RESEARCH SUMMARY BENJAMIN WALTER

Size: px
Start display at page:

Download "RESEARCH SUMMARY BENJAMIN WALTER"

Transcription

1 RESEARCH SUMMARY BENJAMIN WALTER 1. Introdution My generl re of reserh is lgeri topology. Brodly speking, this mens tht I m interested in onnetions etween strt lger nd topologil spes. Modern lgeri topology egins with the ttempt to lssify ll possile topologil spes y lgorithmilly onstruting ertin strt groups from eh topologil spe. Mnipultions of nd reltions etween spes trnslte into mnipultions of nd reltions etween strt groups. To pture different struturl spets, multiple onstrutions moving etween topologil spes nd strt lgeri ojets hve een identified. Questions out struture or existene of topologil spes re trnslted vi these methods to questions out struture or existene of lgeri ojets. We my lso run reverse onstrutions uilding topologil spes from strt lgeri ojets. This llows us to onvert lgeri questions into topologil questions, sometimes hnging omplited lgeri prolems into topologil ones whih re more trtle. Very si exmples of this re the proofs tht sugroups of free groups re free, s well s the fundmentl theorem of lger. My urrent reserh is divided into three projets. My primry projet is ontinuing joint work with Dev Sinh t the University of Oregon on Lie olgers nd relted strutures in lgeri topology. Relted to this work, my seond projet is ontinuing work giving new formultion of ooperds nd olgers in generl symmetri monoidl tegories with prtiulr pplitions in the tegories of ungrded ring modules nd topologil spes. My third projet is joint with Brin Munson t Wellesley College onstruting lulus of grph funtors whih we hope to use to stremline omputtions of hromti numers of grphs à l Bson nd Kozlov. More long-term, I m interested in investigting further new, deep onnetion etween topologil spes nd lgeri ojets vi spetr hinted t y reent work in Goodwillie s lulus of funtors nd topologil operds. The three projets ove eh feed into this long term gol in different mnner. Following is very rief overview of these projets, with in-depth disussions in lter setions Lie olgers nd relted strutures in lgeri topology. My joint work with Dev Sinh on Lie olgers nd pplitions in topology egn in lte Our foundtionl work fed mny ostles whih hve only reently een overome. Now tht the foundtions re omplete, rod vist of pplitions hs opened. In our first pper Lie olgers nd rtionl homotopy theory, I: grph olgers we define new tegory of olgers whih we ll grph olgers, we introdue new pproh to Lie olgers s quotients of grph olgers, nd we pply this to lssil rtionl homotopy theory. We show tht the Hrrison homology funtor from ommuttive lgers to Lie olgers nturlly ftors through our tegory of grph olgers, nd we use this ftoriztion to expliitly disply the dulity etween Hrrison homology nd homotopy vi piring of grphs nd trees. Our work leds to new view of rtionl homotopy theory s well s more omputtionlly-friendly frmework for Hrrison homology nd Lie olgers. In our seond pper Lie olgers nd rtionl homotopy theory, II: Hopf invrints we revisit the geometry ehind the Hrrison/homotopy piring of the first pper in order to give new, geometri 1

2 2 BENJAMIN WALTER nswer to the lssil question how n ohin dt determine homotopy groups? Expliitly we show tht grphs deorted y ohin elements give omplete set of homotopy funtionls omptile with Whitehed produts, nd we give simple, geometri method for mking lultions. Our work unifies nd generlizes onstrutions given y Bordmn-Steer, Sullivn, Hefliger, Hin nd Novikov, using our grph olgeri viewpoint to inorporte oth formlism nd geometry. Our work on grph olgers gives rdilly different nd highly omputle view of n extremely fundmentl ojet, Lie olgers. Initil work indites numer of fruitful pplitions nd extensions of our ides rnging from rtionl homotopy theory with infinite fundmentl group, to the word prolem in group theory, to generlized Hopf invrint one question Cooperds nd Colgers. Considering grph olgers nd the grph ooperd hs led me to work on the foundtions of ooperd theory. Operds re ojets whih enode lger strutures. For exmple there operds Lie, Com, As enoding Lie, ommuttive, nd ssoitive lger struture, s well s A nd E operds enoding homotopy ssoitive nd homotopy ommuttive lger struture. Reent work generlizes these notions to the topologil setting nd eyond. Dully, ooperds enode olger strutures. Tht is, operds tell how things re multiplied, ooperds tell how they re ftored. Operd theory is ided y the ft tht in ll tegories of interest, operdi omposition is ssoitive. However, the dul notion of ooperdi oomposition is ssoitive in lmost none of the stndrd tegories of interest. One striking effet of this is the diffiulty of desriing generl ofree olgers, question whih hs grnered interest in the theoretil omputer siene ommunity (see e.g. work of Berstel nd Reutenuer nd lso Blok nd Griffin). In my pper Cofree olgers over ooperds I ly foundtions for new pproh to ooperd theory using n ssoitive universl omposition produt whose left nd right Kn extensions give the operdi nd ooperdi omposition produts. This is used to give new onstrution of ofree olgers over ooperds improving the existing onstrutions of Smith, Fox, Hzewinkel, nd Blok-Griffin. Furthermore I give exmples showing tht my new foundtions give reltively esy wy to give expliit desriptions of ooperd strutures nd mps etween ooperds nd mke diret omputtions. In further work, I pln to extend these onstrutions to give new desription of the ofree ooperd funtor, vlid in the tegories of ungrded ring modules nd lso topologil spes. This would yield new onstrution of the ooperdi or onstrution whih preliminry lultions indite would extend tht of Mihel Ching in the topologil setting. There re numer of further projets, in my joint work with Sinh desried ove, nd lso investigting Goodwillie s homotopy lulus of funtors, where suh onstrution ould e useful Clulus of grph funtors. My disserttion work ws on Goodwillie s homotopy lulus of funtors. In my disserttion I onstruted new homotopy lulus of funtors in the rtionl homotopy tegories of differentil grded ommuttive olgers nd differentil grded Lie lgers. In similr, joint projet with Brin Munson t Wellesley College we re onstruting new lulus of grph funtors (funtors from the tegory of grphs to the tegory of topologil spes). Our gol is to use this lulus of grph funtors to stremline nd etter understnd the method of Lovász generlized y Bson nd Kozlov in 2007 for omputing ounds for hromti numers of grphs using lgeri topology. We hve urrently solved out hlf of the prolems required to omplete our lulus of grph funtors onstrution, nd expet to e le to omplete our work nd hve it redy for pulition within the next yer. We expet our work to e of gret interest oth to homotopy theorists wnting to etter understnd Weiss nd Goodwillie s luli of funtors nd to pplied mthemtiins nd omputer sientists interested in hromti numers of grphs. 2. Lie olgers nd relted strutures in lgeri topology 2.1. A rief introdution to Lie olgers nd generlized Hopf invrints.

3 RESEARCH SUMMARY 3 Definition 2.1. Let V e vetor spe. Define G(V ) to e the spn of the set of oriented yli grphs with verties leled y elements of V modulo multilinerity in the verties. G(V ) hs n nti-ommuttive oprodut given y ]G[ = e (Gê1 Gê2 Gê2 Gê1 ), where e rnges over the edges of G, nd Gê1 nd Gê2 re the onneted omponents of the grph otined y removing e, whih points to Gê2. For exmple, ] [ ( ) ( ) ( ) ( ) = +. We ll G(V ) the ofree grph olger on V. The numer of verties in grph is lled its weight. Grph olgers pir with non-ssoitive inry lgers vi the onfigurtion piring etween oriented yli grphs nd inry trees desried elow. Definition 2.2. Given G nd T, n oriented yli grph with verties V = {1,..., n} nd inry tree emedded in the upper hlf-plne with leves L = {1,..., n}, define β G,T : { edges of G } { internl verties of T } y sending n edge from vertex i to j in G to the vertex t the ndir of the shortest pth in T etween the leves i nd j. Use β G,T to define the onfigurtion piring of G nd T y sgn ( β G,T (e) ) if β is surjetive, G, T = e n edge of G 0 otherwise where sgn ( β G,T (e) ) = ±1 depending on whether the diretion of e grees with the ordering of the leves of T indued y its plnr emedding. Exmple 1. Following is the mp β G,T for two different inry trees T. 1 2 e 1 e 2 β(e 1) β(e 2) 1 2 e e 1 2 β(e1) β(e 2) In the first exmple, sgn ( β(e 1 ) ) = 1 nd sgn ( β(e 2 ) ) = 1. In the seond exmple, sgn ( β(e 1 ) ) = 1 nd sgn ( β(e 2 ) ) = 1. The onfigurtion piring is so nmed euse it nturlly rises in the ohomology-homology piring for onfigurtion spes. The grph oprodut nd inry lger produt re dul in the onfigurtion piring. Further, the kernel of the onfigurtion piring is preisely the Joi nd nti-symmetry suspe on the inry lger side, nd the Arnold nd rrow-reversing suspe on the grph olger side. Definition 2.3. Define E(V ) to e the quotient of G(V ) y Arn(V ), where Arn(V ) is the suspe generted y rrow-reversing nd Arnold omintions of grphs: (rrow-reversing) + (Arnold) + + Aove,, nd re verties of grph whih is fixed outside of the indited re. Theorem 2.4 (Sinh nd W ). If V is grded in positive degrees, then E(V ) is isomorphi to the ofree Lie olger on V, with the grph oprodut on G(V ) desending to the Lie orket on E(V ). Indeed, if V nd W re linerly dul, then the onfigurtion piring gives perfet piring etween E(V ) nd the free Lie lger on W with grph oprodut dul to Lie rket.

4 4 BENJAMIN WALTER Definition 2.5. Let (A, d A, µ A ) e one-onneted differentil grded lger. The grph olgeri r onstrution G(A) is the totl omplex of ( G(s -1 Ā), da, d µ ). Here s -1 Ā is the desuspension of the idel of positive-degree elements of A, d A is the extension of d A y Leiniz, nd d µ (g) is sum ontrting eh edge of g in turn, multiplying endpoints. If A is ommuttive, the Lie olgeri r onstrution E(A) is the quotient G(A) Arn(s -1 Ā). Theorem 2.6 (Sinh nd W ). E(A) is well defined nd gives model for the Hrrison omplex, or equivlently the André-Quillen homology of ommuttive lger. Thus, these onstrutions ftor through the tegory of grph olgers. The origin of these grph omplexes ws the study of generlized Hopf invrints. Let X e simpliil set, A(X) e the PL-forms on X, E(X) = E(A(X)), nd H n E (X) = H n(e(a(x))). Define G(X) nd H n G (X) similrly. Lemm 2.7. H n 1 E (S n ) is rnk one, generted y weight one oyle. Definition 2.8. Given oyle γ E n 1 S n we let τ(γ) γ e ny ohomologous oyle of weight one. Cll τ(γ) Hopf oyle ssoited to γ. Write E(S n ) for the mp from oyles in En 1 (S n ) to Q given y E(S n ) γ = S n τ(γ). Lemm 2.9. The mp E(S n ) is well defined nd indues the isomorphism Hn 1 E (S n ) = Q. Definition Given oyle γ E n 1 S n nd f : S n X, the Hopf invrint η γ (f) of f with respet to γ is E(S n ) f (γ). Just s E ftors through grph olgers, so too does E(S n ) ftor through (whih is defined G(S n ) in the sme wy s 2.8). In prtie we ompute Hopf invrints y piking grph representtives nd lulting ηγ G(f) = G(S n ) f γ. Exmple 2. Let ω e generting 2-oyle on S 2 nd f : S 3 S 2. The grph γ = ω ω is oyle in G(S 2 ) with f γ = hoie of oounding ohin. Then. Beuse is losed nd of degree two on S 3, it is ext. Let d 1 e d ( d 1 ) = + ( d 1 ). Thus f γ is homologous to d 1. The orresponding Hopf invrint is S 3 d 1, whih is the lssil formul for Hopf invrint given y Whitehed in The formule get more omplited in higher weights, ut they re still omputle nd hve the sme si ingredients pulling k ohins, tking d -1 nd produts. In prtiulr, if γ is defined using Thom forms of disjoint sumnifolds W i of mnifold X, then η γ (f) is generlized linking numer of the f 1 (W i ). Theorem 2.11 (Sinh nd W ). Let X e simply onneted. Then the mp H n E (X) Hom( π n+1 (X), Q ), whih sends γ to the Hopf invrint ssoited to γ, is n isomorphism of Lie olgers. Furthermore the mp ove is desended from olger mp H n G (X) Hom( π n+1 (X), Q ).

5 RESEARCH SUMMARY Future work. First, we pln to extend our pproh to rtionl homotopy theory eyond the simply onneted setting in hrteristi zero. In preliminry lultions, it seems tht our tehniques will pply eyond the nilpotent setting, possily even to infinite fundmentl groups (extending work of Gómez-Tto, Hlperin, nd Thoms). Further, pplying our tehniques to K(π, 1) s ould yield new insight into the lower entrl series nd new lgorithm to ttk the word prolem for residully nilpotent groups. Hopf invrints in this se n e understood s sort of generlized linking numer of elements. A seond re of inquiry is the deeper setting of hrteristi p. The min strting point for our Lie olgeri pproh to homotopy theory ws studying expliit Hopf invrints, nd relizing tht their vlues on Whitehed produts were governed y the sme piring s governs the homology nd ohomology of ordered onfigurtion spes, phenomenon explined y iterted loopspe theory. At p, loopspe theory leds to studying the piring etween the ohomology nd homology of symmetri groups. Another losely relted prolem is our generliztion of the Hopf invrint one question. Hopf invrints over the integers re defined for ny spe nd give full rnk sugroup of Hom ( π n (X), Z ). Clulting the okernel of the inlusion of this sugroup generlizes the lssil Hopf invrint one question nd ould help us onnet our pproh in hrteristi zero to topology in hrteristi p. 3. Cooperds nd olgers 3.1. Universl ompositions nd ofree olgers. Fix symmetri monoidl tegory (C, ), nd write Σ for the tegory whose ojets re surjetions S from finite set to singleton set nd whose morphisms re omptile set isomorphisms (note: this is equivlent to just the tegory of finite sets nd set isomorphisms, whih is equivlent to the symmetri groups viewed s tegory). Write Σ Σ for the tegory of whose ojets re set surjetions S 1 S 2 nd whose morphisms re omptile set isomorphisms. More generlly write the iterted wreth produt Σ Σ }{{} n for the tegory of surjetions S 1 S n nd omptile set isomorphisms. There re funtors Σ n Σ m given y omposing surjetions if n > m, nd inserting isomorphisms if m > n. These fit together to give n ugmented simpliil tegory with extr degeneries. Σ Σ Σ Σ Σ Σ Σ Σ Σ Σ The dotted, leftwrds rrows ove re setions of their neighoring solid rightwrds rrows. Write γ n for the omposition γ n : Σ Σ Σ. A symmetri sequene in C is funtor A : Σ C. Given two symmetri sequenes A, B : Σ C, we define their universl omposition produt A B : Σ Σ C y f g g ( (A B)(S 1 S2 ) = A(S2 ) B ( f 1 (s) f {s} ) ). s S 2 We define A B C : Σ Σ Σ C nd et. similrly. Note tht A B is not gin symmetri sequene. However we my onstrut symmetri sequene from A B y either left or right Kn extension over γ 2 : Σ Σ Σ. The left Kn extension Lkn γ2 A B is the usul operdi omposition produt from the literture. In this lnguge, n operd is symmetri sequene equipped with nturl trnsformtion µ : (A A) Aγ 2 suh tht the two indued nturl trnsformtions µ(µ Id), µ(id µ) : (A A A) Aγ 3 re equl. Dully, ooperd is symmetri sequene with nturl trnsformtion : Aγ 2 (A A) so tht the two indued nturl trnsformtions Aγ 3 (A A A) re equl. The universl omposition produt is ssoitive, ut its Kn extensions my not e. In most tegories of interest (e.g. ungrded ring modules nd topologil spes), ssoitivity is lost on right Kn extension; though not on left Kn extension. Write A B = Rkn γ2 (A B), A B C = Rkn γ3 (A B C), et.

6 6 BENJAMIN WALTER In generl A (B C) (A B) C. However there re prenthesiztion mps from eh of these to A B C. Muh of the diffiulty of olgers n e tred diretly to this point. Using this frmework I hve proven new method for uilding ofree olgers extending nd simplifying tht of Justin Smith. Theorem 3.1 (W ). Let C e ooperd nd V O(C). The ofree C-olger on V is given y the tegoril limit of the digrm C (C V ) C ( C (C V ) ) C V C C V C C C V 3.2. Future work. My desription of ooperds nd olgers vi universl omposition produts hs lredy proven useful in omputtions with the grph ooperd nd its reltionship with the Lie nd ssoitive ooperds. Coneptully, it hs proven onvenient to e le to work on the other side of Kn extension from the literture, nd nottionlly it is muh more len to work with universl omposition produts rther thn the ooperdi omposition produt. Further this work leds to ler understnding of Mihel Ching s onstrution of the topologil ooperdi or onstrution. In this vein, I pln to ontinue reorgniztion of ooperd theory round universl omposition produts. In prtiulr this leds to new wy of desriing the ofree ooperd funtor whih n e used for topologil operdi r onstrution. Applitions would inlude onstrutions useful for my joint work with Sinh on Lie olgers, understnding the topologil grph ooperd nd its liner nd Moore duls, s well s revisiting the work of Ching understnding Goodwillie s homotopy lulus of funtors. 4. Clulus of grph funtors 4.1. Chromti numers vi lgeri topology. By grph G we will men n undireted grph with no multiple edges or loops. A grph mp G H is mp of vertex sets whih preserves djeny. A grph hs n n-oloring if its verties n e olored with n olors suh tht no djent verties re olored the sme. Note tht n n-oloring of grph G is equivlent to grph mp G K n to the omplete grph on n verties. Write χ(g) for the miniml numer of olors required to olor G. In 1978 Lovász onstruted homology ostrutions to the existene of mps G K n, nd more reently his work ws generlized y Bson, Kozlov, nd others through the introdution of ifuntor Hom(, ) whih ssigns topologil spe to pir of grphs. Definition 4.1. Let H e grph. Define P(H), the power grph of H, to e the grph whose vertex set is P 0 (V (H)) with n edge etween S nd T if n only if there is n edge etween every element of S nd every element of T in H. Given grphs G nd H define the poset hom(g, H) to e the set of grph mps G P(H) with poset struture inherited from P(H). Write Hom(G, H) for the reliztion of the poset hom(g, H). Hom(, ) is ifuntor, ontrvrint in the first vrile nd ovrint in the seond. Bson nd Kozlov uild ostrutions to grph mps using funtorility of Hom(, ) s follows. A grph mp f : G K n indues mp of spes Hom(K 2, f) : Hom(K 2, G) Hom(K 2, K n ). Furthermore the ntipodl mp on K 2 gives free Z 2 -tion on the ove spes nd mkes Hom(K 2, f) Z 2 -equivrint mp. Considering Hom(K 2, f) s mp of Z 2 -undles, the generlized Borsuk-Ulm theorem tells us tht the imge of the first nonvnishing Stiefel-Whitney lss of Hom(K 2, G)/Z 2 must e nontrivil in Hom(K 2, K n )/Z 2. However y diret omputtion, Hom(K 2, K n ) is (n 3)-onneted. Theorem 4.2 (Lovász). For ny grph G, χ(g) onnetivity ( Hom(K 2, G) ) + 3.

7 RESEARCH SUMMARY 7 There is nothing prtiulrly importnt out the test grph K 2 used ove side from it hving free group tion. Bson nd Kozlov repled it y the yli grph C 2k+1 with the following result. Theorem 4.3 (Bson nd Kozlov). For ny grph G, χ(g) onnetivity ( Hom(C 2k+1, G) ) + 4. In prtie, the ove onstrutions seem to give firly shrp lower ound for hromti numers. The min ostle to quik hromti numer lultions ppers to e tht it is very omputtionlly intensive to extrt onnetivity informtion for generl grphs. The work required to ompute Hom(C 2k+1, K n ) ove is triumph of ferless omintoril mthemtis A lulus of grph funtors. Brin Munson nd I hve egun the onstrution of lulus of grph funtors pproximting ovrint funtors F : Grphs Top whih re ontinuous in the sense tht the evlution mp Hom(G, H) F(G) F(H) is ontinuous mp. The funtor Hom(K, ) is one suh. The onstrution of our lulus is inspired y Weiss orthogonl lulus of funtors from vetor spes to topologil spes whih re ontinuous in the sense tht mor(v, W) F(V) F(W) is ontinuous. Our work relies on the ft tht hom(, ) is essentilly n enrihment of the tegory of grphs over the tegory of posets. The end result of our work is, for every grph funtor F, n pproximting tower of firtions of grph funtors P 3 F P 2 F P 1 F where the fiers ll hve prtiulr simple form, nd going up the tower etter pproximtes good funtors F in the sense tht nturl trnsformtion F P n F eomes highly onneted. In this se, we should e le to red off onnetivity informtion for Hom(K, G) from the onnetivity of the fiers in the ottom of the pproximting tower of P n Hom(K, ) evluted t G. Working nlogous to Weiss, we hve ompleted roughly hlf of the onstrutions required to reh this gol. At present, we hve worked out the universl property whih should define the n-th polynomil pproximtion P n F (whih involves poset-enrihed homotopy olimit), we n show tht polynomil of degree n implies polynomil of degree n 1, nd we n show tht pproximting towers for funtors exist. We hve lso ompleted the initil onstrutions towrds understnding fiers of pproximting towers. Middle Est Tehnil University North Cyprus Cmpus E-mil ddress: enjmin@metu.edu.tr URL:

Pre-Lie algebras, rooted trees and related algebraic structures

Pre-Lie algebras, rooted trees and related algebraic structures Pre-Lie lgers, rooted trees nd relted lgeri strutures Mrh 23, 2004 Definition 1 A pre-lie lger is vetor spe W with mp : W W W suh tht (x y) z x (y z) = (x z) y x (z y). (1) Exmple 2 All ssoitive lgers

More information

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides.

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides. 1 PYTHAGORAS THEOREM 1 1 Pythgors Theorem In this setion we will present geometri proof of the fmous theorem of Pythgors. Given right ngled tringle, the squre of the hypotenuse is equl to the sum of the

More information

Project 6: Minigoals Towards Simplifying and Rewriting Expressions

Project 6: Minigoals Towards Simplifying and Rewriting Expressions MAT 51 Wldis Projet 6: Minigols Towrds Simplifying nd Rewriting Expressions The distriutive property nd like terms You hve proly lerned in previous lsses out dding like terms ut one prolem with the wy

More information

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic Chpter 3 Vetor Spes In Chpter 2, we sw tht the set of imges possessed numer of onvenient properties. It turns out tht ny set tht possesses similr onvenient properties n e nlyzed in similr wy. In liner

More information

Figure 1. The left-handed and right-handed trefoils

Figure 1. The left-handed and right-handed trefoils The Knot Group A knot is n emedding of the irle into R 3 (or S 3 ), k : S 1 R 3. We shll ssume our knots re tme, mening the emedding n e extended to solid torus, K : S 1 D 2 R 3. The imge is lled tuulr

More information

Linear Algebra Introduction

Linear Algebra Introduction Introdution Wht is Liner Alger out? Liner Alger is rnh of mthemtis whih emerged yers k nd ws one of the pioneer rnhes of mthemtis Though, initilly it strted with solving of the simple liner eqution x +

More information

DEFORMATIONS OF ASSOCIATIVE ALGEBRAS WITH INNER PRODUCTS

DEFORMATIONS OF ASSOCIATIVE ALGEBRAS WITH INNER PRODUCTS Homology, Homotopy nd Applitions, vol. 8(2), 2006, pp.115 131 DEFORMATIONS OF ASSOCIATIVE ALGEBRAS WITH INNER PRODUCTS JOHN TERILLA nd THOMAS TRADLER (ommunited y Jim Stsheff) Astrt We develop the deformtion

More information

6.5 Improper integrals

6.5 Improper integrals Eerpt from "Clulus" 3 AoPS In. www.rtofprolemsolving.om 6.5. IMPROPER INTEGRALS 6.5 Improper integrls As we ve seen, we use the definite integrl R f to ompute the re of the region under the grph of y =

More information

Coalgebra, Lecture 15: Equations for Deterministic Automata

Coalgebra, Lecture 15: Equations for Deterministic Automata Colger, Lecture 15: Equtions for Deterministic Automt Julin Slmnc (nd Jurrin Rot) Decemer 19, 2016 In this lecture, we will study the concept of equtions for deterministic utomt. The notes re self contined

More information

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs Isomorphism of Grphs Definition The simple grphs G 1 = (V 1, E 1 ) n G = (V, E ) re isomorphi if there is ijetion (n oneto-one n onto funtion) f from V 1 to V with the property tht n re jent in G 1 if

More information

Comparing the Pre-image and Image of a Dilation

Comparing the Pre-image and Image of a Dilation hpter Summry Key Terms Postultes nd Theorems similr tringles (.1) inluded ngle (.2) inluded side (.2) geometri men (.) indiret mesurement (.6) ngle-ngle Similrity Theorem (.2) Side-Side-Side Similrity

More information

Electromagnetism Notes, NYU Spring 2018

Electromagnetism Notes, NYU Spring 2018 Eletromgnetism Notes, NYU Spring 208 April 2, 208 Ation formultion of EM. Free field desription Let us first onsider the free EM field, i.e. in the bsene of ny hrges or urrents. To tret this s mehnil system

More information

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite!

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite! Solutions for HW9 Exerise 28. () Drw C 6, W 6 K 6, n K 5,3. C 6 : W 6 : K 6 : K 5,3 : () Whih of the following re iprtite? Justify your nswer. Biprtite: put the re verties in V 1 n the lk in V 2. Biprtite:

More information

A Study on the Properties of Rational Triangles

A Study on the Properties of Rational Triangles Interntionl Journl of Mthemtis Reserh. ISSN 0976-5840 Volume 6, Numer (04), pp. 8-9 Interntionl Reserh Pulition House http://www.irphouse.om Study on the Properties of Rtionl Tringles M. Q. lm, M.R. Hssn

More information

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix tries Definition of tri mtri is regulr rry of numers enlosed inside rkets SCHOOL OF ENGINEERING & UIL ENVIRONEN Emple he following re ll mtries: ), ) 9, themtis ), d) tries Definition of tri Size of tri

More information

Graph Theory. Simple Graph G = (V, E). V={a,b,c,d,e,f,g,h,k} E={(a,b),(a,g),( a,h),(a,k),(b,c),(b,k),...,(h,k)}

Graph Theory. Simple Graph G = (V, E). V={a,b,c,d,e,f,g,h,k} E={(a,b),(a,g),( a,h),(a,k),(b,c),(b,k),...,(h,k)} Grph Theory Simple Grph G = (V, E). V ={verties}, E={eges}. h k g f e V={,,,,e,f,g,h,k} E={(,),(,g),(,h),(,k),(,),(,k),...,(h,k)} E =16. 1 Grph or Multi-Grph We llow loops n multiple eges. G = (V, E.ψ)

More information

University of Sioux Falls. MAT204/205 Calculus I/II

University of Sioux Falls. MAT204/205 Calculus I/II University of Sioux Flls MAT204/205 Clulus I/II Conepts ddressed: Clulus Textook: Thoms Clulus, 11 th ed., Weir, Hss, Giordno 1. Use stndrd differentition nd integrtion tehniques. Differentition tehniques

More information

Part 4. Integration (with Proofs)

Part 4. Integration (with Proofs) Prt 4. Integrtion (with Proofs) 4.1 Definition Definition A prtition P of [, b] is finite set of points {x 0, x 1,..., x n } with = x 0 < x 1

More information

Section 4.4. Green s Theorem

Section 4.4. Green s Theorem The Clulus of Funtions of Severl Vriles Setion 4.4 Green s Theorem Green s theorem is n exmple from fmily of theorems whih onnet line integrls (nd their higher-dimensionl nlogues) with the definite integrls

More information

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6 CS311 Computtionl Strutures Regulr Lnguges nd Regulr Grmmrs Leture 6 1 Wht we know so fr: RLs re losed under produt, union nd * Every RL n e written s RE, nd every RE represents RL Every RL n e reognized

More information

Hyers-Ulam stability of Pielou logistic difference equation

Hyers-Ulam stability of Pielou logistic difference equation vilble online t wwwisr-publitionsom/jns J Nonliner Si ppl, 0 (207, 35 322 Reserh rtile Journl Homepge: wwwtjnsom - wwwisr-publitionsom/jns Hyers-Ulm stbility of Pielou logisti differene eqution Soon-Mo

More information

CIT 596 Theory of Computation 1. Graphs and Digraphs

CIT 596 Theory of Computation 1. Graphs and Digraphs CIT 596 Theory of Computtion 1 A grph G = (V (G), E(G)) onsists of two finite sets: V (G), the vertex set of the grph, often enote y just V, whih is nonempty set of elements lle verties, n E(G), the ege

More information

Discrete Structures Lecture 11

Discrete Structures Lecture 11 Introdution Good morning. In this setion we study funtions. A funtion is mpping from one set to nother set or, perhps, from one set to itself. We study the properties of funtions. A mpping my not e funtion.

More information

Lesson 2: The Pythagorean Theorem and Similar Triangles. A Brief Review of the Pythagorean Theorem.

Lesson 2: The Pythagorean Theorem and Similar Triangles. A Brief Review of the Pythagorean Theorem. 27 Lesson 2: The Pythgoren Theorem nd Similr Tringles A Brief Review of the Pythgoren Theorem. Rell tht n ngle whih mesures 90º is lled right ngle. If one of the ngles of tringle is right ngle, then we

More information

Introduction to Olympiad Inequalities

Introduction to Olympiad Inequalities Introdution to Olympid Inequlities Edutionl Studies Progrm HSSP Msshusetts Institute of Tehnology Snj Simonovikj Spring 207 Contents Wrm up nd Am-Gm inequlity 2. Elementry inequlities......................

More information

NON-DETERMINISTIC FSA

NON-DETERMINISTIC FSA Tw o types of non-determinism: NON-DETERMINISTIC FS () Multiple strt-sttes; strt-sttes S Q. The lnguge L(M) ={x:x tkes M from some strt-stte to some finl-stte nd ll of x is proessed}. The string x = is

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorithm Design nd Anlysis LECTURE 8 Mx. lteness ont d Optiml Ching Adm Smith 9/12/2008 A. Smith; sed on slides y E. Demine, C. Leiserson, S. Rskhodnikov, K. Wyne Sheduling to Minimizing Lteness Minimizing

More information

Math 32B Discussion Session Week 8 Notes February 28 and March 2, f(b) f(a) = f (t)dt (1)

Math 32B Discussion Session Week 8 Notes February 28 and March 2, f(b) f(a) = f (t)dt (1) Green s Theorem Mth 3B isussion Session Week 8 Notes Februry 8 nd Mrh, 7 Very shortly fter you lerned how to integrte single-vrible funtions, you lerned the Fundmentl Theorem of lulus the wy most integrtion

More information

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals AP Clulus BC Chpter 8: Integrtion Tehniques, L Hopitl s Rule nd Improper Integrls 8. Bsi Integrtion Rules In this setion we will review vrious integrtion strtegies. Strtegies: I. Seprte the integrnd into

More information

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS The University of ottinghm SCHOOL OF COMPUTR SCIC A LVL 2 MODUL, SPRIG SMSTR 2015 2016 MACHIS AD THIR LAGUAGS ASWRS Time llowed TWO hours Cndidtes my omplete the front over of their nswer ook nd sign their

More information

Bases for Vector Spaces

Bases for Vector Spaces Bses for Vector Spces 2-26-25 A set is independent if, roughly speking, there is no redundncy in the set: You cn t uild ny vector in the set s liner comintion of the others A set spns if you cn uild everything

More information

Section 1.3 Triangles

Section 1.3 Triangles Se 1.3 Tringles 21 Setion 1.3 Tringles LELING TRINGLE The line segments tht form tringle re lled the sides of the tringle. Eh pir of sides forms n ngle, lled n interior ngle, nd eh tringle hs three interior

More information

Behavior Composition in the Presence of Failure

Behavior Composition in the Presence of Failure Behvior Composition in the Presene of Filure Sestin Srdin RMIT University, Melourne, Austrli Fio Ptrizi & Giuseppe De Giomo Spienz Univ. Rom, Itly KR 08, Sept. 2008, Sydney Austrli Introdution There re

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorithm Design nd Anlysis LECTURE 5 Supplement Greedy Algorithms Cont d Minimizing lteness Ching (NOT overed in leture) Adm Smith 9/8/10 A. Smith; sed on slides y E. Demine, C. Leiserson, S. Rskhodnikov,

More information

ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS

ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS ILLUSTRATING THE EXTENSION OF A SPECIAL PROPERTY OF CUBIC POLYNOMIALS TO NTH DEGREE POLYNOMIALS Dvid Miller West Virgini University P.O. BOX 6310 30 Armstrong Hll Morgntown, WV 6506 millerd@mth.wvu.edu

More information

The Word Problem in Quandles

The Word Problem in Quandles The Word Prolem in Qundles Benjmin Fish Advisor: Ren Levitt April 5, 2013 1 1 Introdution A word over n lger A is finite sequene of elements of A, prentheses, nd opertions of A defined reursively: Given

More information

Lecture Notes No. 10

Lecture Notes No. 10 2.6 System Identifition, Estimtion, nd Lerning Leture otes o. Mrh 3, 26 6 Model Struture of Liner ime Invrint Systems 6. Model Struture In representing dynmil system, the first step is to find n pproprite

More information

PYTHAGORAS THEOREM WHAT S IN CHAPTER 1? IN THIS CHAPTER YOU WILL:

PYTHAGORAS THEOREM WHAT S IN CHAPTER 1? IN THIS CHAPTER YOU WILL: PYTHAGORAS THEOREM 1 WHAT S IN CHAPTER 1? 1 01 Squres, squre roots nd surds 1 02 Pythgors theorem 1 03 Finding the hypotenuse 1 04 Finding shorter side 1 05 Mixed prolems 1 06 Testing for right-ngled tringles

More information

Geometrically Realizing Nested Torus Links

Geometrically Realizing Nested Torus Links Geometrilly Relizing Nested Torus Links mie ry ugust 18, 2017 strt In this pper, we define nested torus links. We then go on to introdue ell deomposition of nested torus links. Using the ell deomposition

More information

ANALYSIS AND MODELLING OF RAINFALL EVENTS

ANALYSIS AND MODELLING OF RAINFALL EVENTS Proeedings of the 14 th Interntionl Conferene on Environmentl Siene nd Tehnology Athens, Greee, 3-5 Septemer 215 ANALYSIS AND MODELLING OF RAINFALL EVENTS IOANNIDIS K., KARAGRIGORIOU A. nd LEKKAS D.F.

More information

p-adic Egyptian Fractions

p-adic Egyptian Fractions p-adic Egyptin Frctions Contents 1 Introduction 1 2 Trditionl Egyptin Frctions nd Greedy Algorithm 2 3 Set-up 3 4 p-greedy Algorithm 5 5 p-egyptin Trditionl 10 6 Conclusion 1 Introduction An Egyptin frction

More information

Learning Objectives of Module 2 (Algebra and Calculus) Notes:

Learning Objectives of Module 2 (Algebra and Calculus) Notes: 67 Lerning Ojetives of Module (Alger nd Clulus) Notes:. Lerning units re grouped under three res ( Foundtion Knowledge, Alger nd Clulus ) nd Further Lerning Unit.. Relted lerning ojetives re grouped under

More information

SECTION A STUDENT MATERIAL. Part 1. What and Why.?

SECTION A STUDENT MATERIAL. Part 1. What and Why.? SECTION A STUDENT MATERIAL Prt Wht nd Wh.? Student Mteril Prt Prolem n > 0 n > 0 Is the onverse true? Prolem If n is even then n is even. If n is even then n is even. Wht nd Wh? Eploring Pure Mths Are

More information

Graph States EPIT Mehdi Mhalla (Calgary, Canada) Simon Perdrix (Grenoble, France)

Graph States EPIT Mehdi Mhalla (Calgary, Canada) Simon Perdrix (Grenoble, France) Grph Sttes EPIT 2005 Mehdi Mhll (Clgry, Cnd) Simon Perdrix (Grenole, Frne) simon.perdrix@img.fr Grph Stte: Introdution A grph-sed representtion of the entnglement of some (lrge) quntum stte. Verties: quits

More information

Exercise sheet 6: Solutions

Exercise sheet 6: Solutions Eerise sheet 6: Solutions Cvet emptor: These re merel etended hints, rther thn omplete solutions. 1. If grph G hs hromti numer k > 1, prove tht its verte set n e prtitioned into two nonempt sets V 1 nd

More information

Discrete Structures, Test 2 Monday, March 28, 2016 SOLUTIONS, VERSION α

Discrete Structures, Test 2 Monday, March 28, 2016 SOLUTIONS, VERSION α Disrete Strutures, Test 2 Mondy, Mrh 28, 2016 SOLUTIONS, VERSION α α 1. (18 pts) Short nswer. Put your nswer in the ox. No prtil redit. () Consider the reltion R on {,,, d with mtrix digrph of R.. Drw

More information

arxiv: v1 [math.co] 6 Jan 2019

arxiv: v1 [math.co] 6 Jan 2019 HOMOTOPY IN THE CATEGORY OF GRAPHS T. CHIH AND L. SCULL rxiv:1901.01619v1 [mth.co] 6 Jn 2019 Astrt. We develop theory of homotopy for grphs whih is internl to the tegory of grphs. Previous uthors hve ssoited

More information

MAT 403 NOTES 4. f + f =

MAT 403 NOTES 4. f + f = MAT 403 NOTES 4 1. Fundmentl Theorem o Clulus We will proo more generl version o the FTC thn the textook. But just like the textook, we strt with the ollowing proposition. Let R[, ] e the set o Riemnn

More information

Factorising FACTORISING.

Factorising FACTORISING. Ftorising FACTORISING www.mthletis.om.u Ftorising FACTORISING Ftorising is the opposite of expning. It is the proess of putting expressions into rkets rther thn expning them out. In this setion you will

More information

Review of Gaussian Quadrature method

Review of Gaussian Quadrature method Review of Gussin Qudrture method Nsser M. Asi Spring 006 compiled on Sundy Decemer 1, 017 t 09:1 PM 1 The prolem To find numericl vlue for the integrl of rel vlued function of rel vrile over specific rnge

More information

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e Green s Theorem. Let be the boundry of the unit squre, y, oriented ounterlokwise, nd let F be the vetor field F, y e y +, 2 y. Find F d r. Solution. Let s write P, y e y + nd Q, y 2 y, so tht F P, Q. Let

More information

Lecture 6: Coding theory

Lecture 6: Coding theory Leture 6: Coing theory Biology 429 Crl Bergstrom Ferury 4, 2008 Soures: This leture loosely follows Cover n Thoms Chpter 5 n Yeung Chpter 3. As usul, some of the text n equtions re tken iretly from those

More information

Chapter 4 State-Space Planning

Chapter 4 State-Space Planning Leture slides for Automted Plnning: Theory nd Prtie Chpter 4 Stte-Spe Plnning Dn S. Nu CMSC 722, AI Plnning University of Mrylnd, Spring 2008 1 Motivtion Nerly ll plnning proedures re serh proedures Different

More information

1.3 SCALARS AND VECTORS

1.3 SCALARS AND VECTORS Bridge Course Phy I PUC 24 1.3 SCLRS ND VECTORS Introdution: Physis is the study of nturl phenomen. The study of ny nturl phenomenon involves mesurements. For exmple, the distne etween the plnet erth nd

More information

Logic Synthesis and Verification

Logic Synthesis and Verification Logi Synthesis nd Verifition SOPs nd Inompletely Speified Funtions Jie-Hong Rolnd Jing 江介宏 Deprtment of Eletril Engineering Ntionl Tiwn University Fll 2010 Reding: Logi Synthesis in Nutshell Setion 2 most

More information

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx Applitions of Integrtion Are of Region Between Two Curves Ojetive: Fin the re of region etween two urves using integrtion. Fin the re of region etween interseting urves using integrtion. Desrie integrtion

More information

Linear choosability of graphs

Linear choosability of graphs Liner hoosility of grphs Louis Esperet, Mikel Montssier, André Rspud To ite this version: Louis Esperet, Mikel Montssier, André Rspud. Liner hoosility of grphs. Stefn Felsner. 2005 Europen Conferene on

More information

Symmetrical Components 1

Symmetrical Components 1 Symmetril Components. Introdution These notes should e red together with Setion. of your text. When performing stedy-stte nlysis of high voltge trnsmission systems, we mke use of the per-phse equivlent

More information

Engr354: Digital Logic Circuits

Engr354: Digital Logic Circuits Engr354: Digitl Logi Ciruits Chpter 4: Logi Optimiztion Curtis Nelson Logi Optimiztion In hpter 4 you will lern out: Synthesis of logi funtions; Anlysis of logi iruits; Tehniques for deriving minimum-ost

More information

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then.

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then. pril 8, 2017 Mth 9 Geometry Solving vetor prolems Prolem Prove tht if vetors nd stisfy, then Solution 1 onsider the vetor ddition prllelogrm shown in the Figure Sine its digonls hve equl length,, the prllelogrm

More information

CS 491G Combinatorial Optimization Lecture Notes

CS 491G Combinatorial Optimization Lecture Notes CS 491G Comintoril Optimiztion Leture Notes Dvi Owen July 30, August 1 1 Mthings Figure 1: two possile mthings in simple grph. Definition 1 Given grph G = V, E, mthing is olletion of eges M suh tht e i,

More information

Algebra 2 Semester 1 Practice Final

Algebra 2 Semester 1 Practice Final Alger 2 Semester Prtie Finl Multiple Choie Ientify the hoie tht est ompletes the sttement or nswers the question. To whih set of numers oes the numer elong?. 2 5 integers rtionl numers irrtionl numers

More information

Technische Universität München Winter term 2009/10 I7 Prof. J. Esparza / J. Křetínský / M. Luttenberger 11. Februar Solution

Technische Universität München Winter term 2009/10 I7 Prof. J. Esparza / J. Křetínský / M. Luttenberger 11. Februar Solution Tehnishe Universität Münhen Winter term 29/ I7 Prof. J. Esprz / J. Křetínský / M. Luttenerger. Ferur 2 Solution Automt nd Forml Lnguges Homework 2 Due 5..29. Exerise 2. Let A e the following finite utomton:

More information

Algebra in a Category

Algebra in a Category Algebr in Ctegory Dniel Muret Otober 5, 2006 In the topos Sets we build lgebri strutures out o sets nd opertions (morphisms between sets) where the opertions re required to stisy vrious xioms. One we hve

More information

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions MEP: Demonstrtion Projet UNIT 4: Trigonometry UNIT 4 Trigonometry tivities tivities 4. Pythgors' Theorem 4.2 Spirls 4.3 linometers 4.4 Rdr 4.5 Posting Prels 4.6 Interloking Pipes 4.7 Sine Rule Notes nd

More information

Hybrid Systems Modeling, Analysis and Control

Hybrid Systems Modeling, Analysis and Control Hyrid Systems Modeling, Anlysis nd Control Rdu Grosu Vienn University of Tehnology Leture 5 Finite Automt s Liner Systems Oservility, Rehility nd More Miniml DFA re Not Miniml NFA (Arnold, Diky nd Nivt

More information

A Lower Bound for the Length of a Partial Transversal in a Latin Square, Revised Version

A Lower Bound for the Length of a Partial Transversal in a Latin Square, Revised Version A Lower Bound for the Length of Prtil Trnsversl in Ltin Squre, Revised Version Pooy Htmi nd Peter W. Shor Deprtment of Mthemtil Sienes, Shrif University of Tehnology, P.O.Bo 11365-9415, Tehrn, Irn Deprtment

More information

Algebra Basics. Algebra Basics. Curriculum Ready ACMNA: 133, 175, 176, 177, 179.

Algebra Basics. Algebra Basics. Curriculum Ready ACMNA: 133, 175, 176, 177, 179. Curriulum Redy ACMNA: 33 75 76 77 79 www.mthletis.om Fill in the spes with nything you lredy know out Alger Creer Opportunities: Arhitets eletriins plumers et. use it to do importnt lultions. Give this

More information

Lecture 2: Cayley Graphs

Lecture 2: Cayley Graphs Mth 137B Professor: Pri Brtlett Leture 2: Cyley Grphs Week 3 UCSB 2014 (Relevnt soure mteril: Setion VIII.1 of Bollos s Moern Grph Theory; 3.7 of Gosil n Royle s Algeri Grph Theory; vrious ppers I ve re

More information

Lecture 3: Equivalence Relations

Lecture 3: Equivalence Relations Mthcmp Crsh Course Instructor: Pdric Brtlett Lecture 3: Equivlence Reltions Week 1 Mthcmp 2014 In our lst three tlks of this clss, we shift the focus of our tlks from proof techniques to proof concepts

More information

Automatic Synthesis of New Behaviors from a Library of Available Behaviors

Automatic Synthesis of New Behaviors from a Library of Available Behaviors Automti Synthesis of New Behviors from Lirry of Aville Behviors Giuseppe De Giomo Università di Rom L Spienz, Rom, Itly degiomo@dis.unirom1.it Sestin Srdin RMIT University, Melourne, Austrli ssrdin@s.rmit.edu.u

More information

Finite State Automata and Determinisation

Finite State Automata and Determinisation Finite Stte Automt nd Deterministion Tim Dworn Jnury, 2016 Lnguges fs nf re df Deterministion 2 Outline 1 Lnguges 2 Finite Stte Automt (fs) 3 Non-deterministi Finite Stte Automt (nf) 4 Regulr Expressions

More information

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point GCSE C Emple 7 Work out 9 Give your nswer in its simplest form Numers n inies Reiprote mens invert or turn upsie own The reiprol of is 9 9 Mke sure you only invert the frtion you re iviing y 7 You multiply

More information

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106 8. Problem Set Due Wenesy, Ot., t : p.m. in - Problem Mony / Consier the eight vetors 5, 5, 5,..., () List ll of the one-element, linerly epenent sets forme from these. (b) Wht re the two-element, linerly

More information

Algorithms & Data Structures Homework 8 HS 18 Exercise Class (Room & TA): Submitted by: Peer Feedback by: Points:

Algorithms & Data Structures Homework 8 HS 18 Exercise Class (Room & TA): Submitted by: Peer Feedback by: Points: Eidgenössishe Tehnishe Hohshule Zürih Eole polytehnique fédérle de Zurih Politenio federle di Zurigo Federl Institute of Tehnology t Zurih Deprtement of Computer Siene. Novemer 0 Mrkus Püshel, Dvid Steurer

More information

CS 573 Automata Theory and Formal Languages

CS 573 Automata Theory and Formal Languages Non-determinism Automt Theory nd Forml Lnguges Professor Leslie Lnder Leture # 3 Septemer 6, 2 To hieve our gol, we need the onept of Non-deterministi Finite Automton with -moves (NFA) An NFA is tuple

More information

LIP. Laboratoire de l Informatique du Parallélisme. Ecole Normale Supérieure de Lyon

LIP. Laboratoire de l Informatique du Parallélisme. Ecole Normale Supérieure de Lyon LIP Lortoire de l Informtique du Prllélisme Eole Normle Supérieure de Lyon Institut IMAG Unité de reherhe ssoiée u CNRS n 1398 One-wy Cellulr Automt on Cyley Grphs Zsuzsnn Rok Mrs 1993 Reserh Report N

More information

Nondeterministic Finite Automata

Nondeterministic Finite Automata Nondeterministi Finite utomt The Power of Guessing Tuesdy, Otoer 4, 2 Reding: Sipser.2 (first prt); Stoughton 3.3 3.5 S235 Lnguges nd utomt eprtment of omputer Siene Wellesley ollege Finite utomton (F)

More information

Nondeterministic Automata vs Deterministic Automata

Nondeterministic Automata vs Deterministic Automata Nondeterministi Automt vs Deterministi Automt We lerned tht NFA is onvenient model for showing the reltionships mong regulr grmmrs, FA, nd regulr expressions, nd designing them. However, we know tht n

More information

y1 y2 DEMUX a b x1 x2 x3 x4 NETWORK s1 s2 z1 z2

y1 y2 DEMUX a b x1 x2 x3 x4 NETWORK s1 s2 z1 z2 BOOLEAN METHODS Giovnni De Miheli Stnford University Boolen methods Exploit Boolen properties. { Don't re onditions. Minimiztion of the lol funtions. Slower lgorithms, etter qulity results. Externl don't

More information

I 3 2 = I I 4 = 2A

I 3 2 = I I 4 = 2A ECE 210 Eletril Ciruit Anlysis University of llinois t Chigo 2.13 We re ske to use KCL to fin urrents 1 4. The key point in pplying KCL in this prolem is to strt with noe where only one of the urrents

More information

Generalization of 2-Corner Frequency Source Models Used in SMSIM

Generalization of 2-Corner Frequency Source Models Used in SMSIM Generliztion o 2-Corner Frequeny Soure Models Used in SMSIM Dvid M. Boore 26 Mrh 213, orreted Figure 1 nd 2 legends on 5 April 213, dditionl smll orretions on 29 My 213 Mny o the soure spetr models ville

More information

For a, b, c, d positive if a b and. ac bd. Reciprocal relations for a and b positive. If a > b then a ab > b. then

For a, b, c, d positive if a b and. ac bd. Reciprocal relations for a and b positive. If a > b then a ab > b. then Slrs-7.2-ADV-.7 Improper Definite Integrls 27.. D.dox Pge of Improper Definite Integrls Before we strt the min topi we present relevnt lger nd it review. See Appendix J for more lger review. Inequlities:

More information

Eigenvectors and Eigenvalues

Eigenvectors and Eigenvalues MTB 050 1 ORIGIN 1 Eigenvets n Eigenvlues This wksheet esries the lger use to lulte "prinipl" "hrteristi" iretions lle Eigenvets n the "prinipl" "hrteristi" vlues lle Eigenvlues ssoite with these iretions.

More information

Computing Persistent Homology

Computing Persistent Homology Computing Persistent Homology Afr Zomorodin nd Gunnr Crlsson (Disrete nd Computtionl Geometry) Astrt We show tht the persistent homology of filtered d- dimensionl simpliil omplex is simply the stndrd homology

More information

Surface maps into free groups

Surface maps into free groups Surfce mps into free groups lden Wlker Novemer 10, 2014 Free groups wedge X of two circles: Set F = π 1 (X ) =,. We write cpitl letters for inverse, so = 1. e.g. () 1 = Commuttors Let x nd y e loops. The

More information

T b a(f) [f ] +. P b a(f) = Conclude that if f is in AC then it is the difference of two monotone absolutely continuous functions.

T b a(f) [f ] +. P b a(f) = Conclude that if f is in AC then it is the difference of two monotone absolutely continuous functions. Rel Vribles, Fll 2014 Problem set 5 Solution suggestions Exerise 1. Let f be bsolutely ontinuous on [, b] Show tht nd T b (f) P b (f) f (x) dx [f ] +. Conlude tht if f is in AC then it is the differene

More information

GM1 Consolidation Worksheet

GM1 Consolidation Worksheet Cmridge Essentils Mthemtis Core 8 GM1 Consolidtion Worksheet GM1 Consolidtion Worksheet 1 Clulte the size of eh ngle mrked y letter. Give resons for your nswers. or exmple, ngles on stright line dd up

More information

= state, a = reading and q j

= state, a = reading and q j 4 Finite Automt CHAPTER 2 Finite Automt (FA) (i) Derterministi Finite Automt (DFA) A DFA, M Q, q,, F, Where, Q = set of sttes (finite) q Q = the strt/initil stte = input lphet (finite) (use only those

More information

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies

State space systems analysis (continued) Stability. A. Definitions A system is said to be Asymptotically Stable (AS) when it satisfies Stte spce systems nlysis (continued) Stbility A. Definitions A system is sid to be Asymptoticlly Stble (AS) when it stisfies ut () = 0, t > 0 lim xt () 0. t A system is AS if nd only if the impulse response

More information

( ) { } [ ] { } [ ) { } ( ] { }

( ) { } [ ] { } [ ) { } ( ] { } Mth 65 Prelulus Review Properties of Inequlities 1. > nd > >. > + > +. > nd > 0 > 4. > nd < 0 < Asolute Vlue, if 0, if < 0 Properties of Asolute Vlue > 0 1. < < > or

More information

Lecture Summaries for Multivariable Integral Calculus M52B

Lecture Summaries for Multivariable Integral Calculus M52B These leture summries my lso be viewed online by liking the L ion t the top right of ny leture sreen. Leture Summries for Multivrible Integrl Clulus M52B Chpter nd setion numbers refer to the 6th edition.

More information

arxiv: v1 [math.ca] 21 Aug 2018

arxiv: v1 [math.ca] 21 Aug 2018 rxiv:1808.07159v1 [mth.ca] 1 Aug 018 Clulus on Dul Rel Numbers Keqin Liu Deprtment of Mthemtis The University of British Columbi Vnouver, BC Cnd, V6T 1Z Augest, 018 Abstrt We present the bsi theory of

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk out solving systems of liner equtions. These re prolems tht give couple of equtions with couple of unknowns, like: 6= x + x 7=

More information

CS241 Week 6 Tutorial Solutions

CS241 Week 6 Tutorial Solutions 241 Week 6 Tutoril olutions Lnguges: nning & ontext-free Grmmrs Winter 2018 1 nning Exerises 1. 0x0x0xd HEXINT 0x0 I x0xd 2. 0xend--- HEXINT 0xe I nd ER -- MINU - 3. 1234-120x INT 1234 INT -120 I x 4.

More information

8 THREE PHASE A.C. CIRCUITS

8 THREE PHASE A.C. CIRCUITS 8 THREE PHSE.. IRUITS The signls in hpter 7 were sinusoidl lternting voltges nd urrents of the so-lled single se type. n emf of suh type n e esily generted y rotting single loop of ondutor (or single winding),

More information

(a) A partition P of [a, b] is a finite subset of [a, b] containing a and b. If Q is another partition and P Q, then Q is a refinement of P.

(a) A partition P of [a, b] is a finite subset of [a, b] containing a and b. If Q is another partition and P Q, then Q is a refinement of P. Chpter 7: The Riemnn Integrl When the derivtive is introdued, it is not hrd to see tht the it of the differene quotient should be equl to the slope of the tngent line, or when the horizontl xis is time

More information

Chapter 8 Roots and Radicals

Chapter 8 Roots and Radicals Chpter 8 Roots nd Rdils 7 ROOTS AND RADICALS 8 Figure 8. Grphene is n inredily strong nd flexile mteril mde from ron. It n lso ondut eletriity. Notie the hexgonl grid pttern. (redit: AlexnderAIUS / Wikimedi

More information

Functions. mjarrar Watch this lecture and download the slides

Functions. mjarrar Watch this lecture and download the slides 9/6/7 Mustf Jrrr: Leture Notes in Disrete Mthemtis. Birzeit University Plestine 05 Funtions 7.. Introdution to Funtions 7. One-to-One Onto Inverse funtions mjrrr 05 Wth this leture nd downlod the slides

More information

A STUDY OF Q-CONTIGUOUS FUNCTION RELATIONS

A STUDY OF Q-CONTIGUOUS FUNCTION RELATIONS Commun. Koren Mth. So. 31 016, No. 1, pp. 65 94 http://dx.doi.org/10.4134/ckms.016.31.1.065 A STUDY OF Q-CONTIGUOUS FUNCTION RELATIONS Hrsh Vrdhn Hrsh, Yong Sup Kim, Medht Ahmed Rkh, nd Arjun Kumr Rthie

More information