5 1,6,4 1, 3,4 1,5 Figure 10: P 3 P 3 13,14 15,16 17,18 7,8 9,10 11,1 1, 3,4 5,6 Figure 11: K 3 K 3 19

Best Monotone Degree Bounds for Various Graph Parameters

Best Monotone Degree Bounds for Various Graph Parameters Best Monotone Degree Bounds for Various Graph Parameters D. Bauer Department of Mathematical Sciences Stevens Institute of Technology Hoboken, NJ 07030 S. L. Hakimi Department of Electrical and Computer

More information

Labeling outerplanar graphs with maximum degree three

Labeling outerplanar graphs with maximum degree three Labeling outerplanar graphs with maximum degree three Xiangwen Li 1 and Sanming Zhou 2 1 Department of Mathematics Huazhong Normal University, Wuhan 430079, China 2 Department of Mathematics and Statistics

More information

On Integer Additive Set-Indexers of Graphs

On Integer Additive Set-Indexers of Graphs On Integer Additive Set-Indexers of Graphs arxiv:1312.7672v4 [math.co] 2 Mar 2014 N K Sudev and K A Germina Abstract A set-indexer of a graph G is an injective set-valued function f : V (G) 2 X such that

More information

A 2-factor in which each cycle has long length in claw-free graphs

A 2-factor in which each cycle has long length in claw-free graphs A -factor in which each cycle has long length in claw-free graphs Roman Čada Shuya Chiba Kiyoshi Yoshimoto 3 Department of Mathematics University of West Bohemia and Institute of Theoretical Computer Science

More information

ON INDUCED SUBGRAPHS WITH ALL DEGREES ODD. 1. Introduction

ON INDUCED SUBGRAPHS WITH ALL DEGREES ODD. 1. Introduction ON INDUCED SUBGRAPHS WITH ALL DEGREES ODD A.D. SCOTT Abstract. Gallai proved that the vertex set of any graph can be partitioned into two sets, each inducing a subgraph with all degrees even. We prove

More information

Large induced subgraphs with all degrees odd

Large induced subgraphs with all degrees odd Large induced subgraphs with all degrees odd A.D. Scott Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, England Abstract: We prove that every connected graph of order

More information

Handout #Ch7 San Skulrattanakulchai Gustavus Adolphus College Dec 6, 2010. Chapter 7: Digraphs

Handout #Ch7 San Skulrattanakulchai Gustavus Adolphus College Dec 6, 2010. Chapter 7: Digraphs MCS-236: Graph Theory Handout #Ch7 San Skulrattanakulchai Gustavus Adolphus College Dec 6, 2010 Chapter 7: Digraphs Strong Digraphs Definitions. A digraph is an ordered pair (V, E), where V is the set

More information

SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH

SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH 31 Kragujevac J. Math. 25 (2003) 31 49. SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH Kinkar Ch. Das Department of Mathematics, Indian Institute of Technology, Kharagpur 721302, W.B.,

More information

Zachary Monaco Georgia College Olympic Coloring: Go For The Gold

Zachary Monaco Georgia College Olympic Coloring: Go For The Gold Zachary Monaco Georgia College Olympic Coloring: Go For The Gold Coloring the vertices or edges of a graph leads to a variety of interesting applications in graph theory These applications include various

More information

Mean Ramsey-Turán numbers

Mean Ramsey-Turán numbers Mean Ramsey-Turán numbers Raphael Yuster Department of Mathematics University of Haifa at Oranim Tivon 36006, Israel Abstract A ρ-mean coloring of a graph is a coloring of the edges such that the average

More information

The positive minimum degree game on sparse graphs

The positive minimum degree game on sparse graphs The positive minimum degree game on sparse graphs József Balogh Department of Mathematical Sciences University of Illinois, USA jobal@math.uiuc.edu András Pluhár Department of Computer Science University

More information

Lecture 17 : Equivalence and Order Relations DRAFT

Lecture 17 : Equivalence and Order Relations DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion

More information

UPPER BOUNDS ON THE L(2, 1)-LABELING NUMBER OF GRAPHS WITH MAXIMUM DEGREE

UPPER BOUNDS ON THE L(2, 1)-LABELING NUMBER OF GRAPHS WITH MAXIMUM DEGREE UPPER BOUNDS ON THE L(2, 1)-LABELING NUMBER OF GRAPHS WITH MAXIMUM DEGREE ANDREW LUM ADVISOR: DAVID GUICHARD ABSTRACT. L(2,1)-labeling was first defined by Jerrold Griggs [Gr, 1992] as a way to use graphs

More information

Ph.D. Thesis. Judit Nagy-György. Supervisor: Péter Hajnal Associate Professor

Ph.D. Thesis. Judit Nagy-György. Supervisor: Péter Hajnal Associate Professor Online algorithms for combinatorial problems Ph.D. Thesis by Judit Nagy-György Supervisor: Péter Hajnal Associate Professor Doctoral School in Mathematics and Computer Science University of Szeged Bolyai

More information

BOUNDARY EDGE DOMINATION IN GRAPHS

BOUNDARY EDGE DOMINATION IN GRAPHS BULLETIN OF THE INTERNATIONAL MATHEMATICAL VIRTUAL INSTITUTE ISSN (p) 0-4874, ISSN (o) 0-4955 www.imvibl.org /JOURNALS / BULLETIN Vol. 5(015), 197-04 Former BULLETIN OF THE SOCIETY OF MATHEMATICIANS BANJA

More information

Outline 2.1 Graph Isomorphism 2.2 Automorphisms and Symmetry 2.3 Subgraphs, part 1

Outline 2.1 Graph Isomorphism 2.2 Automorphisms and Symmetry 2.3 Subgraphs, part 1 GRAPH THEORY LECTURE STRUCTURE AND REPRESENTATION PART A Abstract. Chapter focuses on the question of when two graphs are to be regarded as the same, on symmetries, and on subgraphs.. discusses the concept

More information

Introduction to Graph Theory

Introduction to Graph Theory Introduction to Graph Theory Allen Dickson October 2006 1 The Königsberg Bridge Problem The city of Königsberg was located on the Pregel river in Prussia. The river divided the city into four separate

More information

P. Jeyanthi and N. Angel Benseera

P. Jeyanthi and N. Angel Benseera Opuscula Math. 34, no. 1 (014), 115 1 http://dx.doi.org/10.7494/opmath.014.34.1.115 Opuscula Mathematica A TOTALLY MAGIC CORDIAL LABELING OF ONE-POINT UNION OF n COPIES OF A GRAPH P. Jeyanthi and N. Angel

More information

Cycles and clique-minors in expanders

Cycles and clique-minors in expanders Cycles and clique-minors in expanders Benny Sudakov UCLA and Princeton University Expanders Definition: The vertex boundary of a subset X of a graph G: X = { all vertices in G\X with at least one neighbor

More information

Math 55: Discrete Mathematics

Math 55: Discrete Mathematics Math 55: Discrete Mathematics UC Berkeley, Fall 2011 Homework # 5, due Wednesday, February 22 5.1.4 Let P (n) be the statement that 1 3 + 2 3 + + n 3 = (n(n + 1)/2) 2 for the positive integer n. a) What

More information

Midterm Practice Problems

Midterm Practice Problems 6.042/8.062J Mathematics for Computer Science October 2, 200 Tom Leighton, Marten van Dijk, and Brooke Cowan Midterm Practice Problems Problem. [0 points] In problem set you showed that the nand operator

More information

Connectivity and cuts

Connectivity and cuts Math 104, Graph Theory February 19, 2013 Measure of connectivity How connected are each of these graphs? > increasing connectivity > I G 1 is a tree, so it is a connected graph w/minimum # of edges. Every

More information

. 0 1 10 2 100 11 1000 3 20 1 2 3 4 5 6 7 8 9

. 0 1 10 2 100 11 1000 3 20 1 2 3 4 5 6 7 8 9 Introduction The purpose of this note is to find and study a method for determining and counting all the positive integer divisors of a positive integer Let N be a given positive integer We say d is a

More information

On the crossing number of K m,n

On the crossing number of K m,n On the crossing number of K m,n Nagi H. Nahas nnahas@acm.org Submitted: Mar 15, 001; Accepted: Aug 10, 00; Published: Aug 1, 00 MR Subject Classifications: 05C10, 05C5 Abstract The best lower bound known

More information

8. Matchings and Factors

8. Matchings and Factors 8. Matchings and Factors Consider the formation of an executive council by the parliament committee. Each committee needs to designate one of its members as an official representative to sit on the council,

More information

Pigeonhole Principle Solutions

Pigeonhole Principle Solutions Pigeonhole Principle Solutions 1. Show that if we take n + 1 numbers from the set {1, 2,..., 2n}, then some pair of numbers will have no factors in common. Solution: Note that consecutive numbers (such

More information

Exponential time algorithms for graph coloring

Exponential time algorithms for graph coloring Exponential time algorithms for graph coloring Uriel Feige Lecture notes, March 14, 2011 1 Introduction Let [n] denote the set {1,..., k}. A k-labeling of vertices of a graph G(V, E) is a function V [k].

More information

Discrete Mathematics Problems

Discrete Mathematics Problems Discrete Mathematics Problems William F. Klostermeyer School of Computing University of North Florida Jacksonville, FL 32224 E-mail: wkloster@unf.edu Contents 0 Preface 3 1 Logic 5 1.1 Basics...............................

More information

On an anti-ramsey type result

On an anti-ramsey type result On an anti-ramsey type result Noga Alon, Hanno Lefmann and Vojtĕch Rödl Abstract We consider anti-ramsey type results. For a given coloring of the k-element subsets of an n-element set X, where two k-element

More information

The chromatic spectrum of mixed hypergraphs

The chromatic spectrum of mixed hypergraphs The chromatic spectrum of mixed hypergraphs Tao Jiang, Dhruv Mubayi, Zsolt Tuza, Vitaly Voloshin, Douglas B. West March 30, 2003 Abstract A mixed hypergraph is a triple H = (X, C, D), where X is the vertex

More information

On three zero-sum Ramsey-type problems

On three zero-sum Ramsey-type problems On three zero-sum Ramsey-type problems Noga Alon Department of Mathematics Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University, Tel Aviv, Israel and Yair Caro Department of Mathematics

More information

On the independence number of graphs with maximum degree 3

On the independence number of graphs with maximum degree 3 On the independence number of graphs with maximum degree 3 Iyad A. Kanj Fenghui Zhang Abstract Let G be an undirected graph with maximum degree at most 3 such that G does not contain any of the three graphs

More information

Product irregularity strength of certain graphs

Product irregularity strength of certain graphs Also available at http://amc.imfm.si ISSN 1855-3966 (printed edn.), ISSN 1855-3974 (electronic edn.) ARS MATHEMATICA CONTEMPORANEA 7 (014) 3 9 Product irregularity strength of certain graphs Marcin Anholcer

More information

Graphs without proper subgraphs of minimum degree 3 and short cycles

Graphs without proper subgraphs of minimum degree 3 and short cycles Graphs without proper subgraphs of minimum degree 3 and short cycles Lothar Narins, Alexey Pokrovskiy, Tibor Szabó Department of Mathematics, Freie Universität, Berlin, Germany. August 22, 2014 Abstract

More information

Triangle deletion. Ernie Croot. February 3, 2010

Triangle deletion. Ernie Croot. February 3, 2010 Triangle deletion Ernie Croot February 3, 2010 1 Introduction The purpose of this note is to give an intuitive outline of the triangle deletion theorem of Ruzsa and Szemerédi, which says that if G = (V,

More information

arxiv:1203.1525v1 [math.co] 7 Mar 2012

arxiv:1203.1525v1 [math.co] 7 Mar 2012 Constructing subset partition graphs with strong adjacency and end-point count properties Nicolai Hähnle haehnle@math.tu-berlin.de arxiv:1203.1525v1 [math.co] 7 Mar 2012 March 8, 2012 Abstract Kim defined

More information

COMBINATORIAL PROPERTIES OF THE HIGMAN-SIMS GRAPH. 1. Introduction

COMBINATORIAL PROPERTIES OF THE HIGMAN-SIMS GRAPH. 1. Introduction COMBINATORIAL PROPERTIES OF THE HIGMAN-SIMS GRAPH ZACHARY ABEL 1. Introduction In this survey we discuss properties of the Higman-Sims graph, which has 100 vertices, 1100 edges, and is 22 regular. In fact

More information

3. Eulerian and Hamiltonian Graphs

3. Eulerian and Hamiltonian Graphs 3. Eulerian and Hamiltonian Graphs There are many games and puzzles which can be analysed by graph theoretic concepts. In fact, the two early discoveries which led to the existence of graphs arose from

More information

Lecture 1: Course overview, circuits, and formulas

Lecture 1: Course overview, circuits, and formulas Lecture 1: Course overview, circuits, and formulas Topics in Complexity Theory and Pseudorandomness (Spring 2013) Rutgers University Swastik Kopparty Scribes: John Kim, Ben Lund 1 Course Information Swastik

More information

1 if 1 x 0 1 if 0 x 1

1 if 1 x 0 1 if 0 x 1 Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

More information

A Turán Type Problem Concerning the Powers of the Degrees of a Graph

A Turán Type Problem Concerning the Powers of the Degrees of a Graph A Turán Type Problem Concerning the Powers of the Degrees of a Graph Yair Caro and Raphael Yuster Department of Mathematics University of Haifa-ORANIM, Tivon 36006, Israel. AMS Subject Classification:

More information

FRACTIONAL COLORINGS AND THE MYCIELSKI GRAPHS

FRACTIONAL COLORINGS AND THE MYCIELSKI GRAPHS FRACTIONAL COLORINGS AND THE MYCIELSKI GRAPHS By G. Tony Jacobs Under the Direction of Dr. John S. Caughman A math 501 project submitted in partial fulfillment of the requirements for the degree of Master

More information

Non-Separable Detachments of Graphs

Non-Separable Detachments of Graphs Egerváry Research Group on Combinatorial Optimization Technical reports TR-2001-12. Published by the Egrerváry Research Group, Pázmány P. sétány 1/C, H 1117, Budapest, Hungary. Web site: www.cs.elte.hu/egres.

More information

PUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.

PUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5. PUTNAM TRAINING POLYNOMIALS (Last updated: November 17, 2015) Remark. This is a list of exercises on polynomials. Miguel A. Lerma Exercises 1. Find a polynomial with integral coefficients whose zeros include

More information

An inequality for the group chromatic number of a graph

An inequality for the group chromatic number of a graph An inequality for the group chromatic number of a graph Hong-Jian Lai 1, Xiangwen Li 2 and Gexin Yu 3 1 Department of Mathematics, West Virginia University Morgantown, WV 26505 USA 2 Department of Mathematics

More information

SEQUENCES OF MAXIMAL DEGREE VERTICES IN GRAPHS. Nickolay Khadzhiivanov, Nedyalko Nenov

SEQUENCES OF MAXIMAL DEGREE VERTICES IN GRAPHS. Nickolay Khadzhiivanov, Nedyalko Nenov Serdica Math. J. 30 (2004), 95 102 SEQUENCES OF MAXIMAL DEGREE VERTICES IN GRAPHS Nickolay Khadzhiivanov, Nedyalko Nenov Communicated by V. Drensky Abstract. Let Γ(M) where M V (G) be the set of all vertices

More information

Math 319 Problem Set #3 Solution 21 February 2002

Math 319 Problem Set #3 Solution 21 February 2002 Math 319 Problem Set #3 Solution 21 February 2002 1. ( 2.1, problem 15) Find integers a 1, a 2, a 3, a 4, a 5 such that every integer x satisfies at least one of the congruences x a 1 (mod 2), x a 2 (mod

More information

About the inverse football pool problem for 9 games 1

About the inverse football pool problem for 9 games 1 Seventh International Workshop on Optimal Codes and Related Topics September 6-1, 013, Albena, Bulgaria pp. 15-133 About the inverse football pool problem for 9 games 1 Emil Kolev Tsonka Baicheva Institute

More information

Global secure sets of trees and grid-like graphs. Yiu Yu Ho

Global secure sets of trees and grid-like graphs. Yiu Yu Ho Global secure sets of trees and grid-like graphs by Yiu Yu Ho B.S. University of Central Florida, 2006 M.S. University of Central Florida, 2010 A dissertation submitted in partial fulfillment of the requirements

More information

Inner Product Spaces

Inner Product Spaces Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and

More information

Approximation Algorithms

Approximation Algorithms Approximation Algorithms or: How I Learned to Stop Worrying and Deal with NP-Completeness Ong Jit Sheng, Jonathan (A0073924B) March, 2012 Overview Key Results (I) General techniques: Greedy algorithms

More information

Tools for parsimonious edge-colouring of graphs with maximum degree three. J.L. Fouquet and J.M. Vanherpe. Rapport n o RR-2010-10

Tools for parsimonious edge-colouring of graphs with maximum degree three. J.L. Fouquet and J.M. Vanherpe. Rapport n o RR-2010-10 Tools for parsimonious edge-colouring of graphs with maximum degree three J.L. Fouquet and J.M. Vanherpe LIFO, Université d Orléans Rapport n o RR-2010-10 Tools for parsimonious edge-colouring of graphs

More information

Lecture 16 : Relations and Functions DRAFT

Lecture 16 : Relations and Functions DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/29/2011 Lecture 16 : Relations and Functions Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT In Lecture 3, we described a correspondence

More information

Collinear Points in Permutations

Collinear Points in Permutations Collinear Points in Permutations Joshua N. Cooper Courant Institute of Mathematics New York University, New York, NY József Solymosi Department of Mathematics University of British Columbia, Vancouver,

More information

Graph Theory Problems and Solutions

Graph Theory Problems and Solutions raph Theory Problems and Solutions Tom Davis tomrdavis@earthlink.net http://www.geometer.org/mathcircles November, 005 Problems. Prove that the sum of the degrees of the vertices of any finite graph is

More information

On end degrees and infinite cycles in locally finite graphs

On end degrees and infinite cycles in locally finite graphs On end degrees and infinite cycles in locally finite graphs Henning Bruhn Maya Stein Abstract We introduce a natural extension of the vertex degree to ends. For the cycle space C(G) as proposed by Diestel

More information

Every tree contains a large induced subgraph with all degrees odd

Every tree contains a large induced subgraph with all degrees odd Every tree contains a large induced subgraph with all degrees odd A.J. Radcliffe Carnegie Mellon University, Pittsburgh, PA A.D. Scott Department of Pure Mathematics and Mathematical Statistics University

More information

Class One: Degree Sequences

Class One: Degree Sequences Class One: Degree Sequences For our purposes a graph is a just a bunch of points, called vertices, together with lines or curves, called edges, joining certain pairs of vertices. Three small examples of

More information

A Sublinear Bipartiteness Tester for Bounded Degree Graphs

A Sublinear Bipartiteness Tester for Bounded Degree Graphs A Sublinear Bipartiteness Tester for Bounded Degree Graphs Oded Goldreich Dana Ron February 5, 1998 Abstract We present a sublinear-time algorithm for testing whether a bounded degree graph is bipartite

More information

The degree, size and chromatic index of a uniform hypergraph

The degree, size and chromatic index of a uniform hypergraph The degree, size and chromatic index of a uniform hypergraph Noga Alon Jeong Han Kim Abstract Let H be a k-uniform hypergraph in which no two edges share more than t common vertices, and let D denote the

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete

More information

All trees contain a large induced subgraph having all degrees 1 (mod k)

All trees contain a large induced subgraph having all degrees 1 (mod k) All trees contain a large induced subgraph having all degrees 1 (mod k) David M. Berman, A.J. Radcliffe, A.D. Scott, Hong Wang, and Larry Wargo *Department of Mathematics University of New Orleans New

More information

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called

More information

CS 598CSC: Combinatorial Optimization Lecture date: 2/4/2010

CS 598CSC: Combinatorial Optimization Lecture date: 2/4/2010 CS 598CSC: Combinatorial Optimization Lecture date: /4/010 Instructor: Chandra Chekuri Scribe: David Morrison Gomory-Hu Trees (The work in this section closely follows [3]) Let G = (V, E) be an undirected

More information

On the k-path cover problem for cacti

On the k-path cover problem for cacti On the k-path cover problem for cacti Zemin Jin and Xueliang Li Center for Combinatorics and LPMC Nankai University Tianjin 300071, P.R. China zeminjin@eyou.com, x.li@eyou.com Abstract In this paper we

More information

Odd induced subgraphs in graphs of maximum degree three

Odd induced subgraphs in graphs of maximum degree three Odd induced subgraphs in graphs of maximum degree three David M. Berman, Hong Wang, and Larry Wargo Department of Mathematics University of New Orleans New Orleans, Louisiana, USA 70148 Abstract A long-standing

More information

No: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics

No: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics No: 10 04 Bilkent University Monotonic Extension Farhad Husseinov Discussion Papers Department of Economics The Discussion Papers of the Department of Economics are intended to make the initial results

More information

Types of Degrees in Bipolar Fuzzy Graphs

Types of Degrees in Bipolar Fuzzy Graphs pplied Mathematical Sciences, Vol. 7, 2013, no. 98, 4857-4866 HIKRI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2013.37389 Types of Degrees in Bipolar Fuzzy Graphs Basheer hamed Mohideen Department

More information

Introduced by Stuart Kauffman (ca. 1986) as a tunable family of fitness landscapes.

Introduced by Stuart Kauffman (ca. 1986) as a tunable family of fitness landscapes. 68 Part II. Combinatorial Models can require a number of spin flips that is exponential in N (A. Haken et al. ca. 1989), and that one can in fact embed arbitrary computations in the dynamics (Orponen 1995).

More information

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing

More information

k, then n = p2α 1 1 pα k

k, then n = p2α 1 1 pα k Powers of Integers An integer n is a perfect square if n = m for some integer m. Taking into account the prime factorization, if m = p α 1 1 pα k k, then n = pα 1 1 p α k k. That is, n is a perfect square

More information

Definition 11.1. Given a graph G on n vertices, we define the following quantities:

Definition 11.1. Given a graph G on n vertices, we define the following quantities: Lecture 11 The Lovász ϑ Function 11.1 Perfect graphs We begin with some background on perfect graphs. graphs. First, we define some quantities on Definition 11.1. Given a graph G on n vertices, we define

More information

TU e. Advanced Algorithms: experimentation project. The problem: load balancing with bounded look-ahead. Input: integer m 2: number of machines

TU e. Advanced Algorithms: experimentation project. The problem: load balancing with bounded look-ahead. Input: integer m 2: number of machines The problem: load balancing with bounded look-ahead Input: integer m 2: number of machines integer k 0: the look-ahead numbers t 1,..., t n : the job sizes Problem: assign jobs to machines machine to which

More information

Just the Factors, Ma am

Just the Factors, Ma am 1 Introduction Just the Factors, Ma am The purpose of this note is to find and study a method for determining and counting all the positive integer divisors of a positive integer Let N be a given positive

More information

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely

More information

5 Directed acyclic graphs

5 Directed acyclic graphs 5 Directed acyclic graphs (5.1) Introduction In many statistical studies we have prior knowledge about a temporal or causal ordering of the variables. In this chapter we will use directed graphs to incorporate

More information

136 CHAPTER 4. INDUCTION, GRAPHS AND TREES

136 CHAPTER 4. INDUCTION, GRAPHS AND TREES 136 TER 4. INDUCTION, GRHS ND TREES 4.3 Graphs In this chapter we introduce a fundamental structural idea of discrete mathematics, that of a graph. Many situations in the applications of discrete mathematics

More information

Degree Hypergroupoids Associated with Hypergraphs

Degree Hypergroupoids Associated with Hypergraphs Filomat 8:1 (014), 119 19 DOI 10.98/FIL1401119F Published by Faculty of Sciences and Mathematics, University of Niš, Serbia Available at: http://www.pmf.ni.ac.rs/filomat Degree Hypergroupoids Associated

More information

THE BANACH CONTRACTION PRINCIPLE. Contents

THE BANACH CONTRACTION PRINCIPLE. Contents THE BANACH CONTRACTION PRINCIPLE ALEX PONIECKI Abstract. This paper will study contractions of metric spaces. To do this, we will mainly use tools from topology. We will give some examples of contractions,

More information

Minimum degree condition forcing complete graph immersion

Minimum degree condition forcing complete graph immersion Minimum degree condition forcing complete graph immersion Matt DeVos Department of Mathematics Simon Fraser University Burnaby, B.C. V5A 1S6 Jacob Fox Department of Mathematics MIT Cambridge, MA 02139

More information

A simple criterion on degree sequences of graphs

A simple criterion on degree sequences of graphs Discrete Applied Mathematics 156 (2008) 3513 3517 Contents lists available at ScienceDirect Discrete Applied Mathematics journal homepage: www.elsevier.com/locate/dam Note A simple criterion on degree

More information

GRAPH THEORY LECTURE 4: TREES

GRAPH THEORY LECTURE 4: TREES GRAPH THEORY LECTURE 4: TREES Abstract. 3.1 presents some standard characterizations and properties of trees. 3.2 presents several different types of trees. 3.7 develops a counting method based on a bijection

More information

DETERMINANTS IN THE KRONECKER PRODUCT OF MATRICES: THE INCIDENCE MATRIX OF A COMPLETE GRAPH

DETERMINANTS IN THE KRONECKER PRODUCT OF MATRICES: THE INCIDENCE MATRIX OF A COMPLETE GRAPH DETERMINANTS IN THE KRONECKER PRODUCT OF MATRICES: THE INCIDENCE MATRIX OF A COMPLETE GRAPH CHRISTOPHER RH HANUSA AND THOMAS ZASLAVSKY Abstract We investigate the least common multiple of all subdeterminants,

More information

Lecture 7: NP-Complete Problems

Lecture 7: NP-Complete Problems IAS/PCMI Summer Session 2000 Clay Mathematics Undergraduate Program Basic Course on Computational Complexity Lecture 7: NP-Complete Problems David Mix Barrington and Alexis Maciel July 25, 2000 1. Circuit

More information

Clique coloring B 1 -EPG graphs

Clique coloring B 1 -EPG graphs Clique coloring B 1 -EPG graphs Flavia Bonomo a,c, María Pía Mazzoleni b,c, and Maya Stein d a Departamento de Computación, FCEN-UBA, Buenos Aires, Argentina. b Departamento de Matemática, FCE-UNLP, La

More information

Tenacity and rupture degree of permutation graphs of complete bipartite graphs

Tenacity and rupture degree of permutation graphs of complete bipartite graphs Tenacity and rupture degree of permutation graphs of complete bipartite graphs Fengwei Li, Qingfang Ye and Xueliang Li Department of mathematics, Shaoxing University, Shaoxing Zhejiang 312000, P.R. China

More information

1 The Line vs Point Test

1 The Line vs Point Test 6.875 PCP and Hardness of Approximation MIT, Fall 2010 Lecture 5: Low Degree Testing Lecturer: Dana Moshkovitz Scribe: Gregory Minton and Dana Moshkovitz Having seen a probabilistic verifier for linearity

More information

3. Mathematical Induction

3. Mathematical Induction 3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)

More information

Vector and Matrix Norms

Vector and Matrix Norms Chapter 1 Vector and Matrix Norms 11 Vector Spaces Let F be a field (such as the real numbers, R, or complex numbers, C) with elements called scalars A Vector Space, V, over the field F is a non-empty

More information

Mathematical Induction

Mathematical Induction Mathematical Induction (Handout March 8, 01) The Principle of Mathematical Induction provides a means to prove infinitely many statements all at once The principle is logical rather than strictly mathematical,

More information

Computer Science Department. Technion - IIT, Haifa, Israel. Itai and Rodeh [IR] have proved that for any 2-connected graph G and any vertex s G there

Computer Science Department. Technion - IIT, Haifa, Israel. Itai and Rodeh [IR] have proved that for any 2-connected graph G and any vertex s G there - 1 - THREE TREE-PATHS Avram Zehavi Alon Itai Computer Science Department Technion - IIT, Haifa, Israel Abstract Itai and Rodeh [IR] have proved that for any 2-connected graph G and any vertex s G there

More information

Max Flow, Min Cut, and Matchings (Solution)

Max Flow, Min Cut, and Matchings (Solution) Max Flow, Min Cut, and Matchings (Solution) 1. The figure below shows a flow network on which an s-t flow is shown. The capacity of each edge appears as a label next to the edge, and the numbers in boxes

More information

Practice with Proofs

Practice with Proofs Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using

More information

Graphical degree sequences and realizations

Graphical degree sequences and realizations swap Graphical and realizations Péter L. Erdös Alfréd Rényi Institute of Mathematics Hungarian Academy of Sciences MAPCON 12 MPIPKS - Dresden, May 15, 2012 swap Graphical and realizations Péter L. Erdös

More information

M-Degrees of Quadrangle-Free Planar Graphs

M-Degrees of Quadrangle-Free Planar Graphs M-Degrees of Quadrangle-Free Planar Graphs Oleg V. Borodin, 1 Alexandr V. Kostochka, 1,2 Naeem N. Sheikh, 2 and Gexin Yu 3 1 SOBOLEV INSTITUTE OF MATHEMATICS NOVOSIBIRSK 630090, RUSSIA E-mail: brdnoleg@math.nsc.ru

More information

So let us begin our quest to find the holy grail of real analysis.

So let us begin our quest to find the holy grail of real analysis. 1 Section 5.2 The Complete Ordered Field: Purpose of Section We present an axiomatic description of the real numbers as a complete ordered field. The axioms which describe the arithmetic of the real numbers

More information

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are

More information

SYSTEMS OF PYTHAGOREAN TRIPLES. Acknowledgements. I would like to thank Professor Laura Schueller for advising and guiding me

SYSTEMS OF PYTHAGOREAN TRIPLES. Acknowledgements. I would like to thank Professor Laura Schueller for advising and guiding me SYSTEMS OF PYTHAGOREAN TRIPLES CHRISTOPHER TOBIN-CAMPBELL Abstract. This paper explores systems of Pythagorean triples. It describes the generating formulas for primitive Pythagorean triples, determines

More information

8 Primes and Modular Arithmetic

8 Primes and Modular Arithmetic 8 Primes and Modular Arithmetic 8.1 Primes and Factors Over two millennia ago already, people all over the world were considering the properties of numbers. One of the simplest concepts is prime numbers.

More information

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem

More information