Irregularity strength of regular graphs
|
|
- Linette Butler
- 5 years ago
- Views:
Transcription
1 Irregularity stregth of regular graphs Jakub Przyby lo AGH Uiversity of Sciece a Techology Al. Mickiewicza 30, Kraków, Pola przybylo@wms.mat.agh.eu.pl Submitte: Nov 1, 007; Accepte: Ju 9, 00; Publishe: Ju 13, 00 Mathematics Subject Classificatios: 05C7 Abstract Let G be a simple graph with o isolate eges a at most oe isolate vertex. For a positive iteger w, a w-weightig of G is a map f : E(G) {1,,..., w}. A irregularity stregth of G, s(g), is the smallest w such that there is a w-weightig of G for which e:u e f(e) e:v e f(e) for all pairs of ifferet vertices u, v V (G). A cojecture by Fauree a Lehel says that there is a costat c such that s(g) + c for each -regular graph G,. We show that s(g) < Cosequetly, we improve the results by Frieze, Goul, Karoński a Pfeer (i some cases by a log factor) i this area, as well as the recet result by Cuckler a Lazebik. Keywors: irregularity stregth, graph weightig, regular graph 1 Itrouctio All graphs we cosier are simple a fiite. A ege {u, v} will be eote by uv or vu for short at times. For a give graph G a its vertex v, N G (v) G (v), V (G), E(G) a δ(g) (or simply N(v), (v), V, E a δ) eote the set of eighbours a the egree of v i G, the set of vertices, the set of eges a the miimum egree of G, respectively. By G[D] we mea a iuce subgraph of G with the vertex set D V (G). A set V = {V 1, V,..., V k } of isjoit subsets of a set V is calle a partitio of V if the uio of all elemets of V is V a V i for every i. We shall eote as P k a path of legth k 1 a write P k = v 1 v... v k for short if v i v i+1 are its cosecutive eges, i = 1,,..., k 1. For a graph G a a fiite set S of itegers, a S-weightig of G is a assigmet f : E(G) S. If S = {1,,..., w}, the we call f a w-weightig of G. Moreover, f(e) is calle the weight of a ege e E(G), while the weight of v V (G) is efie as f(v) = u N(v) f(vu). A weightig f is irregular if the obtaie weights of all vertices are ifferet. The smallest positive iteger w for which there exists a irregular w-weightig the electroic joural of combiatorics 15 (00), #R 1
2 of G is calle the irregularity stregth of G a is eote by s(g). If it oes ot exist, we write s(g) =. It is easy to see that s(g) < iff G cotais o isolate eges a at most oe isolate vertex. The otio of the irregularity stregth was itrouce by Chartra at al. [3]. It was motivate by the well kow fact that a simple graph of orer at least must cotai a pair of vertices with the same egree. O the other ha, a multigraph ca be irregular, i.e. the egrees of its vertices ca all be istict. Now suppose we wat to multiply the eges of a graph G i orer to create a irregular multigraph of it. The s(g) is equal to the smallest maximum multiplicity of a ege i such a multigraph, see [7] for a survey by Lehel o this parameter. We will focus our attetio o the regular graphs, which (ot oly by the ame) seem to be the most ifficult to be mae irregular. A simple coutig argumet, see e.g. [3], shows that s(g) + 1 for all -regular graphs,, of orer. A questio whether maybe just a few more weights tha this lower bou woul always suffice was pose by Jacobso (see [7]) after obtaiig a umber of supportig argumets. This was formulate as a cojecture by Fauree a Lehel. Cojecture 1 ([5]) There exists a absolute costat c such that for each -regular graph G,, of orer. They also showe the followig. s(g) + c (1) Theorem ([5]) Let G be a -regular graph,, of orer. The s(g) + 9. () About 15 years later a sizeable step forwar i the survey o this problem was mae by Frieze, Goul, Karoński a Pfeer. Theorem 3 ([6]) Let G be a -regular graph of orer with o isolate vertices or eges. (a) If (/ l ) 1/4, the s(g) 10/ + 1, (b) If (/ l ) 1/ /, the s(g) 4/ + 1, (c) If 1/ + 1, the s(g) 40(log )/ + 1. Their result was recetly supplemete (a improve i some cases) by Cuckler a Lazebik. Theorem 4 ([4]) Let G be a -regular graph of orer with o isolate vertices or eges. If 10 4/3 /3 log 1/3, the s(g) 4/ + 6. Ufortuately, these results o ot cofirm eve a weaker form of Cojecture 1, amely that s(g) c 1 + c (3) the electroic joural of combiatorics 15 (00), #R
3 hols for all -regular graphs of orer, with c 1 a c beig absolute positive costats. I other wors, we o ot eve kow if s(g) is of orer suggeste i this cojecture (see Theorem 3 (c)). We will show it quite briefly i the ext sectio, see Corollary 10. The we will improve the obtaie costats c 1, c by a careful costructio a prove the followig mai result of the paper i the last sectio. Theorem The 5 Let G be a -regular graph of orer with o isolate vertices or eges. s(g) < The right orer of s(g) Let g be a w-weightig of a graph G a let us efie m g = max { X : g(u) = g(v) for all u, v X}. X V (G) The mai iea of the proof of Theorem 3 relie o two steps. First the authors fou a w-weightig g with small m g a small w, e.g. w =, usig probabilistic tools. The they moifie g to a irregular assigmet by meas of the followig etermiistic lemma. Lemma 6 ([6]) Let G be a -regular graph without isolate vertices or isolate eges, a let g be a w-weightig of G. The, there exists a irregular ((3w 1)m g + 1)-weightig of G. Our approach, which will be explaie i etails later, is i a way similar. A equivalet of the first step escribe will be Corollary 11, which we prove at the begiig of the thir sectio. It will be resposible for groupig the set of vertices ito fairly small subsets of elemets with the same weight. Our mai tool will be the followig theorem by Aario-Berry, Dalal a Ree. Theorem 7 ([1]) Give a graph G a for all v V (G), itegers a v, a + v such that a v (v) a + v < (v), a a + v mi ( (v) + a v + 1, a v + 3 ), (4) there exists a spaig subgraph H of G such that H (v) {a v, a v + 1, a + v, a + v + 1} for all v V (G). Corollary Let > 0 be a iteger. There exists a set S of 4 cosecutive itegers such that give ay -regular graph G a umbers a v S, a + v := a v for each v V (G), there exists a spaig subgraph H of G such that H (v) {a v, a v + 1, a + v, a+ v + 1} for all v V (G). the electroic joural of combiatorics 15 (00), #R 3
4 Proof. The theorem is obvious for 3, so let 4. Assume first that is ot ivisible by 4 a take S := { 4,..., 4 3}. Clearly S = 4 a for a v S, a + v := a v , we have a v 4 3, 4 1 a + v a a + v 3 4 <, hece, by Theorem 7, it is eough to prove (4) for all v V (G). Note the that a + v = a v a v + a v + 3 a a+ v = a v + a v a v a v + + 1, thus (4) hols. Aalogously, if is ivisible by 4, we ca take S := {,..., 1}. 4 Let G = (V, E) be a graph a let A, B be two oempty, oitersectig subsets of V. For a give weightig f of eges of G, let f (A, B) := mi{ f(v) f(w) : v A, w B} eote the istace betwee A a B with respect to f. Moreover, let f (A) := 0 if f is costat o A or f (A) := mi{ f(v) f(w) : v, w A, f(v) f(w)} otherwise. Corollary 9 For each -regular graph G a a partitio {A 1,..., A } of its vertices, there exists a -weightig f of G such that f (A i, A j ) 1 for i j. Proof. Let G = (V, E) be a -regular graph with > 0 a let {A 1,..., A } be ay partitio of V. Let S = {s 1,..., s } be a appropriate set from Corollary, where s 1,..., s 4 are 4 (hece s 1 a v 4 cosecutive itegers. Let a v := s i 1 for each v A i, i = 1,..., for all v V ). By Corollary, there exists a spaig subgraph s 4 H of G such that H (v) {s i 1, s i 1 + 1, s i , si } =: Si for every v A i, i = 1...,. Note that sice s < s , the Si S j = for i j. Therefore, if we set f(e) = for all the eges of the subgraph H a f(e) = 1 for all the other eges of G, the f(v) f(w) 1 wheever v A i, w A j a i j (because G is a regular graph). A almost immeiate cosequece of the above corollary is the followig oe, which cofirms that (3) hols. Corollary 10 Let G be a -regular graph of orer with o isolate vertices or eges. The s(g) < (5) Proof. Take ay partitio {A 1,..., A } of V (G) such that A i for all i (it exists sice ( ) ). The, by Corollary 9, there is a -weightig f of G such that m f max A i, 1 i hece, by Lemma 6, we have s(g) 5 ( ) + 1 < This corollary alreay improves i may cases the results by Frieze at al., as well as the oe by Cuckler a Lazebik, see Theorems 3 a 4. the electroic joural of combiatorics 15 (00), #R 4
5 3 Improvig the upper bou i (5) The rest of the paper is evote to stregtheig the iequality (5) above, i.e. replacig costats 40 a 11 by 16 a 6. Our approach cosists also of two steps, which very roughly look as follows. First we costruct a weightig f of a give graph G that partitio the vertex set ito small subsets of vertices with the same weights, but i such a way that there is quite a big ifferece betwee the weights of vertices from istict subsets. This will be provie by Corollary 11 below, which is a immeiate cosequece of Corollary 9. The we costruct a weightig g, which is resposible for scatterig the weights of the vertices from the subsequet subsets ot too far from their iitial weights, but i such a way that as a result they all have istict weights. This is oe i Lemma 15. The sum of this two weightigs will be the esire oe. Corollary 11 For each -regular graph G a a partitio {A 1,..., A } of its vertices, there exists a weightig f : E(G) { +1, 3 +} such that f (A i, A j ) +1 for i j a f (A i ) = 0 or f (A i ) + 1 for all i. Proof. Let G = (V, E) be a -regular graph with > 0 a let {A 1,..., A } be a partitio of V. By Corollary 9, there is a -weightig h of G such that h (A i, A j ) 1 for i j. The it is eough to set f(e) = + 1 if h(e) = 1 a f(e) = 3 + if h(e) =. Note that (3 + ) ( + 1) = + 1. Therefore f(u) f(v) = 0 or f(u) f(v) +1 for u, v V, sice G is a regular graph. Cosequetly, f (A i ) = 0 or f (A i ) + 1 for each i by the efiitio of f (A i ), a f (A i, A j ) + 1 for i j by Corollary 9. Let P3 o = v 1 vv o 3 eote a path P 3 = v 1 v v 3 after removig a mile vertex v from it, but without removig ay ege. I other wors, if P 3 = (V, E) is regare as a graph (V = {v 1, v, v 3 }, E = {v 1 v, v v 3 }), the P3 o is a orere pair (V {v }, E). We shall call P3 o a ope path of legth a v o will be referre to as a ope vertex i P3 o. The other vertices of P3 o, as well as all the vertices of simple paths, e.g. P, P 3, will be calle close. We shall also abuse a little bit the establishe otatio a call P3 o a graph (or a subgraph). Now, a {P, P 3, P3 o }-factor of a graph G is a collectio of vertex (a ege) isjoit subgraphs of G which are either paths of legths 1 or, or ope paths of legth (we call them the compoets of the factor), a that together spa G. (If two graphs share oly oe vertex which is ope i oe or both of them, they are vertex isjoit.) Spa here meas that each vertex of V (G) is a close vertex of exactly oe compoet of this factor. I this sese, e.g. each star (except K 1 ) has a {P, P 3, P3 o}-factor. Let F be a forest. Deote by c F the umber of compoets of F, by L(F ) the set of leaves of F a let R(F ) = V (F ) L(F ). I orer to costruct the weightig g metioe at the begiig of this sectio (a escribe i Lemma 15) we shall ee a {P, P 3, P3 o }-factor of a give graph G cosistig of ot too may P 3 s a sufficietly may P3 o s, see Lemma 14. To obtai it, we first prove the existece of a spaig forest F of G with relatively small value of R(F ), the electroic joural of combiatorics 15 (00), #R 5
6 see Lemma 13. For this aim we shall use the omiatio umber of G, γ(g), which is the size of the smallest omiatig set of G, i.e. the subset, say D, of V (G) such that each vertex i V (G) D has a eighbour i D. The followig probabilistic result ca be fou i Alo a Specer []. Theorem 1 ([]) Let G be a graph of orer a with δ(g). The γ(g) (1 + l(δ(g) + 1)). (6) δ(g) + 1 Lemma 13 Every graph G has a spaig forest F cosistig of trees of orer at least δ(g) + 1 such that R(F ) γ(g) c F. Proof. Let D V (G) be a omiatig set of G of size γ(g) a set N v = {v} N G (v) for v D. Defie a graph H such that V (H) = {N v : v D} a N v N u E(H) iff N v N u a v u (hece N v N u sice D is the smallest omiatig set of G). Let H 1,..., H m be the coecte compoets of H a let T 1,..., T m be their respective spaig trees. Let G i = G[ N v V (H i ) N v] a D i = {v : N v V (H i )} D, i = 1,..., m. Clearly, each G i is coecte, G i δ(g) + 1, D i is a omiatig set of G i a V (G 1 )... V (G m ) = V (G), D 1... D m = D. The esire forest will cosist of spaig trees of these vertex isjoit subgraphs G i of G which we costruct i the followig maer. Take e.g. G 1. Subsequetly, for each u, v D 1 such that N u N v E(T 1 ) choose a vertex w N u N v a a to the tree the eges uw (if possible, i.e. uless u = w or uw is alreay i the tree) a vw (if possible). The we have alreay costructe a subtree of G 1 with the vertex set D 1 such that D 1 D 1 a D 1 D 1 1. Sice D 1 is a omiatig set of G 1, we ca ow joi each vertex from V (G 1 ) D 1 with a vertex from D 1 by a ege a thus costruct a spaig tree F 1 of G 1 such that R(F 1 ) D 1 1. After repeatig this process for each G i we obtai a spaig forest F (cosistig of the trees F 1,..., F m ) of G with R(F ) γ(g) c F. Lemma 14 Let G be a graph of orer a with δ(g). The there is a {P, P 3, P3 o}- factor of G cosistig of at most P δ(g)+1 3 s a with less tha 4γ(G) vertices i P s a P 3 s. Proof. Let F be a spaig forest of G with compoets F 1,..., F cf such that R(F ) γ(g) c F a F i δ(g) + 1 3, i = 1,..., c F. We process the trees F 1,..., F cf oe after aother, so let T be a arbitrary oe of them. Let u be a vertex of egree oe i this tree, where N T (u) = {w}, a let us root this tree at u. Let L 0, L 1,..., L k be the sets of vertices o the cosecutive levels of this roote tree, i.e. L i cosists of the vertices at istace i from u. The L 0 = {u}, L 1 = {w} a L k L(T ). We say that a vertex u 1 V (T ) is below (above) a vertex u V (T ) i T if u 1 (u ) lies o the path joiig u (u 1 ) with u i T a u 1 u. We will cut out the elemets of the esire factor from this tree by the followig algorithm. Process the levels of the vertices oe after aother i the reverse orer, startig at the level L k 1. O a give level, process its vertices oe after aother i a arbitrary orer. Let T 0 := T a let T i eote the tree that remais of the electroic joural of combiatorics 15 (00), #R 6
7 T i 1 after processig the cosecutive vertex. At the momet we start processig a vertex, the oly vertices left above it i the tree are its eighbours. Assume ow that we have just create T j a v V (T ) is the ext vertex to be processe. Deote by X = {x 1,..., x p } the set of eighbours of v i T j that are above v (hece X cosists exclusively of leaves of T j ). The cut off X P o 3 s of the form x l v o x l+1 from T j (by removig the vertices x l, x l+1 a the eges x l v, x l+1 v from T j ) oe after aother a iclue them as the compoets of the factor that we wat to create. If there is still a vertex i X, say x p, cut off x p v (a remove the ege joiig v with its eighbour below) as oe P to the factor. The oly exceptio to that last rule occurs if v = w (a T is o), whe istea of aig x p w, we a P 3 = x p wu to the factor. Clearly, each P a P 3 of the create {P, P 3, P3 o }-factor of T must cotai at least oe vertex from R(T ). Sice there is at most oe P 3 i this factor, these P s a P 3 may cotai at most R(T ) + 1 vertices. By repeatig this process for all F i we create a {P, P 3, P3 o }-factor of G with at most ( R(F i ) + 1) = R(F ) + c F (γ(g) c F ) + c F < 4γ(G) 1 i c F vertices i P s a P 3 s, a cosistig of at most c F i = 1,..., c F, the c F. δ(g)+1 P 3 s. Sice F i δ(g) + 1 for Lemma 15 Let G be a -regular graph of orer, 5, a let L = {,..., }. The there is such a L-weightig g of G that the obtaie vertex weights are all i L (g(v ) L) a either of the vertex weights appears more tha times (mg ). Proof. Let G be a -regular graph of orer, 5, a let L + = {1,..., }, hece L + =. Note that 4. Let us fi a {P, P 3, P3 o }-factor of G which satisfies the thesis of Lemma 14. Let A, B, C be the sets of P s, P 3 s, P3 o s, respectively, from this factor. Deote a := A, b := B a c := C, hece a + 3b + c =. By Lemma 14, b a a + 3b 4γ(G). Therefore, by (6), +1 c γ(g) + l( + 1)) (1. (7) + 1 Note that f() := 1 + l( + 1) 1 4 0, () + 1 sice f is a icreasig fuctio for > 0 a f(5) > 0 (f(5) 0, 01). By (7), () a the fact that c is a iteger, we have c. (9) Set g(e) = 0 for each ege e of G outsie the factor. Now we will weight the eges of the graphs of the factor oe after aother. Each time we weight a ege, we establish the the electroic joural of combiatorics 15 (00), #R 7
8 fial weight of at least oe (close) vertex. To esure that, for each P3 o from C, its two eges must be weighte by a pair of weights (j, j) L L, so that the weight of the ope vertex remaie uchage. First we eal with the graphs from B. If b is o (i particular, if b = 1), weight the eges of the first P 3 by 1 a 1, hece establish the weights of its three (close) vertices as 1, 0 a 1. The, oe after aother, alterately assig the pair of weights ( + i, + i) a ( i, i), i = 0, 1,,..., to the pairs of eges of the cosecutive P 3 s from B. This way the vertices of the give P 3 will obtai weights + i, + i, 3 + i or i, i, 3 i. Note that for b we have cosequetly. Moreover, sice > > b 1, (10) + 1 b, the i 1. Therefore, the establishe so far weights of vertices are all ifferet. Deote the set of these weights by U. Note also that if u U the u U. Fially, by (10), for b, 3 + ( 1) 5( + 1) = < hece i all cases we get U L. Now we weight the eges of some part of the graphs from C. Subsequetly, for the elemets of C, set weights (i, i) to the pairs of their eges (establishig the weights of their close vertices as i a i) either for all i U L + if is eve or for i L + U if is o (by (9), there is eough elemets i C). This way, each vertex weight from the set L {0} ca still be use a eve umber of times (up to the total of ). Now we weight subsequetly all P s from A. First, alterately set 1 a 1 as the weights of the eges from A (each time establishig the weights of two vertices as 1 or 1) util there is at most vertices with establishe weight 1 (a at most vertices with weight 1). The, alterately set a as the ege weights of the elemets from A util there is at most vertices weighte with. Cotiue so (with 3, 4,...) util all the eges i A have bee weighte. At this poit a weight i is establishe for the same umber of vertices as i, for i L +, with oe possible exceptio - for o a, whe for oe j L + two more vertices carry the weight j tha j. Therefore, we may easily fiish the weightig of the elemets from C. Subsequetly, for the remaiig graphs i C, set weights (i, i), i L +, to the pairs of their eges as log as possible, i.e. as log as the umber of vertices with the establishe weight i is less tha for some i L + a as log as there are still some elemets of C left uweighte. At the e either all the eges are alreay weighte a the weightig obtaie complies with our requiremets or there are still some elemets of C left uweighte. I the seco case however, by our costructio, we must have alreay, the electroic joural of combiatorics 15 (00), #R
9 weighte at least vertices (this may occur oly if a is o). Therefore, at most oe P3 o from C remaie uweighte. The we may weight its eges with 0, establishig the weight of the two remaiig vertices as 0. This way, at most 3 vertices (together with at most oe from the first part of the proof cocerig B) have weight 0. Sice 3, the costructio is complete. Proof of Theorem 5. Let G be a -regular graph,, of orer (hece < ). Assume first that 5. The by Theorem, s(g) = = = ( 5) + 7( ) + < Let ow > 5. The, by Lemma 15, there is such a weightig g of G with umbers from the set L = {,..., } that the obtaie vertex weights are all i L a either of the vertex weights appears more tha times. Let A1,..., A be a partitio of V (G) such that g(u) g(v) if u, v A i a u v, i = 1,...,. Now, by Corollary 11, there is a weightig f : E(G) { + 1, 3 + } such that f (A i, A j ) + 1 for i j a f (A i ) = 0 or f (A i ) + 1 for all i. It is easy to see that a weightig f + g is irregular for G. Therefore, sice (f + g) : E(G) {1,..., 4 + }, we have s(g) 4 + < Ackowlegemets. I wish to express my thaks to Felix Lazebik for brigig the mai problem of this paper to my attetio urig a iterestig iscussio i Buapest, a to Igo Schiermeyer for his help a remarks i Freiberg. I also eclose greetigs for the aoymous referee for their valuable commets a suggestios. The author iforms that his research were supporte by MNiSzW grat o. N N Refereces [1] L. Aario-Berry, K. Dalal, B.A. Ree, Degree costraie subgraphs, Proceeigs of GRACO005, volume 19 of Electro. Notes Discrete Math., Amsteram (005) (electroic), Elsevier. [] N. Alo, J.H. Specer, The Probabilistic Metho, Joh Wiley a Sos, Ic., 199. [3] G. Chartra, M.S. Jacobso, J. Lehel, O.R. Oellerma, S. Ruiz, F. Saba, Irregular etworks. Proc. of the 50th Aiversary Cof. o Graph Theory, Fort Waye, Iiaa (196). [4] B. Cuckler, F. Lazebik, Irregularity Stregth of Dese Graphs, to appear i J. Graph Theory. the electroic joural of combiatorics 15 (00), #R 9
10 [5] R.J. Fauree, J. Lehel, Bou o the irregularity stregth of regular graphs, Colloq Math Soc Jańos Bolyai, 5, Combiatorics, Eger North Holla, Amsteram (197) [6] A. Frieze, R.J. Goul, M. Karoński, F. Pfeer, O Graph Irregularity Stregth, J. Graph Theory 41 (00) o [7] J. Lehel, Facts a quests o egree irregular assigmets, Graph Theory, Combiatorics a Applicatios, Willey, New York (1991) the electroic joural of combiatorics 15 (00), #R 10
On (K t e)-saturated Graphs
Noame mauscript No. (will be iserted by the editor O (K t e-saturated Graphs Jessica Fuller Roald J. Gould the date of receipt ad acceptace should be iserted later Abstract Give a graph H, we say a graph
More informationCombination Labelings Of Graphs
Applied Mathematics E-Notes, (0), - c ISSN 0-0 Available free at mirror sites of http://wwwmaththuedutw/ame/ Combiatio Labeligs Of Graphs Pak Chig Li y Received February 0 Abstract Suppose G = (V; E) is
More informationAsymptotics of Pattern Avoidance in the Klazar Set Partition and Permutation-Tuple Settings Permutation Patterns 2017 Abstract
Asymptotics of Patter Avoiace i the Klazar Set Partitio a Permutatio-Tuple Settigs Permutatio Patters 2017 Abstract Bejami Guby Departmet of Mathematics Harvar Uiversity Cambrige, Massachusetts, U.S.A.
More information1 Graph Sparsfication
CME 305: Discrete Mathematics ad Algorithms 1 Graph Sparsficatio I this sectio we discuss the approximatio of a graph G(V, E) by a sparse graph H(V, F ) o the same vertex set. I particular, we cosider
More informationLecture 2: Spectra of Graphs
Spectral Graph Theory ad Applicatios WS 20/202 Lecture 2: Spectra of Graphs Lecturer: Thomas Sauerwald & He Su Our goal is to use the properties of the adjacecy/laplacia matrix of graphs to first uderstad
More informationStrong Complementary Acyclic Domination of a Graph
Aals of Pure ad Applied Mathematics Vol 8, No, 04, 83-89 ISSN: 79-087X (P), 79-0888(olie) Published o 7 December 04 wwwresearchmathsciorg Aals of Strog Complemetary Acyclic Domiatio of a Graph NSaradha
More informationINTERSECTION CORDIAL LABELING OF GRAPHS
INTERSECTION CORDIAL LABELING OF GRAPHS G Meea, K Nagaraja Departmet of Mathematics, PSR Egieerig College, Sivakasi- 66 4, Virudhuagar(Dist) Tamil Nadu, INDIA meeag9@yahoocoi Departmet of Mathematics,
More informationPerhaps the method will give that for every e > U f() > p - 3/+e There is o o-trivial upper boud for f() ad ot eve f() < Z - e. seems to be kow, where
ON MAXIMUM CHORDAL SUBGRAPH * Paul Erdos Mathematical Istitute of the Hugaria Academy of Scieces ad Reu Laskar Clemso Uiversity 1. Let G() deote a udirected graph, with vertices ad V(G) deote the vertex
More informationn n B. How many subsets of C are there of cardinality n. We are selecting elements for such a
4. [10] Usig a combiatorial argumet, prove that for 1: = 0 = Let A ad B be disjoit sets of cardiality each ad C = A B. How may subsets of C are there of cardiality. We are selectig elemets for such a subset
More informationSome cycle and path related strongly -graphs
Some cycle ad path related strogly -graphs I. I. Jadav, G. V. Ghodasara Research Scholar, R. K. Uiversity, Rajkot, Idia. H. & H. B. Kotak Istitute of Sciece,Rajkot, Idia. jadaviram@gmail.com gaurag ejoy@yahoo.co.i
More informationMean cordiality of some snake graphs
Palestie Joural of Mathematics Vol. 4() (015), 49 445 Palestie Polytechic Uiversity-PPU 015 Mea cordiality of some sake graphs R. Poraj ad S. Sathish Narayaa Commuicated by Ayma Badawi MSC 010 Classificatios:
More informationNew Results on Energy of Graphs of Small Order
Global Joural of Pure ad Applied Mathematics. ISSN 0973-1768 Volume 13, Number 7 (2017), pp. 2837-2848 Research Idia Publicatios http://www.ripublicatio.com New Results o Eergy of Graphs of Small Order
More informationRandom Graphs and Complex Networks T
Radom Graphs ad Complex Networks T-79.7003 Charalampos E. Tsourakakis Aalto Uiversity Lecture 3 7 September 013 Aoucemet Homework 1 is out, due i two weeks from ow. Exercises: Probabilistic iequalities
More informationThe isoperimetric problem on the hypercube
The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose
More informationSymmetric Class 0 subgraphs of complete graphs
DIMACS Techical Report 0-0 November 0 Symmetric Class 0 subgraphs of complete graphs Vi de Silva Departmet of Mathematics Pomoa College Claremot, CA, USA Chaig Verbec, Jr. Becer Friedma Istitute Booth
More informationA RELATIONSHIP BETWEEN BOUNDS ON THE SUM OF SQUARES OF DEGREES OF A GRAPH
J. Appl. Math. & Computig Vol. 21(2006), No. 1-2, pp. 233-238 Website: http://jamc.et A RELATIONSHIP BETWEEN BOUNDS ON THE SUM OF SQUARES OF DEGREES OF A GRAPH YEON SOO YOON AND JU KYUNG KIM Abstract.
More informationOnes Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationSuper Vertex Magic and E-Super Vertex Magic. Total Labelling
Proceedigs of the Iteratioal Coferece o Applied Mathematics ad Theoretical Computer Sciece - 03 6 Super Vertex Magic ad E-Super Vertex Magic Total Labellig C.J. Deei ad D. Atoy Xavier Abstract--- For a
More informationPropagation time for probabilistic zero forcing
Propagatio time for probabilistic zero forcig Jesse Geeso Leslie Hogbe arxiv:181.1076v1 [math.co] Dec 018 December 1, 018 Abstract Zero forcig is a colorig game playe o a graph that was itrouce more tha
More informationProtected points in ordered trees
Applied Mathematics Letters 008 56 50 www.elsevier.com/locate/aml Protected poits i ordered trees Gi-Sag Cheo a, Louis W. Shapiro b, a Departmet of Mathematics, Sugkyukwa Uiversity, Suwo 440-746, Republic
More informationSome non-existence results on Leech trees
Some o-existece results o Leech trees László A.Székely Hua Wag Yog Zhag Uiversity of South Carolia This paper is dedicated to the memory of Domiique de Cae, who itroduced LAS to Leech trees.. Abstract
More information4-Prime cordiality of some cycle related graphs
Available at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 193-9466 Vol. 1, Issue 1 (Jue 017), pp. 30 40 Applicatios ad Applied Mathematics: A Iteratioal Joural (AAM) 4-Prime cordiality of some cycle related
More informationCompactness of Fuzzy Sets
Compactess of uzzy Sets Amai E. Kadhm Departmet of Egieerig Programs, Uiversity College of Madeat Al-Elem, Baghdad, Iraq. Abstract The objective of this paper is to study the compactess of fuzzy sets i
More informationMinimum Spanning Trees
Presetatio for use with the textbook, lgorithm esig ad pplicatios, by M. T. Goodrich ad R. Tamassia, Wiley, 0 Miimum Spaig Trees 0 Goodrich ad Tamassia Miimum Spaig Trees pplicatio: oectig a Network Suppose
More informationOn Infinite Groups that are Isomorphic to its Proper Infinite Subgroup. Jaymar Talledo Balihon. Abstract
O Ifiite Groups that are Isomorphic to its Proper Ifiite Subgroup Jaymar Talledo Baliho Abstract Two groups are isomorphic if there exists a isomorphism betwee them Lagrage Theorem states that the order
More information15-859E: Advanced Algorithms CMU, Spring 2015 Lecture #2: Randomized MST and MST Verification January 14, 2015
15-859E: Advaced Algorithms CMU, Sprig 2015 Lecture #2: Radomized MST ad MST Verificatio Jauary 14, 2015 Lecturer: Aupam Gupta Scribe: Yu Zhao 1 Prelimiaries I this lecture we are talkig about two cotets:
More informationMinimum Spanning Trees. Application: Connecting a Network
Miimum Spaig Tree // : Presetatio for use with the textbook, lgorithm esig ad pplicatios, by M. T. oodrich ad R. Tamassia, Wiley, Miimum Spaig Trees oodrich ad Tamassia Miimum Spaig Trees pplicatio: oectig
More information6.854J / J Advanced Algorithms Fall 2008
MIT OpeCourseWare http://ocw.mit.edu 6.854J / 18.415J Advaced Algorithms Fall 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 18.415/6.854 Advaced Algorithms
More informationA Note on Chromatic Transversal Weak Domination in Graphs
Iteratioal Joural of Mathematics Treds ad Techology Volume 17 Number 2 Ja 2015 A Note o Chromatic Trasversal Weak Domiatio i Graphs S Balamuruga 1, P Selvalakshmi 2 ad A Arivalaga 1 Assistat Professor,
More informationSome New Results on Prime Graphs
Ope Joural of Discrete Mathematics, 202, 2, 99-04 http://dxdoiorg/0426/ojdm202209 Published Olie July 202 (http://wwwscirporg/joural/ojdm) Some New Results o Prime Graphs Samir Vaidya, Udaya M Prajapati
More informationMAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS
Fura Uiversity Electroic Joural of Udergraduate Matheatics Volue 00, 1996 6-16 MAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS DAVID SITTON Abstract. How ay edges ca there be i a axiu atchig i a coplete
More informationAverage Connectivity and Average Edge-connectivity in Graphs
Average Coectivity ad Average Edge-coectivity i Graphs Jaehoo Kim, Suil O July 1, 01 Abstract Coectivity ad edge-coectivity of a graph measure the difficulty of breakig the graph apart, but they are very
More informationLecture 1: Introduction and Strassen s Algorithm
5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access
More informationCHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs
CHAPTER IV: GRAPH THEORY Sectio : Itroductio to Graphs Sice this class is called Number-Theoretic ad Discrete Structures, it would be a crime to oly focus o umber theory regardless how woderful those topics
More informationCharacterizing graphs of maximum principal ratio
Characterizig graphs of maximum pricipal ratio Michael Tait ad Josh Tobi November 9, 05 Abstract The pricipal ratio of a coected graph, deoted γg, is the ratio of the maximum ad miimum etries of its first
More informationCounting the Number of Minimum Roman Dominating Functions of a Graph
Coutig the Number of Miimum Roma Domiatig Fuctios of a Graph SHI ZHENG ad KOH KHEE MENG, Natioal Uiversity of Sigapore We provide two algorithms coutig the umber of miimum Roma domiatig fuctios of a graph
More informationON MATHIEU-BERG S INEQUALITY
ON MATHIEU-BERG S INEQUALITY BICHENG YANG DEPARTMENT OF MATHEMATICS, GUANGDONG EDUCATION COLLEGE, GUANGZHOU, GUANGDONG 533, PEOPLE S REPUBLIC OF CHINA. bcyag@pub.guagzhou.gd.c ABSTRACT. I this paper, by
More information1.2 Binomial Coefficients and Subsets
1.2. BINOMIAL COEFFICIENTS AND SUBSETS 13 1.2 Biomial Coefficiets ad Subsets 1.2-1 The loop below is part of a program to determie the umber of triagles formed by poits i the plae. for i =1 to for j =
More information2 X = 2 X. The number of all permutations of a set X with n elements is. n! = n (n 1) (n 2) nn e n
1 Discrete Mathematics revisited. Facts to remember Give set X, the umber of subsets of X is give by X = X. The umber of all permutatios of a set X with elemets is! = ( 1) ( )... 1 e π. The umber ( ) k
More informationGraphs. Minimum Spanning Trees. Slides by Rose Hoberman (CMU)
Graphs Miimum Spaig Trees Slides by Rose Hoberma (CMU) Problem: Layig Telephoe Wire Cetral office 2 Wirig: Naïve Approach Cetral office Expesive! 3 Wirig: Better Approach Cetral office Miimize the total
More informationThe Adjacency Matrix and The nth Eigenvalue
Spectral Graph Theory Lecture 3 The Adjacecy Matrix ad The th Eigevalue Daiel A. Spielma September 5, 2012 3.1 About these otes These otes are ot ecessarily a accurate represetatio of what happeed i class.
More informationOn Ryser s conjecture for t-intersecting and degree-bounded hypergraphs arxiv: v2 [math.co] 9 Dec 2017
O Ryser s cojecture for t-itersectig ad degree-bouded hypergraphs arxiv:1705.1004v [math.co] 9 Dec 017 Zoltá Király Departmet of Computer Sciece ad Egerváry Research Group (MTA-ELTE) Eötvös Uiversity Pázmáy
More information3. b. Present a combinatorial argument that for all positive integers n : : 2 n
. b. Preset a combiatorial argumet that for all positive itegers : : Cosider two distict sets A ad B each of size. Sice they are distict, the cardiality of A B is. The umber of ways of choosig a pair of
More informationTHE COMPETITION NUMBERS OF JOHNSON GRAPHS
Discussioes Mathematicae Graph Theory 30 (2010 ) 449 459 THE COMPETITION NUMBERS OF JOHNSON GRAPHS Suh-Ryug Kim, Boram Park Departmet of Mathematics Educatio Seoul Natioal Uiversity, Seoul 151 742, Korea
More informationSpanning Maximal Planar Subgraphs of Random Graphs
Spaig Maximal Plaar Subgraphs of Radom Graphs 6. Bollobiis* Departmet of Mathematics, Louisiaa State Uiversity, Bato Rouge, LA 70803 A. M. Frieze? Departmet of Mathematics, Caregie-Mello Uiversity, Pittsburgh,
More informationAlpha Individual Solutions MAΘ National Convention 2013
Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5
More informationc-dominating Sets for Families of Graphs
c-domiatig Sets for Families of Graphs Kelsie Syder Mathematics Uiversity of Mary Washigto April 6, 011 1 Abstract The topic of domiatio i graphs has a rich history, begiig with chess ethusiasts i the
More informationAustralian Journal of Basic and Applied Sciences, 5(11): , 2011 ISSN On tvs of Subdivision of Star S n
Australia Joural of Basic ad Applied Scieces 5(11): 16-156 011 ISSN 1991-8178 O tvs of Subdivisio of Star S 1 Muhaad Kara Siddiqui ad Deeba Afzal 1 Abdus Sala School of Matheatical Scieces G.C. Uiversity
More informationON A PROBLEM OF C. E. SHANNON IN GRAPH THEORY
ON A PROBLEM OF C. E. SHANNON IN GRAPH THEORY m. rosefeld1 1. Itroductio. We cosider i this paper oly fiite odirected graphs without multiple edges ad we assume that o each vertex of the graph there is
More informationLarge Feedback Arc Sets, High Minimum Degree Subgraphs, and Long Cycles in Eulerian Digraphs
Combiatorics, Probability ad Computig (013, 859 873. c Cambridge Uiversity Press 013 doi:10.1017/s0963548313000394 Large Feedback Arc Sets, High Miimum Degree Subgraphs, ad Log Cycles i Euleria Digraphs
More informationcondition w i B i S maximum u i
ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility
More informationTight Approximation Bounds for Vertex Cover on Dense k-partite Hypergraphs
Tight Approximatio Bouds for Vertex Cover o Dese -Partite Hypergraphs Mare Karpisi Richard Schmied Claus Viehma arxiv:07.2000v [cs.ds] Jul 20 Abstract We establish almost tight upper ad lower approximatio
More informationXiaozhou (Steve) Li, Atri Rudra, Ram Swaminathan. HP Laboratories HPL Keyword(s): graph coloring; hardness of approximation
Flexible Colorig Xiaozhou (Steve) Li, Atri Rudra, Ram Swamiatha HP Laboratories HPL-2010-177 Keyword(s): graph colorig; hardess of approximatio Abstract: Motivated b y reliability cosideratios i data deduplicatio
More informationAssignment 5; Due Friday, February 10
Assigmet 5; Due Friday, February 10 17.9b The set X is just two circles joied at a poit, ad the set X is a grid i the plae, without the iteriors of the small squares. The picture below shows that the iteriors
More informationThompson s Group F (p + 1) is not Minimally Almost Convex
Thompso s Group F (p + ) is ot Miimally Almost Covex Claire Wladis Thompso s Group F (p + ). A Descriptio of F (p + ) Thompso s group F (p + ) ca be defied as the group of piecewiseliear orietatio-preservig
More informationCS : Programming for Non-Majors, Summer 2007 Programming Project #3: Two Little Calculations Due by 12:00pm (noon) Wednesday June
CS 1313 010: Programmig for No-Majors, Summer 2007 Programmig Project #3: Two Little Calculatios Due by 12:00pm (oo) Wedesday Jue 27 2007 This third assigmet will give you experiece writig programs that
More informationALAN FRIEZE, CHARALAMPOS E. TSOURAKAKIS
RAINBOW CONNECTIVITY OF G,p) AT THE CONNECTIVITY THRESHOLD ALAN FRIEZE, CHARALAMPOS E. TSOURAKAKIS Abstract. A edge colored graph G is raibow edge coected if ay two vertices are coected by a path whose
More informationCIS 121 Data Structures and Algorithms with Java Fall Big-Oh Notation Tuesday, September 5 (Make-up Friday, September 8)
CIS 11 Data Structures ad Algorithms with Java Fall 017 Big-Oh Notatio Tuesday, September 5 (Make-up Friday, September 8) Learig Goals Review Big-Oh ad lear big/small omega/theta otatios Practice solvig
More informationMonochromatic Structures in Edge-coloured Graphs and Hypergraphs - A survey
Moochromatic Structures i Edge-coloured Graphs ad Hypergraphs - A survey Shiya Fujita 1, Hery Liu 2, ad Colto Magat 3 1 Iteratioal College of Arts ad Scieces Yokohama City Uiversity 22-2, Seto, Kaazawa-ku
More informationSubtrees of a random tree
Subtrees of a radom tree Bogumi l Kamiński Pawe l Pra lat November 21, 2018 Abstract Let T be a radom tree take uiformly at radom from the family of labelled trees o vertices. I this ote, we provide bouds
More informationThe size Ramsey number of a directed path
The size Ramsey umber of a directed path Ido Be-Eliezer Michael Krivelevich Bey Sudakov May 25, 2010 Abstract Give a graph H, the size Ramsey umber r e (H, q) is the miimal umber m for which there is a
More informationRelationship between augmented eccentric connectivity index and some other graph invariants
Iteratioal Joural of Advaced Mathematical Scieces, () (03) 6-3 Sciece Publishig Corporatio wwwsciecepubcocom/idexphp/ijams Relatioship betwee augmeted eccetric coectivity idex ad some other graph ivariats
More informationOctahedral Graph Scaling
Octahedral Graph Scalig Peter Russell Jauary 1, 2015 Abstract There is presetly o strog iterpretatio for the otio of -vertex graph scalig. This paper presets a ew defiitio for the term i the cotext of
More informationOur starting point is the following sketch of part of one of these polygons having n vertexes and side-length s-
PROPERTIES OF REGULAR POLYGONS The simplest D close figures which ca be costructe by the cocateatio of equal legth straight lies are the regular polygos icluig the equilateral triagle, the petago, a the
More informationLecture 5. Counting Sort / Radix Sort
Lecture 5. Coutig Sort / Radix Sort T. H. Corme, C. E. Leiserso ad R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukwa Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-2018
More informationMatrix Partitions of Split Graphs
Matrix Partitios of Split Graphs Tomás Feder, Pavol Hell, Ore Shklarsky Abstract arxiv:1306.1967v2 [cs.dm] 20 Ju 2013 Matrix partitio problems geeralize a umber of atural graph partitio problems, ad have
More informationLecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions
U.C. Berkeley CS170 : Algorithms Midterm 1 Solutios Lecturers: Sajam Garg ad Prasad Raghavedra Feb 1, 017 Midterm 1 Solutios 1. (4 poits) For the directed graph below, fid all the strogly coected compoets
More informationarxiv: v1 [math.co] 22 Dec 2015
The flag upper boud theorem for 3- ad 5-maifolds arxiv:1512.06958v1 [math.co] 22 Dec 2015 Hailu Zheg Departmet of Mathematics Uiversity of Washigto Seattle, WA 98195-4350, USA hailuz@math.washigto.edu
More informationImproved Random Graph Isomorphism
Improved Radom Graph Isomorphism Tomek Czajka Gopal Paduraga Abstract Caoical labelig of a graph cosists of assigig a uique label to each vertex such that the labels are ivariat uder isomorphism. Such
More information4-PRIME CORDIAL LABELING OF SOME DEGREE SPLITTING GRAPHS
Iteratioal Joural of Maagemet, IT & Egieerig Vol. 8 Issue 7, July 018, ISSN: 49-0558 Impact Factor: 7.119 Joural Homepage: Double-Blid Peer Reviewed Refereed Ope Access Iteratioal Joural - Icluded i the
More informationCS473-Algorithms I. Lecture 2. Asymptotic Notation. CS 473 Lecture 2 1
CS473-Algorithms I Lecture Asymptotic Notatio CS 473 Lecture 1 O-otatio (upper bouds) f() = O(g()) if positive costats c, 0 such that e.g., = O( 3 ) 0 f() cg(), 0 c 3 c c = 1 & 0 = or c = & 0 = 1 Asymptotic
More informationChapter 11. Friends, Overloaded Operators, and Arrays in Classes. Copyright 2014 Pearson Addison-Wesley. All rights reserved.
Chapter 11 Frieds, Overloaded Operators, ad Arrays i Classes Copyright 2014 Pearso Addiso-Wesley. All rights reserved. Overview 11.1 Fried Fuctios 11.2 Overloadig Operators 11.3 Arrays ad Classes 11.4
More informationPrime Cordial Labeling on Graphs
World Academy of Sciece, Egieerig ad Techology Iteratioal Joural of Mathematical ad Computatioal Scieces Vol:7, No:5, 013 Prime Cordial Labelig o Graphs S. Babitha ad J. Baskar Babujee, Iteratioal Sciece
More informationAn Efficient Algorithm for Graph Bisection of Triangularizations
A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045 Oe Brookigs Drive St. Louis, Missouri 63130-4899, USA jaegerg@cse.wustl.edu
More informationCMPT 125 Assignment 2 Solutions
CMPT 25 Assigmet 2 Solutios Questio (20 marks total) a) Let s cosider a iteger array of size 0. (0 marks, each part is 2 marks) it a[0]; I. How would you assig a poiter, called pa, to store the address
More informationarxiv: v2 [cs.ds] 24 Mar 2018
Similar Elemets ad Metric Labelig o Complete Graphs arxiv:1803.08037v [cs.ds] 4 Mar 018 Pedro F. Felzeszwalb Brow Uiversity Providece, RI, USA pff@brow.edu March 8, 018 We cosider a problem that ivolves
More informationGreedy Algorithms. Interval Scheduling. Greedy Algorithms. Interval scheduling. Greedy Algorithms. Interval Scheduling
Greedy Algorithms Greedy Algorithms Witer Paul Beame Hard to defie exactly but ca give geeral properties Solutio is built i small steps Decisios o how to build the solutio are made to maximize some criterio
More informationModule 8-7: Pascal s Triangle and the Binomial Theorem
Module 8-7: Pascal s Triagle ad the Biomial Theorem Gregory V. Bard April 5, 017 A Note about Notatio Just to recall, all of the followig mea the same thig: ( 7 7C 4 C4 7 7C4 5 4 ad they are (all proouced
More informationTHE DIAMETER GAME JÓZSEF BALOGH, RYAN MARTIN, AND ANDRÁS PLUHÁR
THE DIAMETER GAME JÓZSEF BALOGH, RYAN MARTIN, AND ANDRÁS PLUHÁR Abstract. A large class of the so-called Positioal Games are defied o the complete graph o vertices. The players, Maker ad Breaker, take
More informationBig-O Analysis. Asymptotics
Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses
More informationCSC 220: Computer Organization Unit 11 Basic Computer Organization and Design
College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:
More informationMinimum Spanning Trees
Miimum Spaig Trees Miimum Spaig Trees Spaig subgraph Subgraph of a graph G cotaiig all the vertices of G Spaig tree Spaig subgraph that is itself a (free) tree Miimum spaig tree (MST) Spaig tree of a weighted
More informationBig-O Analysis. Asymptotics
Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses
More informationPlanar graphs. Definition. A graph is planar if it can be drawn on the plane in such a way that no two edges cross each other.
Plaar graphs Defiitio. A graph is plaar if it ca be draw o the plae i such a way that o two edges cross each other. Example: Face 1 Face 2 Exercise: Which of the followig graphs are plaar? K, P, C, K,m,
More informationComputing Vertex PI, Omega and Sadhana Polynomials of F 12(2n+1) Fullerenes
Iraia Joural of Mathematical Chemistry, Vol. 1, No. 1, April 010, pp. 105 110 IJMC Computig Vertex PI, Omega ad Sadhaa Polyomials of F 1(+1) Fullerees MODJTABA GHORBANI Departmet of Mathematics, Faculty
More informationAdministrative UNSUPERVISED LEARNING. Unsupervised learning. Supervised learning 11/25/13. Final project. No office hours today
Admiistrative Fial project No office hours today UNSUPERVISED LEARNING David Kauchak CS 451 Fall 2013 Supervised learig Usupervised learig label label 1 label 3 model/ predictor label 4 label 5 Supervised
More informationAn Efficient Algorithm for Graph Bisection of Triangularizations
Applied Mathematical Scieces, Vol. 1, 2007, o. 25, 1203-1215 A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045, Oe
More informationChapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3
More informationStreaming, Network Flow
CS 38 Itrouctio to Algorithms Week 8 Recitatio Notes TA: Joey Hog jhhog@caltech.eu) 1 Streamig Algorithms We ca imagie a situatio i which a stream of ata is beig recieve but there is too much ata comig
More informationThe Magma Database file formats
The Magma Database file formats Adrew Gaylard, Bret Pikey, ad Mart-Mari Breedt Johaesburg, South Africa 15th May 2006 1 Summary Magma is a ope-source object database created by Chris Muller, of Kasas City,
More informationA study on Interior Domination in Graphs
IOSR Joural of Mathematics (IOSR-JM) e-issn: 2278-5728, p-issn: 219-765X. Volume 12, Issue 2 Ver. VI (Mar. - Apr. 2016), PP 55-59 www.iosrjourals.org A study o Iterior Domiatio i Graphs A. Ato Kisley 1,
More informationCSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)
CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a
More informationOn Alliance Partitions and Bisection Width for Planar Graphs
Joural of Graph Algorithms ad Applicatios http://jgaa.ifo/ vol. 17, o. 6, pp. 599 614 (013) DOI: 10.7155/jgaa.00307 O Alliace Partitios ad Bisectio Width for Plaar Graphs Marti Olse 1 Morte Revsbæk 1 AU
More informationSum-connectivity indices of trees and unicyclic graphs of fixed maximum degree
1 Sum-coectivity idices of trees ad uicyclic graphs of fixed maximum degree Zhibi Du a, Bo Zhou a *, Nead Triajstić b a Departmet of Mathematics, South Chia Normal Uiversity, uagzhou 510631, Chia email:
More informationThe digraph drop polynomial
The digraph drop polyomial Fa Chug Ro Graham Abstract For a weighted directed graph (or digraph, for short), deoted by D = (V, E, w), we defie a two-variable polyomial B D (x, y), called the drop polyomial
More informationΣ P(i) ( depth T (K i ) + 1),
EECS 3101 York Uiversity Istructor: Ady Mirzaia DYNAMIC PROGRAMMING: OPIMAL SAIC BINARY SEARCH REES his lecture ote describes a applicatio of the dyamic programmig paradigm o computig the optimal static
More informationConvergence results for conditional expectations
Beroulli 11(4), 2005, 737 745 Covergece results for coditioal expectatios IRENE CRIMALDI 1 ad LUCA PRATELLI 2 1 Departmet of Mathematics, Uiversity of Bologa, Piazza di Porta Sa Doato 5, 40126 Bologa,
More informationUniversity of Waterloo Department of Electrical and Computer Engineering ECE 250 Algorithms and Data Structures
Uiversity of Waterloo Departmet of Electrical ad Computer Egieerig ECE 250 Algorithms ad Data Structures Midterm Examiatio ( pages) Istructor: Douglas Harder February 7, 2004 7:30-9:00 Name (last, first)
More informationMINIMUM CROSSINGS IN JOIN OF GRAPHS WITH PATHS AND CYCLES
3 Acta Electrotechica et Iformatica, Vol. 1, No. 3, 01, 3 37, DOI: 10.478/v10198-01-008-0 MINIMUM CROSSINGS IN JOIN OF GRAPHS WITH PATHS AND CYCLES Mariá KLEŠČ, Matúš VALO Departmet of Mathematics ad Theoretical
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More information