The number of edges in a bipartite graph of given radius

Size: px
Start display at page:

Download "The number of edges in a bipartite graph of given radius"

Transcription

1 The number of edges in a bipartite graph of given radius P. Dankelmann, Henda C. Swart, P. van den Berg University of KwaZulu-Natal, Durban, South Africa Abstract Vizing established an upper bound on the size of a graph of given order and radius. We find a sharp upper bound on the size of a bipartite graph of given order and radius. 1 Introduction Let G be a connected graph with vertex set V (G) and edge set E(G). The order of G is n = V (G), and the size is m = E(G). The distance d G (u, v) between two vertices u and v is the number of edges in a shortest u v path in G. The eccentricity e G (v) of v is the distance from v to a vertex farthest away from it in G. The radius of G, rad(g), is the minimum eccentricity of G, that is rad(g) = min v V (G) e G (v), and the diameter of G, diam(g), is the maximum eccentricity of G, that is diam(g) = max v V (G) e G (v). Several bounds on the radius in terms of other graph parameters are known. Erdös, Pach, Pollack and Tuza [4] proved that if G is a connected graph of order n and minimum degree δ, then rad(g) 3(n 3) (δ + 1) + 5, and also constructed graphs that, apart from the additive constant, attain the bound and, moreover, they gave improved bounds for K 3 -free and C 4 -free Support by the South African National Research Foundation is gratefully acknowledged. 1

2 graphs. Using different methods, Dankelmann, Dlamini and Swart [1,, 3] obtained slight improvements of their bounds. Dankelmann, Mukwembi and Swart [9] proved that if G is a 3 edgeconnected graph of order n, then rad(g) 1 3 n In [10], Mukwembi proved that if G is also bipartite, then rad(g) 3 10 n , and both bounds are sharp, apart from an additive constant. Definition 1 Let n and r be any natural numbers such that n r. Define f(n, r) to be the maximum number of edges in a a graph of order n and radius r, and C(n, r) to be the set of all graphs of order n, radius r, and size f(n, r). Vizing [13] gave the following bound on the size of a connected graph in terms of order and radius. Theorem 1 [13] For any natural numbers n and r such that n r, a) f(n, 1) = 1 n(n 1) b) f(n, ) = 1n(n 1) 1n = 1 n(n ) c) f(n, r) = 1 (n 4rn + 5n + 4r 6r) for n r 6. The graph with radius 1 and the maximum number of edges is the complete graph. C(n, ) consists of all graphs obtained from K n by removing 1 n edges covering V (K n). Examples for graphs in C(n, r), n r 6, consist of a complete graph K n r and a cycle C r, where every vertex of the K n r is joined to the same three consecutive vertices of C r. The goal of this paper is to establish a similar sharp upper bound on the size of a connected, bipartite graph of given radius and order (see Theorem ), and to determine all graphs attaining that bound. The notation we use is as follows. The degree of a vertex v of G, denoted by deg G (v), is the number of vertices adjacent to v. The maximum degree

3 and the minimum degree of G are denoted by (G) and δ(g), respectively. The neighbourhood N G (v) of a vertex v is the set of vertices adjacent to v in G. A set S of vertices is called a cutset if its deletion increases the number of components. A vertex v is called a cut-vertex if {v} is a cutset, and a non-cut vertex or ncv otherwise. A vertex x is said to be separated from a vertex y by a vertex v if v lies on every x y path (i.e., if x and y are in different components of G v). If S V (G), then S G denotes the subgraph of G induced by S. When the graph is understood, then we sometimes drop the argument or subscript G. The join G 1 + G of two vertex disjoint graphs G 1 and G is the graph consisting of the union G 1 G, together with all edges of the type xy, where x V (G 1 ) and y V (G ). For k 3 vertex disjoint graphs G 1, G,..., G k, the sequential join G 1 + G G k is the graph (G 1 + G ) (G + G 3 )... (G k 1 + G k ). The sequential join of k disjoint copies of a graph G will be denoted by [k]g, the union of k disjoint copies of G will be denoted by kg, while [k 1 ]G 1 + G + [k 3 ]G 3 will denote the sequential join G 1 + G G 1 + G + G 3 + G G 3. We write K n and C n for the complete graph and the cycle of order n, respectively. A vertex c of G is called central if e G (c) = rad(g). The centre C(G) is the set of all central vertices in G. An eccentric vertex of a vertex v is a vertex farthest away from v. If there is only one such vertex u, then u is called the unique eccentric point (or uep) of v. A conjugate vertex v of a vertex v is a central vertex which has v as its uep. (So a vertex might have more than one conjugate vertex, or none.) A conjugate pair is a pair of central vertices, each of which is the uep of the other. A spanning tree T of G is said to be radius-preserving if rad(g) = rad(t ). We define a non-trivial graph G to be vertex-radius-decreasing if rad(g v) < rad(g) for every ncv v of G. A graph G is called edge-radius-decreasing or erd if rad(g + e) < rad(g) for every e / E(G). Clearly, the graphs described after Theorem 1 are erd. Erd graphs have been studied by Nishanov [11, 1], Harary and Thomassen [8] and Gliviak, Knor and Soltés [7], but no simple characterizaton is known. Preliminary Results Definition The set B(n, r) consists of all graphs G obtained from C r with three consecutive vertices replaced by ak 1, bk 1, ck 1, where a + c = n r+3, b = n r+3, or a + c = n r+3, b = n r+3. We use the 3

4 ak 1 bk 1 ck 1 Figure 1: An example of a graph in B(n, r). notation V 1(G) = V (ak 1 ck 1 ) and V (G) = V (bk 1 ). (See Figure 1.) Let h(n, r) := n 4 nr + r + n r for n r 8. In the proof of Lemma 1, we denote, for a vertex v of G, the star induced by v and its neighbours by S G (v). Lemma 1 Let G be a connected bipartite graph of order n and radius at least r 4. If u, v V (G) with d(u, v), then deg G (u) + deg G (v) n r + 4. If deg G (u) + deg G (v) = n r + 4 then m(g) h(n, r). If deg G (u) + deg G (v) = n r + 4 and m(g) = h(n, r), then G is one of the graphs in the family B(n, r). Proof Let F be the union of the two stars S G (u) and S G (v). Since u and v have no common neighbours, F contains no cycle. Hence there exists a spanning tree T of G containing F. Let P be a diametral path of T. By rad(t ) rad(g) r, we have diam(t ) r 1; so P has at least r vertices. Since P contains at most two neighbours of u and v, respectively, we have Hence V (T ) V (P ) deg T (u) + deg T (v) 4 = deg G (u) + deg G (v) 4. deg G (u) + deg G (v) n V (P ) + 4 n r + 4, as desired. Now assume that deg G (u) + deg G (v) = n r + 4. Then P has exactly r vertices, say, P = w 0, w 1,... w r 1, rad(t ) = r, and u and v are internal 4

5 vertices of P, say u = w a and v = w b ; where (say) a < b. Moreover, T has the following properties: (a) each vertex not on a diametral path is an end-vertex of T and adjacent to u or to v, (b) all vertices other than u or v have degree at most in T. To see that these two properties hold observe that, if one of them is violated, then a diametral path of T misses more than deg G (u) + deg G (v) 4 vertices, and thus has fewer than r vertices, hence T has radius less than r, a contradiction. It is clear that every spanning tree of G containing F has properties (a) and (b). We can choose T to also have the property of preserving the distance between u and v. This can be achieved by considering the union F of F and a u v geodesic in G. Clearly F is a (not necessarily spanning) subtree of G, so there exists a spanning tree T of G containing F which has the desired property. We now consider which edges G can contain, in addition to those of T. We show that, if e E(G) E(T ), then either (i) e = w 0 w r 1, or (ii) e joins a vertex in N G (u) to a vertex in N G (v), or (iii) e = xw a+ or e = xw a for some vertex x N G (w a ) V (P ), or (iv) e = xw b+ or e = xw b for some vertex x N G (w b ) V (P ). Note that the indices are taken modulo r, so if a = r then a vertex x N G (w a ) can be joined to w 0. First assume that e joins two vertices of P. Suppose that e = w i w j with w i w j w 0 w r 1. Then at least one of the end points of e, say w i, has degree at least 3 in T + e. Let w i be such a vertex. Clearly, e is not incident with u or v since u and v have the same degree in G and in T, so w i w a, w b. Consider the union of three stars S G (u), S G (v) and S T +e (w i ), which we denote by F 1. First we show that F 1 contains a cycle. Suppose to the contrary that F 1 is a forest. Then there exists a spanning tree T 1 of G containing F 1. In T 1, vertices u and v have degree deg G (u) + deg G (v), respectively, but v i has degree at least 3, so T 1 does not have property (b), a contradiction. This shows that F 1 contains a cycle C 1. Clearly, C 1 must contain w i and either w a and its two neighbours on P or w b and its two neighbours on P. Without loss of generality, we assume the former, so C 1 contains w a, w a+1, w i, w a 1. So i = a + and e = w a 1 w a+ or i = a and e = w a w a+1. If e = w a 1 w a+ consider the tree T = T w a+1 w a+ + w a 1 w a+. Clearly, u and v have full degree in T, but w a 1 has degree 3, contradicting property (b). Similarly, if 5

6 e = w a w a+1 the tree T = T w a w a 1 +w a w a+1 does not have property (b), a contradiction. Hence w 0 w r 1 is the only edge between two vertices of P present in G but not in T. Now let e E(G) E(T ) be an edge joining a vertex x N G (w a ) V (P ) to a vertex w i on P. Suppose that e is not of type (iii), i.e., that i a, a+. Then either i a + 4 or i a 4. (Note that in this part of the proof, subscripts are not taken modulo r.) Case 1: w i is not a neighbour of w b on P. So i b 1, b + 1. If i a + 3 consider the graph T + xw i, which has the unique cycle w a w a+1 w a+..., w i xw a. Clearly, all edges in the set E := {w a+1 w a+, w a+ w a+3,..., w i w i 1 } are on this cycle, so T +xw i e =: T (e ) is a spanning tree of G for all e E. Since vertex w i has degree 3 in T (e ), and vertex w a has full degree, property (b) implies that in T (e ) vertex w b does not have full degree. So each edge in E is incident with vertex w b. Since only two edges of E can be incident with w b, we have E = {w a+1 w a+, w a+ w a+3 } and w b = w a+. But then w a and w b are at distance, contradicting our hypothesis. If i a 3 then similar arguments lead to the same conclusion. Case : w i is a neighbour of w b on P. So i = b 1 or i = b + 1. Then w a xw i w b is a (w a w b )-path of length 3, so w a and w b are at distance 1 or 3 in T (and in G). First consider the case that w a and w b are at distance 1, so b = a + 1. Then i = b + 1 (since i = b 1 = a is not possible) and thus i = a + ; so e = xw a+, as desired. Now consider the case that w a and w b are at distance 3; hence b = a + 3. But then i {b 1, b + 1} = {a +, a + 4}. If i = a + then e = xw a+, so e is of type (iii). That leaves the case i = b + 1 = a + 4. We show that a + 4 = r 1, i.e., that w a+4 is an end-vertex of P. Suppose to the contrary that r 1 > a + 4. In the tree T w a+1 w a+ + xw a+4 =: T, vertices u and v have full degree and vertex w a+4 has three neighbours, contradicting property (b). Hence a + 4 = r 1. We now show that not all vertices in N G (w b ) are adjacent to a vertex in N G (w a ). Suppose to the contrary that each vertex y N G (w b ) has a neighbour y N G (w a ). Then we can reduce the distance from w a to the end-vertices in N T (w b ) as follows. Consider the tree T = T {yw b y N T (w b ), y w b 1 } + {yy y N T (w b ), y w b 1 }. Since every end-vertex of T, except possibly w 0, is within distance 3 of w a, the distance from w 0 to any end-vertex of T is at most d T (w 0, w a ) + 3 = 6

7 r, while any two end-vertices of T, other than w 0, are within distance at most 5. Hence the diameter of T is at most r 1, which implies rad(t ) r 1, a contradiction to rad(g) r. This proves that there exist a vertex y N G (w b ) not adjacent to any vertex in N G (w a ). Hence, we can obtain, if necessary by renaming y and w r 1, that no vertex in N G (w a ) is adjacent to to vertex w a+4. Hence property (iv) holds. We now show that in addition to properties (i)-(iv) the following holds: (v) if x N G (w a ), then at most one of the edges xw a, xw a+ is present in G, (vi) if y N G (w b ), then at most one of the edges xw b, xw b+ is present in G, (vii) if xy E(G) for some x N G (w a ), y N G (w b ), then b = a + 1 or b = a + 3. To prove (v), suppose that a vertex x N G (a) is adjacent to w a and to w a+. Then the tree T := T {w a w a 1, w a+1 w a+ } + {xw a, xw a+ } preserves the degrees of w a and w b, but has another vertex, namely x of degree 3. This contradicts property (b), and so (v) holds. Similarly, (vi) holds. Property (vii) follows directly from the fact that T preserves the distance between w a and w b in G. Now the bound on the size of G follows easily. In addition to the edges of T, G can only have edges satisfying (i)-(vii). There is only one edge satisfying (i), namely the edge w 0 w r 1. The graph G has at most (deg G (w a ) )(deg G (w b ) ) (n r) edges of the form xy, where x N 4 G (w a ) V (P ) and y N G (w b ) V (P ), that are not in T. Finally, each vertex not on P has at most one edge, not in T joining it to a vertex on P. Hence m(g) m(t ) (deg G (w a ) )(deg G (w b ) ) + (n V (P ) ) n + (n r) + n r 4 = h(n, r), as desired. From the above proof it follows that, if m(g) = h(n, r), then (N G (w a ) N G (w b )) V (P ) G is a balanced, complete bipartite graph of order n r, w 0 w r 1 E(G) and every vertex in N G (w a ) V (P ) (or in N G (w b ) V (P )) is adjacent to either w a+ or w a (or to either w b or w b+, respectively.) We show next that if x N G (w a ) V (P ) and y N G (w b ) V (P ), then it is impossible that both xw a and yw b+ are edges in G. Suppose to the 7

8 contrary that xw a, yw b+ E(G). Then b = a + 3 as otherwise rad(g) < r and consider the spanning tree T of G, where T =: T {w b+1 w b+, w a+1 w a+, w a 1 w a } + {yw b+, xy, xw a }. In T the vertices w a and w b have full degree, while x and y are both of degree 3, which contradicts (b). Consequently, it follows that G B(n, r). We now present propositions that will be needed in the proof of our main result. Proposition 1 [13] For any connected graph G of order n, (G) n rad(g) +. Definition 3 Given integers n, d with 3 d n, define a path-complete bipartite graph as follows: G(n, d) = [d 1 t]k 1 + n d + 1 where 1 t d. K1 + n d + 1 K1 + [t]k 1, Proposition [3] Let G be a bipartite graph of order n and diameter d 3. Then n m(g) 4 nd + 3n + d 4 d 7, 4 with equality if and only if G is a path-complete bipartite graph G(n, d). Proposition 3 [5] Let {v, v } be any conjugate pair in a graph G = K. If G {v, v } is connected, then rad(g {v, v }) rad(g). Proposition 4 [6, 5] Let v be an ncv of a graph G. Then rad(g v) < rad(g) if and only if v has a conjugate vertex, and in this case rad(g v) = rad(g) 1. Proposition 5 [5] Let G be a vertex-radius-decreasing graph, and v a ncv of G. If v is not central, then all its conjugate vertices are cut-vertices. If v is central, then it has exactly one conjugate vertex v, and v is a ncv (so v and v form a conjugate pair). 8

9 Proposition 6 [6, 5] A graph G of order n is a vertex-radius-decreasing block if and only if G is self-centered, n is even, and V (G) can be partitioned into conjugate pairs. Proposition 7 [5] In any vertex-radius-decreasing graph containing at least one cut-vertex, every ncv has degree 1. Proposition 8 Let G be a bipartite graph and let v be a vertex in a partite set V i, i = 1,. Then deg G (v) V 3 i rad(g) +. Proof Let T v be a distance-preserving spanning tree of G with v as its root; so deg Tv (v) = deg G (v). Let P be a diametral path of T v. Then P has length diam(t v ) rad(t v ) 1 rad(g) 1. So P contains at least rad(g) vertices, with at least rad(g) of them in V 3 i. Moreover, at most two of them can be neighbours of v on P. So there are at least deg G (v) neighbours of v which are not on P. So and Proposition 8 follows. 3 The Main Result V 3 i rad(g) + deg G (v), In this section we obtain a bound on the size of a bipartite graph of order n and radius r. The following lemma deals with the case r = 4 of our main theorem. Lemma Let G be a bipartite graph of order n 8 and radius 4. Then n m(g) n + 8, 4 Moreover, if m(g) = n 4 n + 8, then G B(n, 4). Proof Since rad(g) = 4, there exists a vertex x V (G) such that e G (x) = 4. Moreover, there is a vertex x 4 V (G) such that d(x, x 4 ) = 4, having xx 1 x x 3 x 4 as a shortest x x 4 path in G. For 1 i 4, let N i be the ith distance layer of x. So x i N i for 1 i 4. Since e G (x 1 ) 4, there is a vertex x 1 V (G) such that d(x 1, x 1 ) = 4. Thus x 1 N 3 and 9

10 x x 1 / E(G). But x 1 must have a neighbour in N, say x, where x x and x 1 x / E(G). Moreover, x must have a neighbour in N 1 that is not x 1, say x 1. Since e G (x ) 4, there is a vertex x V (G) such that d(x, x ) = 4, where x / {x, x 4 }. Suppose, without loss of generality, that x V 1. Then certainly {x, x 4 } and {x, x } are disjoint pairs of vertices in V 1 that are distance 4 apart. Since e G (x 1) 4, there is a vertex x 1 V such that d(x 1, x 1) = 4, where x 1 / {x 1, x 1 }. Then certainly {x 1, x 1 } and {x 1, x 1} are disjoint pairs of vertices in V that are distance 4 apart. So there exist four disjoint pairs of vertices, say u i and v i, such that d(u i, v i ) = 4 for 1 i 4, where u i, v i V 1 for i = 1, and u i, v i V for i = 3, 4. Denote by G, the bipartite complement of G; that is the graph with bipartition (V 1, V ) such that for u V 1, v V, uv E(G) if and only if uv / E(G). Let V 1 = V 1 {u 1, v 1, u, v } and V = V {u 3, v 3, u 4, v 4 }. We show that m(g) n 8. For each vertex w V, there exist edges e 1 (w) and e (w) joining w to a vertex in {u 1, v 1 } and {u, v }, respectively, in G since otherwise d G (u 1, v 1 ) =. Similarly, for each vertex w V 1, there exist edges e 3 (w) and e 4 (w) joining w to a vertex in {u 3, v 3 } and {u 4, v 4 }. Clearly, the subsets of E(G) are disjoint. Hence, A = {e 1 (w) w V } {e (w) w V }, B = {e 3 (w) w V 1} {e 4 (w) w V 1} m(g) A + B = V + ( V 1 4) = n 8. We have m(g)+m(g) n 4 since the maximum size of a complete bipartite graph is n 4. Hence m(g) n n m(g) n + 8, 4 4 as required. We now show that if m(g) = n 4 n + 8, then G B(n, 4). Suppose that m(g) = n 4 n + 8. Then, m(g) = n 8, and hence, m(g) = A + B = V + ( V 1 4). Hence, in G, every vertex in V is adjacent to exactly one vertex in {u 1, v 1 } and exactly one vertex in {u, v }, 10

11 and every vertex in V 1. Every vertex in V 1 is adjacent to exactly one vertex in {u 3, v 3 } and exactly one vertex in {u 4, v 4 }. Let x, y be an arbitrary adjacent pair of vertices in V 1 V. Then deg G (x)+deg G (y) = V 1 + V = n 4. Hence, by Lemma 1, the result follows. We now present our main theorem. Theorem For natural numbers n and r such that n r, the maximum number of edges in a bipartite graph of order n and radius at least r is b(n, r), where a) b(n, 1) = n 1, b) b(n, ) = n 4, c) b(n, 3) = n 4 n, d) b(n, r) = n 4 nr + r + (n r) for n r 8. The bipartite graph with radius 1 and the maximum number of edges is the star K 1,n 1. The bipartite graph with radius and the maximum number of edges is the complete bipartite graph K. The bipartite graph with n n, radius 3 and the maximum number of edges is obtained from the complete,, by the removal of a minimum edge cover. If G is a bipartite graph K n n graph with radius r 4 and the maximum number of edges, then G B(n, r). Proof a) The only bipartite graph with radius 1 and order n is the star K 1,n 1, which has n 1 edges. b) The bipartite graph with radius and the maximum number of edges is the complete bipartite graph K n, n which has n n = n 4 edges. c) Let G be a bipartite graph of order n, radius 3 and partite sets V 1 and V. Since rad(g) = 3, every vertex in V 1 must be non-adjacent to at least one vertex in V, and vice versa. Thus, m(g) n, and since the maximum size of a complete bipartite graph is n n, we have m(g) m(g), 4 4 and thus m(g) n n. Clearly, equality holds if G is obtained from 4 the complete graph K n, n, by the removal of a minimum edge cover. 11

12 d) Let G be a bipartite graph of order n, radius at least r 4 and maximum size with partite sets V 1 and V. By double induction, we prove that if G has order n and rad(g) r, then m(g) b(n, r) for n r 8, and m(g) = b(n, r) if and only if G B(n, r). We first show the inequality for the case n = r, i.e., we show that m(g) b(r, r) for r 4. Let G be a graph of radius r and order r. By Proposition 1, (G) n r + =. It follows that m(g) 1 n (G) n = r = b(r, r). Moreover, G must be a cycle of length r and thus G B(r, r). For the case r = 4, it has been shown in Lemma that, for n 8, m(g) b(n, 4) and if m(g) = b(n, 4), G B(n, 4). Now let n and r be natural numbers such that r 5 and n r + 1 and assume validity of the theorem for all bipartite graphs of order n and radius at least r, where either 4 r r 1 or else r = r and r n n 1. Let G be any bipartite graph of order n and radius at least r. Claim 1 If {x, x } is a conjugate pair of vertices in G, and the graph G {x, x } is disconnected, then m(g) b(n, r) and if m(g) = b(n, r), then G B(n, r). Let S = {x, x }. Let G 1, G,..., G k be the components of G S. Let G x = V (G 1 ) S G and G y = V (G )... V (G k ) S G. Note that G x and G y are connected for otherwise either x or x is not central. Suppose n(g x ) = t and thus n(g y ) = n t +. Moreover diam(g x ), diam(g y ) r and thus r + 1 t n r + 1. By m(g) = m(g x ) + m(g y ) and Proposition we have m(g) n nt + 5n t nr r + r t 4 = n nr + 4 r + n r + 1 (t r 1)(t n + r 1) b(n, r) since r + 1 t n r + 1 and therefore 1 (t r 1)(t n + r 1) 0. If m(g) = b(n, r), then equality holds throughout the above inequalities, and it follows that G x and G y are both graphs of diameter r and maximum size, given their orders. Moreover, t = r + 1 or t = n r + 1. Without loss of generality, say n(g x ) = n r + 1 and thus n(g y ) = r + 1. Since diam(g x ) = r, Proposition implies G x = G(n r + 1, r) = [r ]K1 + n r K 1 + n r K 1 + K 1. 1

13 So G x contains partite sets X and Y where X = n r + 1, and Y = n r + 1, where every vertex in X has degree n r = n r +, and every vertex in Y has degree n r +1+1 = n r +. So G contains adjacent vertices, x X and y Y, such that deg G (x)+deg G (y) = n r+4. It follows from Lemma 1 that G B(n, r). Claim If G contains a conjugate pair of vertices then m(g) b(n, r). If m(g) = b(n, r), then G B(n, r). Let {x, x } be a conjugate pair of vertices in G. By Claim 1, we may assume that G = G {x, x } is connected. Then by Proposition 3, rad(g ) r. By Lemma 1, we need only consider the case where deg G (x) + deg G (x ) < n r + 4. Moreover, by the induction hypothesis, we know that m(g ) b(n, r). Hence, m(g) m(g ) + deg G (x) + deg G (x ) b(n, r) + n r + 3 = ( ) n (n )r + r + (n r) + n r + 3 = n 4 nr + r + n r = b(n, r), as required. If m(g) = b(n, r), then we have equality throughout i.e., m(g ) = b(n, r) and deg G (x) + deg G (x ) = n r + 3. Without loss of generality, say deg G (x) deg G (x ). Then, deg G (x) n r +. By the induction hypothesis, G B(n, r) and so in G, V 1(G ) = n r+3 = n r + 1 and V (G ) = n r+3 = n r or V 1(G ) = n r, V (G ) = n r + 1. Since n(g ) r and n(g ) + = n, n r +. Thus deg G (x) n r + r + r + = 3. Note that x can be adjacent to at most vertices in V (G ) (V 1(G ) V (G )) as otherwise rad(g) < r. However, as rad(g) r, it then follows that x cannot be adjacent to a vertex in V 1(G ) V (G ) and to two vertices in V (G ) (V 1(G ) V (G )). So x is adjacent to at most one vertex in V (G ) (V 1(G ) V (G )), and thus x is adjacent to at least n r+ 1 = n r+1 vertices in V 1(G ) V (G ), i.e., x is adjacent to every vertex in V 1(G ) or x 13

14 is adjacent to every vertex in V (G ). Moreover, deg G (x) = n r +, and thus deg G (x ) = n r + 1. Since rad(g) 5, d G (x, x ) 5 and thus x cannot be adjacent to any vertex in V 1 V as otherwise rad(g) < r, and thus deg G (x ) =. Hence, n = r + since n r + 1 = and n r +. Moreover, n(g ) = r and so G = Cr. Hence, deg G (x) = r+ r + = 3, and thus x must be adjacent to three vertices on G = Cr, which is a contradiction as then rad(g) < r. Hence, equality cannot be attained in this case. Claim 3 If G is a vertex-radius-decreasing graph then m(g) b(n, r), and if m(g) = b(n, r) then G B(n, r). By Claim, we need only consider the case where G has no conjugate pairs. Then, by Proposition 6, G must contain at least one cut-vertex and by Proposition 7, any ncv of G must have degree 1. Hence, G contains two end vertices x 1 and x. Let G = G {x 1, x }, and note that if rad(g ) r, then any central vertex c of G is within distance r from every vertex in V (G) {x 1, x }, including the neighbours of x 1 and x. But then c is within distance r 1 from x 1 and x, contradicting rad(g) = r. Hence rad(g ) r 1. So, by the induction hypothesis, m(g ) b(n, r 1). Hence, m(g) = + m(g ) + b(n, r 1) = b(n, r), If m(g) = b(n, r), we have equality throughout. So m(g ) = b(n, r 1) and thus by our induction hypothesis, G B(n, r 1). If V 1(G) 3 or V (G), then G is not a vertex-radius-decreasing graph; thus V 1(G) = and V (G) = 1. Hence, n r + 3 = 3, and thus n = r which is a contradiction as n > r. Hence, equality cannot be attained in this case. Claim 4 If v is a ncv of G with rad(g v) r and deg G (v) n r +, then m(g) b(n, r). If m(g) = b(n, r), then G B(n, r). By the induction hypothesis, m(g v) b(n 1, r), and hence, m(g) = m(g v) + deg G (v) b(n 1, r) + n r + 14

15 = (n 1) (n 1)r + r + (n 1 r) + n r + 4 = n nr + r + n r 4 = b(n, r), as required. If m(g) = b(n, r), we have equality throughout; so m(g v) = b(n 1, r) and deg G (v) = n r +. By the induction hypothesis, G v B(n 1, r). If n(g v) = r, then G v is a cycle of length r, and moreover every vertex in G v has degree. Hence, any neighbour of v in G, say z, has degree 3 and thus G contains adjacent vertices v and z such that deg G (z) + deg G (x) = 5 = n r + 4. Hence G B(n, r) by Lemma 1. Since n(g v) r + 1 and n = n(g v) 1, n r +. Hence deg G (v) = n r + r+ r + 3. Note that v can be adjacent to at most one vertex in G {v} (V 1(G v) V (G v)) as otherwise rad(g) < r. Thus v is adjacent to at least n r + 1 = n r + 1 vertices in V 1(G v) V (G v). Let w V i (G v), i = 1, such that vw E(G), and let y V 3 i(g v) such that wy E(G v). Then and thus deg G v (w) + deg G v (y) = V 1(G v) + V (G v) + 1, deg G (w) +deg G (y) = V 1(G v) + V (G v) + = (n 1) r+3+ = n r+4, and hence G B(n, r) by Lemma 1. Claim 5 If w is a ncv of G with deg G (w) n r+ and rad(g w) r 1, then every neighbour of w is a ncv. By Proposition 4, w has a conjugate vertex w such that d G (w, w) = r and d G (w, u) r 1 for every u V (G) {w}. Let s and t be neighbours of w. It follows that if u is any vertex in V (G) {w, s}, then no shortest w u path can contain s. In particular, G s contains a w t path and hence a w w path. So G s is connected. Since s N G (w) was chosen arbitrarily, it follows that no neighbour of w is a cut-vertex. Claim 6 If v is a ncv of G with rad(g v) r and deg G (v) > n r +, then m(g) b(n, r). If m(g) = b(n, r), then G B(n, r). 15

16 We first show that v has a neighbour that is a ncv. Suppose to the contrary that every neighbour of v is a cut-vertex. Let T v be a distance-preserving spanning tree of G with v as its root; so deg Tv (v) = deg G (v). Let P be a diametral path of T v. Then P has length diam(t v ) rad(t v ) 1 rad(g) 1. So P contains at least rad(g) vertices. Moreover, the (deg G (v) ) neighbours of v not on P cannot be leaves because they are cut-vertices, and so they must be adjacent to a vertex that is non-adjacent to every other neighbour of v. Hence, since deg Tv (v) n r + 3, n r + (deg Tv (v) ) r + ( ) n r = n +, which is a contradiction. Thus, v must have a neighbour, say x, which is a ncv. If deg G (x) n r + 3, then deg G(v) + deg G (x) n r + 6, which is a contradiction by Lemma 1. Hence, deg G (x) n r +. Moreover, since x is a ncv, rad(g x) r 1 by Claim 4. By Proposition 4, x has a conjugate vertex, say x. If rad(g x) r 1, then {x, x} would form a conjugate pair and the result follows by Claim. So rad(g x) r and since d(x, v), deg G (x) n r + by Lemma 1. Hence, x must be a cut-vertex by Claim 4, and so G {x} has at least two components, say G 1 and G. Assume without loss of generality, that v, x V (G 1 ). Let x 1 be a neighbour of x of degree at least in V (G 1 ). Since d(v, x 1 ), deg G (x 1 ) n r + by Lemma 1. Suppose x 1 is a ncv. Then, by Claim 4, rad(g x 1 ) r 1. Applying Claim 5 to x 1 now yields that x is not a cut-vertex, which is a contradiction. Hence, x 1 is a cut-vertex. Let H be the component of G x 1 containing x and denote by N i the ith distance layer of x 1 in H. Since x 1 is a cut-vertex; it follows that every vertex in N 1 is an endvertex or a cut-vertex. By the same argument, if every vertex in N i, i 1, is an end-vertex or a cut-vertex, then so is every vertex in N i+1 (if any exists). Hence, by induction, each vertex in H is either an end-vertex or a cut-vertex. Consider a distance preserving spanning tree T of V (H) {x}. Then either T is a path or T contains at least two end-vertices distinct from x 1. 16

17 In the former case, let x be the end-vertex of T, x x 1, and y the neighbour of x, and in the latter case, let x and y be two end-vertices distinct from x. In both cases G =: G x y has n vertices, rad(g ) r 1 and m(g ) = m(g). Hence, by induction, m(g) = m(g ) + b(n, r 1) + = b(n, r). If m(g) = b(n, r), we have equality throughout; so m(g ) = b(n, r 1). By the induction hypothesis, G B(n, r 1). Hence G contains vertices w, v such that d G (w, v) and deg G (w)+deg G (v) = (n ) (r 1)+4 = n r + 4. By Lemma 1, G B(n, r). Claim 7 If v is a ncv of G with rad(g v) r, then m(g) b(n, r). If m(g) = b(n, r), then G B(n, r). This follows from Claims 4 and 6. References [1] P. Dankelmann, G. Dlamini and H.C. Swart, Upper bounds on distance measures in K,l -free graphs. (submitted) [] P. Dankelmann, G. Dlamini and H.C. Swart, Upper bounds on distance measures in K 3,3 -free graphs. Util. Math. 67 (005) [3] G. Dlamini, Aspects of Distances in Graphs, Ph.D. thesis, University of Natal, Durban, 003. [4] P. Erdös, J. Pach, R. Pollack and Z. Tuza, Radius, diameter and minimum degree. J. Combin. Theory B 47 (1989), [5] S. Fajtlowicz, A characterisation of radius critical graphs. J. Graph Theory 1 (1988), [6] F. Gliviak, On radially critical graphs. Recent Advances in Graph Theory (Proc. Sympos. Prague 1974), Academia Praha, Prague (1975), [7] F. Gliviak, M. Knor and L. Soltes, On radially maximal graphs. Australas. J. Combin. 9 (1994),

18 [8] F Harary and C. Thomassen, Anticritical graphs. Math. Proc. Cambridge Philos. Soc. 79 (1976), [9] S. Mukwembi, Bounds on Distances in Graphs. Ph.D. Thesis, University of KwaZulu-Natal, Durban, 006. [10] S. Mukwembi, The radius of a triangle-free graph with prescribed edgeconnnectivity, Util. Math. (to appear). [11] Y. Nishanov, On radially critical graphs with the maximum diameter (in Russian). Trudy Samarkand. Gos. Univ. 35 (197), [1] Y Nishanov, A lower bound on the number of edges in radially critical graphs (in Russian). Trudy Samarkand. Gos. Univ. 56 (1975), [13] V. Vizing, The number of edges in a graph of given radius. Soviet Math. Dokl. 8 (1967),

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

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

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

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

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

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

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

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

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

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

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

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

Cycles in a Graph Whose Lengths Differ by One or Two

Cycles in a Graph Whose Lengths Differ by One or Two Cycles in a Graph Whose Lengths Differ by One or Two J. A. Bondy 1 and A. Vince 2 1 LABORATOIRE DE MATHÉMATIQUES DISCRÉTES UNIVERSITÉ CLAUDE-BERNARD LYON 1 69622 VILLEURBANNE, FRANCE 2 DEPARTMENT OF MATHEMATICS

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

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

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

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

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

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

Lecture 4: BK inequality 27th August and 6th September, 2007

Lecture 4: BK inequality 27th August and 6th September, 2007 CSL866: Percolation and Random Graphs IIT Delhi Amitabha Bagchi Scribe: Arindam Pal Lecture 4: BK inequality 27th August and 6th September, 2007 4. Preliminaries The FKG inequality allows us to lower bound

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

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

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

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

Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis. Contents. Introduction. Maarten van Steen. Version: April 28, 2014

Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis. Contents. Introduction. Maarten van Steen. Version: April 28, 2014 Graph Theory and Complex Networks: An Introduction Maarten van Steen VU Amsterdam, Dept. Computer Science Room R.0, steen@cs.vu.nl Chapter 0: Version: April 8, 0 / Contents Chapter Description 0: Introduction

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

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

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

Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis

Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis Graph Theory and Complex Networks: An Introduction Maarten van Steen VU Amsterdam, Dept. Computer Science Room R4.0, steen@cs.vu.nl Chapter 06: Network analysis Version: April 8, 04 / 3 Contents Chapter

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

SEMITOTAL AND TOTAL BLOCK-CUTVERTEX GRAPH

SEMITOTAL AND TOTAL BLOCK-CUTVERTEX GRAPH CHAPTER 3 SEMITOTAL AND TOTAL BLOCK-CUTVERTEX GRAPH ABSTRACT This chapter begins with the notion of block distances in graphs. Using block distance we defined the central tendencies of a block, like B-radius

More information

A threshold for the Maker-Breaker clique game

A threshold for the Maker-Breaker clique game A threshold for the Maker-Breaker clique game Tobias Müller Miloš Stojaković October 7, 01 Abstract We study the Maker-Breaker k-clique game played on the edge set of the random graph G(n, p. In this game,

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

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

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

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

On Some Vertex Degree Based Graph Invariants

On Some Vertex Degree Based Graph Invariants MATCH Communications in Mathematical and in Computer Chemistry MATCH Commun. Math. Comput. Chem. 65 (20) 723-730 ISSN 0340-6253 On Some Vertex Degree Based Graph Invariants Batmend Horoldagva a and Ivan

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

Generalized Induced Factor Problems

Generalized Induced Factor Problems Egerváry Research Group on Combinatorial Optimization Technical reports TR-2002-07. Published by the Egrerváry Research Group, Pázmány P. sétány 1/C, H 1117, Budapest, Hungary. Web site: www.cs.elte.hu/egres.

More information

Degree-associated reconstruction parameters of complete multipartite graphs and their complements

Degree-associated reconstruction parameters of complete multipartite graphs and their complements Degree-associated reconstruction parameters of complete multipartite graphs and their complements Meijie Ma, Huangping Shi, Hannah Spinoza, Douglas B. West January 23, 2014 Abstract Avertex-deleted subgraphofagraphgisacard.

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

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

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

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

Combinatorial 5/6-approximation of Max Cut in graphs of maximum degree 3

Combinatorial 5/6-approximation of Max Cut in graphs of maximum degree 3 Combinatorial 5/6-approximation of Max Cut in graphs of maximum degree 3 Cristina Bazgan a and Zsolt Tuza b,c,d a LAMSADE, Université Paris-Dauphine, Place du Marechal de Lattre de Tassigny, F-75775 Paris

More information

An inequality for the group chromatic number of a graph

An inequality for the group chromatic number of a graph Discrete Mathematics 307 (2007) 3076 3080 www.elsevier.com/locate/disc Note An inequality for the group chromatic number of a graph Hong-Jian Lai a, Xiangwen Li b,,1, Gexin Yu c a Department of Mathematics,

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

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

The Goldberg Rao Algorithm for the Maximum Flow Problem

The Goldberg Rao Algorithm for the Maximum Flow Problem The Goldberg Rao Algorithm for the Maximum Flow Problem COS 528 class notes October 18, 2006 Scribe: Dávid Papp Main idea: use of the blocking flow paradigm to achieve essentially O(min{m 2/3, n 1/2 }

More information

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

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

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

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

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

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

Maximum Hitting Time for Random Walks on Graphs. Graham Brightwell, Cambridge University Peter Winkler*, Emory University

Maximum Hitting Time for Random Walks on Graphs. Graham Brightwell, Cambridge University Peter Winkler*, Emory University Maximum Hitting Time for Random Walks on Graphs Graham Brightwell, Cambridge University Peter Winkler*, Emory University Abstract. For x and y vertices of a connected graph G, let T G (x, y denote the

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

Balloons, Cut-Edges, Matchings, and Total Domination in Regular Graphs of Odd Degree

Balloons, Cut-Edges, Matchings, and Total Domination in Regular Graphs of Odd Degree Balloons, Cut-Edges, Matchings, and Total Domination in Regular Graphs of Odd Degree Suil O, Douglas B. West November 9, 2008; revised June 2, 2009 Abstract A balloon in a graph G is a maximal 2-edge-connected

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

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

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

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

Total colorings of planar graphs with small maximum degree

Total colorings of planar graphs with small maximum degree Total colorings of planar graphs with small maximum degree Bing Wang 1,, Jian-Liang Wu, Si-Feng Tian 1 Department of Mathematics, Zaozhuang University, Shandong, 77160, China School of Mathematics, Shandong

More information

8.1 Min Degree Spanning Tree

8.1 Min Degree Spanning Tree CS880: Approximations Algorithms Scribe: Siddharth Barman Lecturer: Shuchi Chawla Topic: Min Degree Spanning Tree Date: 02/15/07 In this lecture we give a local search based algorithm for the Min Degree

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

The Independence Number in Graphs of Maximum Degree Three

The Independence Number in Graphs of Maximum Degree Three The Independence Number in Graphs of Maximum Degree Three Jochen Harant 1 Michael A. Henning 2 Dieter Rautenbach 1 and Ingo Schiermeyer 3 1 Institut für Mathematik, TU Ilmenau, Postfach 100565, D-98684

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

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

Embedding nearly-spanning bounded degree trees

Embedding nearly-spanning bounded degree trees Embedding nearly-spanning bounded degree trees Noga Alon Michael Krivelevich Benny Sudakov Abstract We derive a sufficient condition for a sparse graph G on n vertices to contain a copy of a tree T of

More information

On Pebbling Graphs by their Blocks

On Pebbling Graphs by their Blocks On Pebbling Graphs by their Blocks Dawn Curtis, Taylor Hines, Glenn Hurlbert, Tatiana Moyer Department of Mathematics and Statistics Arizona State University, Tempe, AZ 85287-1804 November 19, 2008 dawn.curtis@asu.edu

More information

DEGREE-ASSOCIATED RECONSTRUCTION PARAMETERS OF COMPLETE MULTIPARTITE GRAPHS AND THEIR COMPLEMENTS

DEGREE-ASSOCIATED RECONSTRUCTION PARAMETERS OF COMPLETE MULTIPARTITE GRAPHS AND THEIR COMPLEMENTS TAIWANESE JOURNAL OF MATHEMATICS Vol. xx, No. xx, pp. 0-0, xx 20xx DOI: 10.11650/tjm.19.2015.4850 This paper is available online at http://journal.taiwanmathsoc.org.tw DEGREE-ASSOCIATED RECONSTRUCTION

More information

Approximated Distributed Minimum Vertex Cover Algorithms for Bounded Degree Graphs

Approximated Distributed Minimum Vertex Cover Algorithms for Bounded Degree Graphs Approximated Distributed Minimum Vertex Cover Algorithms for Bounded Degree Graphs Yong Zhang 1.2, Francis Y.L. Chin 2, and Hing-Fung Ting 2 1 College of Mathematics and Computer Science, Hebei University,

More information

Lecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs

Lecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs CSE599s: Extremal Combinatorics November 21, 2011 Lecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs Lecturer: Anup Rao 1 An Arithmetic Circuit Lower Bound An arithmetic circuit is just like

More information

Analysis of Algorithms, I

Analysis of Algorithms, I Analysis of Algorithms, I CSOR W4231.002 Eleni Drinea Computer Science Department Columbia University Thursday, February 26, 2015 Outline 1 Recap 2 Representing graphs 3 Breadth-first search (BFS) 4 Applications

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

Graph theoretic techniques in the analysis of uniquely localizable sensor networks

Graph theoretic techniques in the analysis of uniquely localizable sensor networks Graph theoretic techniques in the analysis of uniquely localizable sensor networks Bill Jackson 1 and Tibor Jordán 2 ABSTRACT In the network localization problem the goal is to determine the location of

More information

On-line Ramsey Theory for Bounded Degree Graphs

On-line Ramsey Theory for Bounded Degree Graphs On-line Ramsey Theory for Bounded Degree Graphs Jane Butterfield Tracy Grauman William B. Kinnersley Kevin G. Milans Christopher Stocker Douglas B. West University of Illinois Urbana IL, U.S.A. Submitted:

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

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

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

An example of a computable

An example of a computable An example of a computable absolutely normal number Verónica Becher Santiago Figueira Abstract The first example of an absolutely normal number was given by Sierpinski in 96, twenty years before the concept

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

Discrete Mathematics & Mathematical Reasoning Chapter 10: Graphs

Discrete Mathematics & Mathematical Reasoning Chapter 10: Graphs Discrete Mathematics & Mathematical Reasoning Chapter 10: Graphs Kousha Etessami U. of Edinburgh, UK Kousha Etessami (U. of Edinburgh, UK) Discrete Mathematics (Chapter 6) 1 / 13 Overview Graphs and Graph

More information

A Study of Sufficient Conditions for Hamiltonian Cycles

A Study of Sufficient Conditions for Hamiltonian Cycles DeLeon 1 A Study of Sufficient Conditions for Hamiltonian Cycles Melissa DeLeon Department of Mathematics and Computer Science Seton Hall University South Orange, New Jersey 07079, U.S.A. ABSTRACT A graph

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

Tiers, Preference Similarity, and the Limits on Stable Partners

Tiers, Preference Similarity, and the Limits on Stable Partners Tiers, Preference Similarity, and the Limits on Stable Partners KANDORI, Michihiro, KOJIMA, Fuhito, and YASUDA, Yosuke February 7, 2010 Preliminary and incomplete. Do not circulate. Abstract We consider

More information

Determination of the normalization level of database schemas through equivalence classes of attributes

Determination of the normalization level of database schemas through equivalence classes of attributes Computer Science Journal of Moldova, vol.17, no.2(50), 2009 Determination of the normalization level of database schemas through equivalence classes of attributes Cotelea Vitalie Abstract In this paper,

More information

Mathematical Induction. Lecture 10-11

Mathematical Induction. Lecture 10-11 Mathematical Induction Lecture 10-11 Menu Mathematical Induction Strong Induction Recursive Definitions Structural Induction Climbing an Infinite Ladder Suppose we have an infinite ladder: 1. We can reach

More information

MA651 Topology. Lecture 6. Separation Axioms.

MA651 Topology. Lecture 6. Separation Axioms. MA651 Topology. Lecture 6. Separation Axioms. This text is based on the following books: Fundamental concepts of topology by Peter O Neil Elements of Mathematics: General Topology by Nicolas Bourbaki Counterexamples

More information

SCORE SETS IN ORIENTED GRAPHS

SCORE SETS IN ORIENTED GRAPHS Applicable Analysis and Discrete Mathematics, 2 (2008), 107 113. Available electronically at http://pefmath.etf.bg.ac.yu SCORE SETS IN ORIENTED GRAPHS S. Pirzada, T. A. Naikoo The score of a vertex v in

More information

Distributed Computing over Communication Networks: Maximal Independent Set

Distributed Computing over Communication Networks: Maximal Independent Set Distributed Computing over Communication Networks: Maximal Independent Set What is a MIS? MIS An independent set (IS) of an undirected graph is a subset U of nodes such that no two nodes in U are adjacent.

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

Lecture Notes on GRAPH THEORY Tero Harju

Lecture Notes on GRAPH THEORY Tero Harju Lecture Notes on GRAPH THEORY Tero Harju Department of Mathematics University of Turku FIN-20014 Turku, Finland e-mail: harju@utu.fi 1994 2011 Contents 1 Introduction..........................................................

More information

Course on Social Network Analysis Graphs and Networks

Course on Social Network Analysis Graphs and Networks Course on Social Network Analysis Graphs and Networks Vladimir Batagelj University of Ljubljana Slovenia V. Batagelj: Social Network Analysis / Graphs and Networks 1 Outline 1 Graph...............................

More information

Institut für Informatik Lehrstuhl Theoretische Informatik I / Komplexitätstheorie. An Iterative Compression Algorithm for Vertex Cover

Institut für Informatik Lehrstuhl Theoretische Informatik I / Komplexitätstheorie. An Iterative Compression Algorithm for Vertex Cover Friedrich-Schiller-Universität Jena Institut für Informatik Lehrstuhl Theoretische Informatik I / Komplexitätstheorie Studienarbeit An Iterative Compression Algorithm for Vertex Cover von Thomas Peiselt

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

INCIDENCE-BETWEENNESS GEOMETRY

INCIDENCE-BETWEENNESS GEOMETRY INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full

More information

SHORT CYCLE COVERS OF GRAPHS WITH MINIMUM DEGREE THREE

SHORT CYCLE COVERS OF GRAPHS WITH MINIMUM DEGREE THREE SHOT YLE OVES OF PHS WITH MINIMUM DEEE THEE TOMÁŠ KISE, DNIEL KÁL, END LIDIKÝ, PVEL NEJEDLÝ OET ŠÁML, ND bstract. The Shortest ycle over onjecture of lon and Tarsi asserts that the edges of every bridgeless

More information

each college c i C has a capacity q i - the maximum number of students it will admit

each college c i C has a capacity q i - the maximum number of students it will admit n colleges in a set C, m applicants in a set A, where m is much larger than n. each college c i C has a capacity q i - the maximum number of students it will admit each college c i has a strict order i

More information