SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES

Size: px
Start display at page:

Download "SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES"

Transcription

1 SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES MARCELLO DELGADO Abstrct. The purpose of this pper is to build up the bsic conceptul frmework nd underlying motivtions tht will llow us to understnd ctegoricl subdivision, nd then work through some specific exmples. Contents 1. Subdivision of Simplicil Sets 1 2. The Nerve of him Fundmentl Ctegory 2 4. A Whole New Section 3 5. Concrete Exmples 4 Acknowledgements 7 References 7 1. Subdivision of Simplicil Sets The ide of subdividing ctegory rises from the notion of brycentric subdivision of simplicil complex. A brycentric subdivision decomposes n n-simplex into simplicil complex of n! n-simplices whose geometric reliztion is homotopy equivlent to the originl simplicil complex. It is with this ide in mind tht we will define the subdivision of simplicil set. First, we hve the notion of geometric simplicil complex, spce built from simplices. We cn move towrds n bstrct definition of simplicil complex. Definition 1.1 (Abstrct Simplicil Complex). A simplicil complex is set X nd collection of its finite subsets S (clled the simplices of X) with the property tht for ny simplex K of X, every subset of K is lso simplex of X. This gives us the fce nd degenercy mps from clss [2], whereby we cn include lower dimensionl simplices in higher dimensionl ones s fces nd we cn project from higher dimensionl simplex onto one of its fces. The key thing to tke wy from this bstrction from the geometric simplicil complexes from topology is the importnce of the fce nd degenercy mps, in prticulr their composition properties. Especilly when working with ordered simplicil complexes (which we cn do by imposing prtil ordering on X so tht the simplices re the totlly ordered subsets), these fce nd degenercy mps become mps of finite totlly ordered sets. This motivtes the following pir of definitions. Dte: July

2 2 MARCELLO DELGADO Definition 1.2 ( ). Let [n] represent the finite poset {0 < 1 <... < n}. Then let denote the ctegory tht hs s its objects the finite posets [n] for ll nonnegtive integers n nd s its rrows the monotonic functions between these posets. Definition 1.3 (Simplicil Sets). A simplicil set is contrvrint functor K : op Set. The ctegory of simplicil sets is the ctegory of ll such contrvrint functors, [ op, Set], nd it is denoted sset. While bstrct, we note tht ech object of picks out set which serves s the set of simplices of tht dimension nd we inherit the fce nd degenercy mps with the composition properties we love from the monotonic mps in nd by contrvrincy. In the wy we hve subdivision of simplicil complexes, we cn define subdivision on simplicil sets, functor Sd : ssets ssets, which is explined in detil in My s notes [2]. With this functor, we cn define subdivision on smll ctegories by composing nd precomposing it with functors to nd from Ct, respectively. These re the fundmentl ctegory nd nerve functors. 2. The Nerve of him... Here, we will construct the nerve functor N : Ct sset. The nerve functor gives us wy to turn smll ctegories into simplicil sets in firly intuitive wy. First, we note tht every poset, nd in prticulr the posets [n], cn be seen s ctegories with t most one rrow between ny pir of objects nd monotonic mps between posets cn then be seen s functors. Thus, we hve n inclusion : Ct. For given smll ctegory C, define NC n to be the set of ll covrint functors [n] C. For n rrow µ : [m] [n], define µ := µ : NC n NC m. This collection of sets NC n defines simplicil set, where the objects [n] of re mpped to the corresponding set NC n nd rrows µ in re mpped to µ. Now suppose we hve functor F : C D. We get nturl trnsformtion F : NC ND given by F n = F : NC n ND n. Thus, we hve functor N : Ct sset given on objects by C NC nd on rrows by F F. Definition 2.1 (Nerve Functor). The covrint functor N : Ct sset is clled the nerve functor. 3. Fundmentl Ctegory Now we describe the fundmentl ctegory functor, τ 1 : ssets Ct, llowing us to ssocite ctegory to simplicil set in cnonicl wy, nd it will turn out tht this functor is left djoint to the nerve functor. Strting with simplicil set K, tke s the objects of τ 1 K the elements of K 0, the 0-simplices of K. For every 1-simplex y, hve n rrow y : d 1 y d 0 y. Tck on ll forml composites tht mke sense (i.e. form yz if d 0 z = d 1 y). Finlly, we impose the following two reltions: s 0 x = 1 x for x K 0 nd d 1 z = d 0 z d 2 z for z K 2 This gives us well-defined ctegory [2]. Definition 3.1 (Fundmentl Ctegory Functor). The functor τ 1 : sset Ct is clled the fundmentl ctegory functor.

3 SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES 3 Now tht we hve ll these pieces in plce, we re in position to define ctegoricl subdivision. Definition 3.2 (Subdivision). We define the subdivision functor Sd : Ct Ct s Sd := τ 1 Sd N, where the Sd in the composition is the subdivision functor on simplicil sets. While this definition mkes conceptul sense, it is not computtionlly friendly. To see concrete exmples of ctegoricl subdivision, we need more constructive look t subdivision. 4. A Whole New Section So in order to understnd the construction of the subdivision functor, we first need to introduce the concept of left fiber. Definition 4.1 ([1]). [Left Fiber] Let F : C D be functor nd let T ob D. The left fiber F/T of F over T is the ctegory of pirs (X, µ), where X ob C nd µ : F X T with rrows f : (X, µ) (X, µ ) corresponding to rrows f : X X in C s.t. µ F f = µ. Digrmmticlly, F f F X F X µ µ T Let s consider the objects of, the posets [n], s ctegories. Then we hve n inclusion functor : Ct. If we consider n rbitrry smll ctegory C in Ct, we cn look t the left fiber of over C: /C. The objects of this ctegory re the ll the rrows [p] C for ll [p], which re exctly ll the the simplices of NC. In the following discussion, we will use [n] to represent the imge of [n] under, but for ny rrows f : [m] [n], f : [m] [n] will represent the imge of f in Ct. If we re lredy using subscripts for something else, then we ll use superscript : f. Now tht we hve this ctegory, consider q simplex X NC q nd surjective (monotonic) mp s : [q + 1] [q] in. If d, d : [q + 1] [q] re the two right inverses of s, then we sy tht d, d : ([q], X) ([q + 1], Xs) re elementry equivlent, denoted d d. Clerly, is symmetric nd reflexive. Let be the miniml equivlence reltion on the rrows of /C generted by. The we cn define [ /C] := ( /C)/. Now tht we hve this, we cn define the subdivision of smll ctegory C: Definition 4.2 (Subdvision). For smll ctegory C, the subdivision of C, Sd(C), is the full subctegory of [ /C] tken on the nondegenerte simplices of C, where nondegenrte simplex is one in which none of the q composed rrows is n identity rrow for some object in C. This functor is equl to the functor given erlier in terms of simplicil sets, i.e. Sd = τ 1 sd N [1].

4 4 MARCELLO DELGADO 5. Concrete Exmples Here in this section, we will compute few concrete exmples of subdivisions. We will strt with some trivil exmples nd work up to some interesting ones, including one infinite exmple. We ll see multiple times instnces of how two consecutive subdivisions yields poset. It s worth noting t this point tht when we compute these exmples, since our result will only depend on nondegenerte simplices, we will omit them in the erly stges of the computtion (despite the fct tht they should be there in the ctegories we re looking t t tht stge) becuse they ll be irrelevnt in the finl result. Further, when we re looking for rrows in /C, we do not need to consider the σ i mps. To see this, suppose we hve n rrow in /C corresponding to some σ i : [q + 1] [q]. Then this tells us tht the (q + 1)-simplex we re considering fctors through s q-simplex, nd so one of its composble rrows is n identity. Thus, the (q + 1)-simplex is degenerte, nd doesn t pper in Sd(C). Finlly, we will only consider the rrows δ i. The reson for this is tht ny rrows in cn be written s composition of the σ i nd δ i, nd so the rrows in /C corresponding to these compositions re just the composition of the rrows for the ssocited δ i nd σ i (remembering of course tht the σ i will become irrelevnt). Hving this, let s consider our first concrete exmple. Consider the ctegory 1 consisting of single object nd its identity rrow. First, let s mke list of ll the nondegenerte simplices of 1. We only hve one nondegenerte 0-simplex, : [0] 1, nd no nondegenerte simplices of higher dimension. Since there re no other simplices, then there re no nonidentity rrows in /C, nd since there re no nontrivil composble pirs, then we hve no elementry equivlent pirs. Thus, Sd(1) = 1. Now consider the ctegory 1, consisting of single object which hs one nonidentity rrow :. In this exmple, we ll ssume tht f f = 1. Now, we hve one 0-simplex, : [0] 1, nd one nondegenerte 1-simplex, : [1] 1. Agin, there re no other nondegenerte simplices. Thus, we re considering ctegory with two objects: nd. Our potentil rrows re, : [0] [1], which in /C will be of the form δ0, δ1 : X for some object (simplex) X. We re looking for simplices X : [0] 1 such tht X =. picks out the codomin (by deleting 0) of, which is 0, so X = 0. Anlogously, we hve n rrow δ1 : 0 since picks out 0 (by deleting 1). nd cnnot be right inverses for the sme mp, so they re not elementry equivlent. Therefore, we get tht Sd(1 ) = 0 We lso note the following useful heuristic: If we view 1 s 0 0, then it s subdivision is 0 δ0 δ 1 0. Our next exmple is the ctegory 2: 0 1. There re three nondegenerte simplices: 0 : [0] 2, 1 : [0] 2, nd : [1] 2. Since there is no nonidentity rrow [0] [0], we cn ssume tht ll nonidentity rrows in Sd(2) will be either of the form 0 or 1. Following the led of the previous exmple, we see tht

5 SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES 5 these two rrows re : 1 nd : 0. Agin, these re not elementry equivlents, so we hve tht Sd(2) = 0 δ1 δ 1 1. Our next exmple is the ctegory C tht is just corner of rrows: 0 The heuristic tells us tht our subdivision should look like this: 0 2 b 1 In C, we hve three 0-simplices nd two 1-simplieces: 0 : [0] C : [1] C 1 : [0] C b : [1] C 2 : [0] C 2 b 1. There re no nonidentity mps [0] [0]. Any mp [1] [1] is either constnt mp (giving us degenercy) or the identity (by monotonicity), so we only need to consider rrows [0] [1]. There re no rrows 0 b or 2 since the imges of 0 nd b re disjoint nd the imges of 2 nd re disjoint. Thus, we hve four possible rrows in Sd(C), ll of which turn out to ctully be rrows. Thus, we hve tht Sd(C) = 0 δ b Or, if we linerize it, we get 0 δ1 δ 1 δ 2 b 0 1, which is exctly wht we expected. Note tht Sd(C) = Sd 2 (2), which is poset. Now let s consider the ctegory P consisting if two objects 0 nd 1 nd two prllel nonisomorphism rrows, b : 0 1. Digrmmticlly, P = 0 1. This ctegory hs two 0-simplices, 0 : [0] P nd 1 : [0] P, nd two 1-simplices, : [1] P nd b : [1] P. There re no other nondegenerte simplices. This gives us four relevnt rrows in [ /P]: : 1, : 0, : 1 b, nd : 0 b. Since none of these rrows re elementry equivlent pirs, we hve tht Sd(P) = 0 1 b It s worth noting tht Sd(P) = Sd 2 (1 ), nd tht it s poset. If we look t the geometric reliztion of 1, N(1 ), we observe tht it s homeomorphic to S 1 nd tht Sd 2 (1 ) is the 4-point model tht is wekly homotopy equivlent to S 1. b

6 6 MARCELLO DELGADO Now let s exmine n exmple with nontrivil composition of rrows. Consider the ctegory T : 0 1 Let s mke list of ll the nondegenerte simplices: b 0-simplices 1-simplices 2-simplices 0 : [0] T : [1] T b : [2] T 1 : [0] T b : [1] T 2 : [0] T b : [1] T Here, we distinguish between the 1-simplex corresponding to the composite b nd between the 2-simplex consisting of the two composble rrows 0 1 b 2 which we denote b. So our subdivided ctegory will hve these seven objects. Now let s looks t rrows in our new ctegory. We hve six rrows going from the 0-simplices to the 1-simplices which re the mps tht compose with the degenercy mps δ i to give us mps tht pick out the domin nd codomin of ech rrow s in ech of the previous exmples. This gives us the six rrows : 1 : 0 : 2 b 2 b : 1 b : 2 b : 0 b We lso get three more rrows tht pick out the fces of the commuttive tringle: : b b : b b δ 2 : b Thus, we get the following digrm for /T (restricted to nondegenerte simplices): 0 δ 2 1 b δ1 b 2 b We leve out the composite rrows nd we don t clim tht this digrm commutes since we hve not shown, for exmple, tht δ 2 = for the two composite rrows 0 b. Wht we would like to show is tht these three pirs of composites re elementry equivlent, tht is: δ 2 δ 2 There is only single mp s : [2] [0]. By composition with ny of the six mps listed bove, we get 1 [0] since there re no other mps [0] [0], which proves elementry equivlence. Thus, the digrm bove commutes in Sd(T ). We cn rerrnge this digrm nd get the following digrm which commutes becuse the

7 SOME EXAMPLES OF SUBDIVISION OF SMALL CATEGORIES 7 unlbeled composites re elementry equivlent nd re identified in [ /T ]: 1 δ 2 δ 0 b b 0 b 2 This should remind us very strongly of the result of brycentric subdivision of 2-simplex in lgebric topology. For our lst finite exmple, consider the groupoid G : 0 1, where b = 1 0 nd b = 1 1. We observe tht G hs two nondegenerte simplices of ech dimension: the 0-simplices 0 nd 1, the 1-simplices nd b, nd for ech [q] for q > 2 the two compositions of length q b... nd bb.... As for the rrows, there re two wys to include string of lternting s nd bs of length q into one of length q + 1: dd the pproprite letter to the beginning ( ) or to the end (δ q+1 ). It will turn out [1] tht ll composites will work out to be ppropritely elementry equivlent, so tht we get Sd(G) = δ 2 0 b b 1 b b bb δ 2 And our finl exmple is our only infinite exmple. Consider the ctegory A We know how ech corner of rrows subdivides by previous exmple. Since we hve no nontrivil compositions of rrows nd since ech corner subdivides into two corners, we get tht Sd(A) = A. δ 3 δ 3 Acknowledgements Thnks gin to my mentors Clire nd Emily, without with which this pper would be lot shorter. References [1] Mtis del Hoyo On the subdivision of smll ctegories Topology nd its Applictions. Volume 155, Issue 11, 1 June 2008, Pges [2] J. P. My. Subdivisions of Smll Ctegories. my/finite/subdivide.pdf b

a(e, x) = x. Diagrammatically, this is encoded as the following commutative diagrams / X

a(e, x) = x. Diagrammatically, this is encoded as the following commutative diagrams / X 4. Mon, Sept. 30 Lst time, we defined the quotient topology coming from continuous surjection q : X! Y. Recll tht q is quotient mp (nd Y hs the quotient topology) if V Y is open precisely when q (V ) X

More information

If you are at the university, either physically or via the VPN, you can download the chapters of this book as PDFs.

If you are at the university, either physically or via the VPN, you can download the chapters of this book as PDFs. Lecture 5 Wlks, Trils, Pths nd Connectedness Reding: Some of the mteril in this lecture comes from Section 1.2 of Dieter Jungnickel (2008), Grphs, Networks nd Algorithms, 3rd edition, which is ville online

More information

INTRODUCTION TO SIMPLICIAL COMPLEXES

INTRODUCTION TO SIMPLICIAL COMPLEXES INTRODUCTION TO SIMPLICIAL COMPLEXES CASEY KELLEHER AND ALESSANDRA PANTANO 0.1. Introduction. In this ctivity set we re going to introduce notion from Algebric Topology clled simplicil homology. The min

More information

Section 3.1: Sequences and Series

Section 3.1: Sequences and Series Section.: Sequences d Series Sequences Let s strt out with the definition of sequence: sequence: ordered list of numbers, often with definite pttern Recll tht in set, order doesn t mtter so this is one

More information

such that the S i cover S, or equivalently S

such that the S i cover S, or equivalently S MATH 55 Triple Integrls Fll 16 1. Definition Given solid in spce, prtition of consists of finite set of solis = { 1,, n } such tht the i cover, or equivlently n i. Furthermore, for ech i, intersects i

More information

Definition of Regular Expression

Definition of Regular Expression Definition of Regulr Expression After the definition of the string nd lnguges, we re redy to descrie regulr expressions, the nottion we shll use to define the clss of lnguges known s regulr sets. Recll

More information

MATH 25 CLASS 5 NOTES, SEP

MATH 25 CLASS 5 NOTES, SEP MATH 25 CLASS 5 NOTES, SEP 30 2011 Contents 1. A brief diversion: reltively prime numbers 1 2. Lest common multiples 3 3. Finding ll solutions to x + by = c 4 Quick links to definitions/theorems Euclid

More information

Subtracting Fractions

Subtracting Fractions Lerning Enhncement Tem Model Answers: Adding nd Subtrcting Frctions Adding nd Subtrcting Frctions study guide. When the frctions both hve the sme denomintor (bottom) you cn do them using just simple dding

More information

Unit #9 : Definite Integral Properties, Fundamental Theorem of Calculus

Unit #9 : Definite Integral Properties, Fundamental Theorem of Calculus Unit #9 : Definite Integrl Properties, Fundmentl Theorem of Clculus Gols: Identify properties of definite integrls Define odd nd even functions, nd reltionship to integrl vlues Introduce the Fundmentl

More information

Ray surface intersections

Ray surface intersections Ry surfce intersections Some primitives Finite primitives: polygons spheres, cylinders, cones prts of generl qudrics Infinite primitives: plnes infinite cylinders nd cones generl qudrics A finite primitive

More information

MA1008. Calculus and Linear Algebra for Engineers. Course Notes for Section B. Stephen Wills. Department of Mathematics. University College Cork

MA1008. Calculus and Linear Algebra for Engineers. Course Notes for Section B. Stephen Wills. Department of Mathematics. University College Cork MA1008 Clculus nd Liner Algebr for Engineers Course Notes for Section B Stephen Wills Deprtment of Mthemtics University College Cork s.wills@ucc.ie http://euclid.ucc.ie/pges/stff/wills/teching/m1008/ma1008.html

More information

In the last lecture, we discussed how valid tokens may be specified by regular expressions.

In the last lecture, we discussed how valid tokens may be specified by regular expressions. LECTURE 5 Scnning SYNTAX ANALYSIS We know from our previous lectures tht the process of verifying the syntx of the progrm is performed in two stges: Scnning: Identifying nd verifying tokens in progrm.

More information

COMP 423 lecture 11 Jan. 28, 2008

COMP 423 lecture 11 Jan. 28, 2008 COMP 423 lecture 11 Jn. 28, 2008 Up to now, we hve looked t how some symols in n lphet occur more frequently thn others nd how we cn sve its y using code such tht the codewords for more frequently occuring

More information

CS201 Discussion 10 DRAWTREE + TRIES

CS201 Discussion 10 DRAWTREE + TRIES CS201 Discussion 10 DRAWTREE + TRIES DrwTree First instinct: recursion As very generic structure, we could tckle this problem s follows: drw(): Find the root drw(root) drw(root): Write the line for the

More information

Math 464 Fall 2012 Notes on Marginal and Conditional Densities October 18, 2012

Math 464 Fall 2012 Notes on Marginal and Conditional Densities October 18, 2012 Mth 464 Fll 2012 Notes on Mrginl nd Conditionl Densities klin@mth.rizon.edu October 18, 2012 Mrginl densities. Suppose you hve 3 continuous rndom vribles X, Y, nd Z, with joint density f(x,y,z. The mrginl

More information

File Manager Quick Reference Guide. June Prepared for the Mayo Clinic Enterprise Kahua Deployment

File Manager Quick Reference Guide. June Prepared for the Mayo Clinic Enterprise Kahua Deployment File Mnger Quick Reference Guide June 2018 Prepred for the Myo Clinic Enterprise Khu Deployment NVIGTION IN FILE MNGER To nvigte in File Mnger, users will mke use of the left pne to nvigte nd further pnes

More information

Fig.25: the Role of LEX

Fig.25: the Role of LEX The Lnguge for Specifying Lexicl Anlyzer We shll now study how to uild lexicl nlyzer from specifiction of tokens in the form of list of regulr expressions The discussion centers round the design of n existing

More information

Dr. D.M. Akbar Hussain

Dr. D.M. Akbar Hussain Dr. D.M. Akr Hussin Lexicl Anlysis. Bsic Ide: Red the source code nd generte tokens, it is similr wht humns will do to red in; just tking on the input nd reking it down in pieces. Ech token is sequence

More information

A GENERALIZED PROCEDURE FOR DEFINING QUOTIENT SPACES. b y HAROLD G. LAWRENCE A THESIS OREGON STATE UNIVERSITY MASTER OF ARTS

A GENERALIZED PROCEDURE FOR DEFINING QUOTIENT SPACES. b y HAROLD G. LAWRENCE A THESIS OREGON STATE UNIVERSITY MASTER OF ARTS A GENERALIZED PROCEDURE FOR DEFINING QUOTIENT SPACES b y HAROLD G. LAWRENCE A THESIS submitted to OREGON STATE UNIVERSITY in prtil fulfillment of the requirements for the degree of MASTER OF ARTS June

More information

AVolumePreservingMapfromCubetoOctahedron

AVolumePreservingMapfromCubetoOctahedron Globl Journl of Science Frontier Reserch: F Mthemtics nd Decision Sciences Volume 18 Issue 1 Version 1.0 er 018 Type: Double Blind Peer Reviewed Interntionl Reserch Journl Publisher: Globl Journls Online

More information

CS311H: Discrete Mathematics. Graph Theory IV. A Non-planar Graph. Regions of a Planar Graph. Euler s Formula. Instructor: Işıl Dillig

CS311H: Discrete Mathematics. Graph Theory IV. A Non-planar Graph. Regions of a Planar Graph. Euler s Formula. Instructor: Işıl Dillig CS311H: Discrete Mthemtics Grph Theory IV Instructor: Işıl Dillig Instructor: Işıl Dillig, CS311H: Discrete Mthemtics Grph Theory IV 1/25 A Non-plnr Grph Regions of Plnr Grph The plnr representtion of

More information

10.5 Graphing Quadratic Functions

10.5 Graphing Quadratic Functions 0.5 Grphing Qudrtic Functions Now tht we cn solve qudrtic equtions, we wnt to lern how to grph the function ssocited with the qudrtic eqution. We cll this the qudrtic function. Grphs of Qudrtic Functions

More information

Fall 2018 Midterm 1 October 11, ˆ You may not ask questions about the exam except for language clarifications.

Fall 2018 Midterm 1 October 11, ˆ You may not ask questions about the exam except for language clarifications. 15-112 Fll 2018 Midterm 1 October 11, 2018 Nme: Andrew ID: Recittion Section: ˆ You my not use ny books, notes, extr pper, or electronic devices during this exm. There should be nothing on your desk or

More information

6.2 Volumes of Revolution: The Disk Method

6.2 Volumes of Revolution: The Disk Method mth ppliction: volumes by disks: volume prt ii 6 6 Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem 6) nd the ccumultion process is to determine so-clled volumes

More information

Theory of Computation CSE 105

Theory of Computation CSE 105 $ $ $ Theory of Computtion CSE 105 Regulr Lnguges Study Guide nd Homework I Homework I: Solutions to the following problems should be turned in clss on July 1, 1999. Instructions: Write your nswers clerly

More information

9 4. CISC - Curriculum & Instruction Steering Committee. California County Superintendents Educational Services Association

9 4. CISC - Curriculum & Instruction Steering Committee. California County Superintendents Educational Services Association 9. CISC - Curriculum & Instruction Steering Committee The Winning EQUATION A HIGH QUALITY MATHEMATICS PROFESSIONAL DEVELOPMENT PROGRAM FOR TEACHERS IN GRADES THROUGH ALGEBRA II STRAND: NUMBER SENSE: Rtionl

More information

ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών

ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών ΕΠΛ323 - Θωρία και Πρακτική Μταγλωττιστών Lecture 3 Lexicl Anlysis Elis Athnsopoulos elisthn@cs.ucy.c.cy Recognition of Tokens if expressions nd reltionl opertors if è if then è then else è else relop

More information

Solutions to Math 41 Final Exam December 12, 2011

Solutions to Math 41 Final Exam December 12, 2011 Solutions to Mth Finl Em December,. ( points) Find ech of the following its, with justifiction. If there is n infinite it, then eplin whether it is or. ( ) / ln() () (5 points) First we compute the it:

More information

ON THE DEHN COMPLEX OF VIRTUAL LINKS

ON THE DEHN COMPLEX OF VIRTUAL LINKS ON THE DEHN COMPLEX OF VIRTUAL LINKS RACHEL BYRD, JENS HARLANDER Astrct. A virtul link comes with vriety of link complements. This rticle is concerned with the Dehn spce, pseudo mnifold with oundry, nd

More information

EECS 281: Homework #4 Due: Thursday, October 7, 2004

EECS 281: Homework #4 Due: Thursday, October 7, 2004 EECS 28: Homework #4 Due: Thursdy, October 7, 24 Nme: Emil:. Convert the 24-bit number x44243 to mime bse64: QUJD First, set is to brek 8-bit blocks into 6-bit blocks, nd then convert: x44243 b b 6 2 9

More information

arxiv:cs.cg/ v1 18 Oct 2005

arxiv:cs.cg/ v1 18 Oct 2005 A Pir of Trees without Simultneous Geometric Embedding in the Plne rxiv:cs.cg/0510053 v1 18 Oct 2005 Mrtin Kutz Mx-Plnck-Institut für Informtik, Srbrücken, Germny mkutz@mpi-inf.mpg.de October 19, 2005

More information

a < a+ x < a+2 x < < a+n x = b, n A i n f(x i ) x. i=1 i=1

a < a+ x < a+2 x < < a+n x = b, n A i n f(x i ) x. i=1 i=1 Mth 33 Volume Stewrt 5.2 Geometry of integrls. In this section, we will lern how to compute volumes using integrls defined by slice nlysis. First, we recll from Clculus I how to compute res. Given the

More information

Fall 2017 Midterm Exam 1 October 19, You may not use any books, notes, or electronic devices during this exam.

Fall 2017 Midterm Exam 1 October 19, You may not use any books, notes, or electronic devices during this exam. 15-112 Fll 2017 Midterm Exm 1 October 19, 2017 Nme: Andrew ID: Recittion Section: You my not use ny books, notes, or electronic devices during this exm. You my not sk questions bout the exm except for

More information

Spring 2018 Midterm Exam 1 March 1, You may not use any books, notes, or electronic devices during this exam.

Spring 2018 Midterm Exam 1 March 1, You may not use any books, notes, or electronic devices during this exam. 15-112 Spring 2018 Midterm Exm 1 Mrch 1, 2018 Nme: Andrew ID: Recittion Section: You my not use ny books, notes, or electronic devices during this exm. You my not sk questions bout the exm except for lnguge

More information

ECE 468/573 Midterm 1 September 28, 2012

ECE 468/573 Midterm 1 September 28, 2012 ECE 468/573 Midterm 1 September 28, 2012 Nme:! Purdue emil:! Plese sign the following: I ffirm tht the nswers given on this test re mine nd mine lone. I did not receive help from ny person or mteril (other

More information

Section 10.4 Hyperbolas

Section 10.4 Hyperbolas 66 Section 10.4 Hyperbols Objective : Definition of hyperbol & hyperbols centered t (0, 0). The third type of conic we will study is the hyperbol. It is defined in the sme mnner tht we defined the prbol

More information

Unit 5 Vocabulary. A function is a special relationship where each input has a single output.

Unit 5 Vocabulary. A function is a special relationship where each input has a single output. MODULE 3 Terms Definition Picture/Exmple/Nottion 1 Function Nottion Function nottion is n efficient nd effective wy to write functions of ll types. This nottion llows you to identify the input vlue with

More information

1. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES)

1. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES) Numbers nd Opertions, Algebr, nd Functions 45. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES) In sequence of terms involving eponentil growth, which the testing service lso clls geometric

More information

Pointwise convergence need not behave well with respect to standard properties such as continuity.

Pointwise convergence need not behave well with respect to standard properties such as continuity. Chpter 3 Uniform Convergence Lecture 9 Sequences of functions re of gret importnce in mny res of pure nd pplied mthemtics, nd their properties cn often be studied in the context of metric spces, s in Exmples

More information

CS321 Languages and Compiler Design I. Winter 2012 Lecture 5

CS321 Languages and Compiler Design I. Winter 2012 Lecture 5 CS321 Lnguges nd Compiler Design I Winter 2012 Lecture 5 1 FINITE AUTOMATA A non-deterministic finite utomton (NFA) consists of: An input lphet Σ, e.g. Σ =,. A set of sttes S, e.g. S = {1, 3, 5, 7, 11,

More information

Presentation Martin Randers

Presentation Martin Randers Presenttion Mrtin Rnders Outline Introduction Algorithms Implementtion nd experiments Memory consumption Summry Introduction Introduction Evolution of species cn e modelled in trees Trees consist of nodes

More information

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it.

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it. 6.3 Volumes Just s re is lwys positive, so is volume nd our ttitudes towrds finding it. Let s review how to find the volume of regulr geometric prism, tht is, 3-dimensionl oject with two regulr fces seprted

More information

Midterm 2 Sample solution

Midterm 2 Sample solution Nme: Instructions Midterm 2 Smple solution CMSC 430 Introduction to Compilers Fll 2012 November 28, 2012 This exm contins 9 pges, including this one. Mke sure you hve ll the pges. Write your nme on the

More information

1 Drawing 3D Objects in Adobe Illustrator

1 Drawing 3D Objects in Adobe Illustrator Drwing 3D Objects in Adobe Illustrtor 1 1 Drwing 3D Objects in Adobe Illustrtor This Tutoril will show you how to drw simple objects with three-dimensionl ppernce. At first we will drw rrows indicting

More information

Answer Key Lesson 6: Workshop: Angles and Lines

Answer Key Lesson 6: Workshop: Angles and Lines nswer Key esson 6: tudent Guide ngles nd ines Questions 1 3 (G p. 406) 1. 120 ; 360 2. hey re the sme. 3. 360 Here re four different ptterns tht re used to mke quilts. Work with your group. se your Power

More information

Integration. September 28, 2017

Integration. September 28, 2017 Integrtion September 8, 7 Introduction We hve lerned in previous chpter on how to do the differentition. It is conventionl in mthemtics tht we re supposed to lern bout the integrtion s well. As you my

More information

Summer Review Packet For Algebra 2 CP/Honors

Summer Review Packet For Algebra 2 CP/Honors Summer Review Pcket For Alger CP/Honors Nme Current Course Mth Techer Introduction Alger uilds on topics studied from oth Alger nd Geometr. Certin topics re sufficientl involved tht the cll for some review

More information

If f(x, y) is a surface that lies above r(t), we can think about the area between the surface and the curve.

If f(x, y) is a surface that lies above r(t), we can think about the area between the surface and the curve. Line Integrls The ide of line integrl is very similr to tht of single integrls. If the function f(x) is bove the x-xis on the intervl [, b], then the integrl of f(x) over [, b] is the re under f over the

More information

Homework. Context Free Languages III. Languages. Plan for today. Context Free Languages. CFLs and Regular Languages. Homework #5 (due 10/22)

Homework. Context Free Languages III. Languages. Plan for today. Context Free Languages. CFLs and Regular Languages. Homework #5 (due 10/22) Homework Context Free Lnguges III Prse Trees nd Homework #5 (due 10/22) From textbook 6.4,b 6.5b 6.9b,c 6.13 6.22 Pln for tody Context Free Lnguges Next clss of lnguges in our quest! Lnguges Recll. Wht

More information

9 Graph Cutting Procedures

9 Graph Cutting Procedures 9 Grph Cutting Procedures Lst clss we begn looking t how to embed rbitrry metrics into distributions of trees, nd proved the following theorem due to Brtl (1996): Theorem 9.1 (Brtl (1996)) Given metric

More information

Introduction to Computer Engineering EECS 203 dickrp/eecs203/ CMOS transmission gate (TG) TG example

Introduction to Computer Engineering EECS 203  dickrp/eecs203/ CMOS transmission gate (TG) TG example Introduction to Computer Engineering EECS 23 http://ziyng.eecs.northwestern.edu/ dickrp/eecs23/ CMOS trnsmission gte TG Instructor: Robert Dick Office: L477 Tech Emil: dickrp@northwestern.edu Phone: 847

More information

What do all those bits mean now? Number Systems and Arithmetic. Introduction to Binary Numbers. Questions About Numbers

What do all those bits mean now? Number Systems and Arithmetic. Introduction to Binary Numbers. Questions About Numbers Wht do ll those bits men now? bits (...) Number Systems nd Arithmetic or Computers go to elementry school instruction R-formt I-formt... integer dt number text chrs... floting point signed unsigned single

More information

Engineer To Engineer Note

Engineer To Engineer Note Engineer To Engineer Note EE-188 Technicl Notes on using Anlog Devices' DSP components nd development tools Contct our technicl support by phone: (800) ANALOG-D or e-mil: dsp.support@nlog.com Or visit

More information

Rational Numbers---Adding Fractions With Like Denominators.

Rational Numbers---Adding Fractions With Like Denominators. Rtionl Numbers---Adding Frctions With Like Denomintors. A. In Words: To dd frctions with like denomintors, dd the numertors nd write the sum over the sme denomintor. B. In Symbols: For frctions c nd b

More information

MATH 2530: WORKSHEET 7. x 2 y dz dy dx =

MATH 2530: WORKSHEET 7. x 2 y dz dy dx = MATH 253: WORKSHT 7 () Wrm-up: () Review: polr coordintes, integrls involving polr coordintes, triple Riemnn sums, triple integrls, the pplictions of triple integrls (especilly to volume), nd cylindricl

More information

CSCE 531, Spring 2017, Midterm Exam Answer Key

CSCE 531, Spring 2017, Midterm Exam Answer Key CCE 531, pring 2017, Midterm Exm Answer Key 1. (15 points) Using the method descried in the ook or in clss, convert the following regulr expression into n equivlent (nondeterministic) finite utomton: (

More information

Dynamic Programming. Andreas Klappenecker. [partially based on slides by Prof. Welch] Monday, September 24, 2012

Dynamic Programming. Andreas Klappenecker. [partially based on slides by Prof. Welch] Monday, September 24, 2012 Dynmic Progrmming Andres Klppenecker [prtilly bsed on slides by Prof. Welch] 1 Dynmic Progrmming Optiml substructure An optiml solution to the problem contins within it optiml solutions to subproblems.

More information

Improper Integrals. October 4, 2017

Improper Integrals. October 4, 2017 Improper Integrls October 4, 7 Introduction We hve seen how to clculte definite integrl when the it is rel number. However, there re times when we re interested to compute the integrl sy for emple 3. Here

More information

Math 142, Exam 1 Information.

Math 142, Exam 1 Information. Mth 14, Exm 1 Informtion. 9/14/10, LC 41, 9:30-10:45. Exm 1 will be bsed on: Sections 7.1-7.5. The corresponding ssigned homework problems (see http://www.mth.sc.edu/ boyln/sccourses/14f10/14.html) At

More information

12-B FRACTIONS AND DECIMALS

12-B FRACTIONS AND DECIMALS -B Frctions nd Decimls. () If ll four integers were negtive, their product would be positive, nd so could not equl one of them. If ll four integers were positive, their product would be much greter thn

More information

1 Quad-Edge Construction Operators

1 Quad-Edge Construction Operators CS48: Computer Grphics Hndout # Geometric Modeling Originl Hndout #5 Stnford University Tuesdy, 8 December 99 Originl Lecture #5: 9 November 99 Topics: Mnipultions with Qud-Edge Dt Structures Scribe: Mike

More information

Integration. October 25, 2016

Integration. October 25, 2016 Integrtion October 5, 6 Introduction We hve lerned in previous chpter on how to do the differentition. It is conventionl in mthemtics tht we re supposed to lern bout the integrtion s well. As you my hve

More information

A Formalism for Functionality Preserving System Level Transformations

A Formalism for Functionality Preserving System Level Transformations A Formlism for Functionlity Preserving System Level Trnsformtions Smr Abdi Dniel Gjski Center for Embedded Computer Systems UC Irvine Center for Embedded Computer Systems UC Irvine Irvine, CA 92697 Irvine,

More information

P(r)dr = probability of generating a random number in the interval dr near r. For this probability idea to make sense we must have

P(r)dr = probability of generating a random number in the interval dr near r. For this probability idea to make sense we must have Rndom Numers nd Monte Crlo Methods Rndom Numer Methods The integrtion methods discussed so fr ll re sed upon mking polynomil pproximtions to the integrnd. Another clss of numericl methods relies upon using

More information

Determining Single Connectivity in Directed Graphs

Determining Single Connectivity in Directed Graphs Determining Single Connectivity in Directed Grphs Adm L. Buchsbum 1 Mrtin C. Crlisle 2 Reserch Report CS-TR-390-92 September 1992 Abstrct In this pper, we consider the problem of determining whether or

More information

TO REGULAR EXPRESSIONS

TO REGULAR EXPRESSIONS Suject :- Computer Science Course Nme :- Theory Of Computtion DA TO REGULAR EXPRESSIONS Report Sumitted y:- Ajy Singh Meen 07000505 jysmeen@cse.iit.c.in BASIC DEINITIONS DA:- A finite stte mchine where

More information

3.5.1 Single slit diffraction

3.5.1 Single slit diffraction 3.5.1 Single slit diffrction Wves pssing through single slit will lso diffrct nd produce n interference pttern. The reson for this is to do with the finite width of the slit. We will consider this lter.

More information

2 Computing all Intersections of a Set of Segments Line Segment Intersection

2 Computing all Intersections of a Set of Segments Line Segment Intersection 15-451/651: Design & Anlysis of Algorithms Novemer 14, 2016 Lecture #21 Sweep-Line nd Segment Intersection lst chnged: Novemer 8, 2017 1 Preliminries The sweep-line prdigm is very powerful lgorithmic design

More information

Lists in Lisp and Scheme

Lists in Lisp and Scheme Lists in Lisp nd Scheme Lists in Lisp nd Scheme Lists re Lisp s fundmentl dt structures, ut there re others Arrys, chrcters, strings, etc. Common Lisp hs moved on from eing merely LISt Processor However,

More information

A New Learning Algorithm for the MAXQ Hierarchical Reinforcement Learning Method

A New Learning Algorithm for the MAXQ Hierarchical Reinforcement Learning Method A New Lerning Algorithm for the MAXQ Hierrchicl Reinforcement Lerning Method Frzneh Mirzzdeh 1, Bbk Behsz 2, nd Hmid Beigy 1 1 Deprtment of Computer Engineering, Shrif University of Technology, Tehrn,

More information

Physics 208: Electricity and Magnetism Exam 1, Secs Feb IMPORTANT. Read these directions carefully:

Physics 208: Electricity and Magnetism Exam 1, Secs Feb IMPORTANT. Read these directions carefully: Physics 208: Electricity nd Mgnetism Exm 1, Secs. 506 510 11 Feb. 2004 Instructor: Dr. George R. Welch, 415 Engineering-Physics, 845-7737 Print your nme netly: Lst nme: First nme: Sign your nme: Plese

More information

Suffix trees, suffix arrays, BWT

Suffix trees, suffix arrays, BWT ALGORITHMES POUR LA BIO-INFORMATIQUE ET LA VISUALISATION COURS 3 Rluc Uricru Suffix trees, suffix rrys, BWT Bsed on: Suffix trees nd suffix rrys presenttion y Him Kpln Suffix trees course y Pco Gomez Liner-Time

More information

Typing with Weird Keyboards Notes

Typing with Weird Keyboards Notes Typing with Weird Keyords Notes Ykov Berchenko-Kogn August 25, 2012 Astrct Consider lnguge with n lphet consisting of just four letters,,,, nd. There is spelling rule tht sys tht whenever you see n next

More information

Lecture 7: Integration Techniques

Lecture 7: Integration Techniques Lecture 7: Integrtion Techniques Antiderivtives nd Indefinite Integrls. In differentil clculus, we were interested in the derivtive of given rel-vlued function, whether it ws lgeric, eponentil or logrithmic.

More information

Mathematics Background

Mathematics Background For more roust techer experience, plese visit Techer Plce t mthdshord.com/cmp3 Mthemtics Bckground Extending Understnding of Two-Dimensionl Geometry In Grde 6, re nd perimeter were introduced to develop

More information

ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών. Lecture 3b Lexical Analysis Elias Athanasopoulos

ΕΠΛ323 - Θεωρία και Πρακτική Μεταγλωττιστών. Lecture 3b Lexical Analysis Elias Athanasopoulos ΕΠΛ323 - Θωρία και Πρακτική Μταγλωττιστών Lecture 3 Lexicl Anlysis Elis Athnsopoulos elisthn@cs.ucy.c.cy RecogniNon of Tokens if expressions nd relnonl opertors if è if then è then else è else relop è

More information

Properties of Tree Convex Constraints 1,2

Properties of Tree Convex Constraints 1,2 Properties of Tree Convex Constrints 1,2 Yunlin Zhng, Eugene C Freuder b Deprtment of Computer Science, Texs Tech University, Lubbock, USA b Cork Constrint Computtion Center, University College Cork, Irelnd

More information

Intersection Graphs of L-Shapes and Segments in the Plane

Intersection Graphs of L-Shapes and Segments in the Plane Intersection Grphs of -Shpes nd Segments in the Plne Stefn Felsner 1, Kolj Knuer 2, George B. Mertzios 3, nd Torsten Ueckerdt 4 1 Institut für Mthemtik, Technische Universität Berlin, Germny. 2 IRMM, Université

More information

Guide for sending an Electronic Dental referral

Guide for sending an Electronic Dental referral Guide for sending n Electronic Dentl referrl 1. Lunch Rego vi your Ptient Record System Open the Rego referrl templte vi your Ptient Record System: Exct / SOE: Open the ptient record, then click on Ptient

More information

Class-XI Mathematics Conic Sections Chapter-11 Chapter Notes Key Concepts

Class-XI Mathematics Conic Sections Chapter-11 Chapter Notes Key Concepts Clss-XI Mthemtics Conic Sections Chpter-11 Chpter Notes Key Concepts 1. Let be fixed verticl line nd m be nother line intersecting it t fixed point V nd inclined to it t nd ngle On rotting the line m round

More information

Engineer To Engineer Note

Engineer To Engineer Note Engineer To Engineer Note EE-186 Technicl Notes on using Anlog Devices' DSP components nd development tools Contct our technicl support by phone: (800) ANALOG-D or e-mil: dsp.support@nlog.com Or visit

More information

Graphs with at most two trees in a forest building process

Graphs with at most two trees in a forest building process Grphs with t most two trees in forest uilding process rxiv:802.0533v [mth.co] 4 Fe 208 Steve Butler Mis Hmnk Mrie Hrdt Astrct Given grph, we cn form spnning forest y first sorting the edges in some order,

More information

Digital Design. Chapter 6: Optimizations and Tradeoffs

Digital Design. Chapter 6: Optimizations and Tradeoffs Digitl Design Chpter 6: Optimiztions nd Trdeoffs Slides to ccompny the tetbook Digitl Design, with RTL Design, VHDL, nd Verilog, 2nd Edition, by Frnk Vhid, John Wiley nd Sons Publishers, 2. http://www.ddvhid.com

More information

Lecture Overview. Knowledge-based systems in Bioinformatics, 1MB602. Procedural abstraction. The sum procedure. Integration as a procedure

Lecture Overview. Knowledge-based systems in Bioinformatics, 1MB602. Procedural abstraction. The sum procedure. Integration as a procedure Lecture Overview Knowledge-bsed systems in Bioinformtics, MB6 Scheme lecture Procedurl bstrction Higher order procedures Procedures s rguments Procedures s returned vlues Locl vribles Dt bstrction Compound

More information

CS143 Handout 07 Summer 2011 June 24 th, 2011 Written Set 1: Lexical Analysis

CS143 Handout 07 Summer 2011 June 24 th, 2011 Written Set 1: Lexical Analysis CS143 Hndout 07 Summer 2011 June 24 th, 2011 Written Set 1: Lexicl Anlysis In this first written ssignment, you'll get the chnce to ply round with the vrious constructions tht come up when doing lexicl

More information

Digital Design. Chapter 1: Introduction. Digital Design. Copyright 2006 Frank Vahid

Digital Design. Chapter 1: Introduction. Digital Design. Copyright 2006 Frank Vahid Chpter : Introduction Copyright 6 Why Study?. Look under the hood of computers Solid understnding --> confidence, insight, even better progrmmer when wre of hrdwre resource issues Electronic devices becoming

More information

MENSURATION-IV

MENSURATION-IV MENSURATION-IV Theory: A solid is figure bounded by one or more surfce. Hence solid hs length, bredth nd height. The plne surfces tht bind solid re clled its fces. The fundmentl difference between plne

More information

How to Design REST API? Written Date : March 23, 2015

How to Design REST API? Written Date : March 23, 2015 Visul Prdigm How Design REST API? Turil How Design REST API? Written Dte : Mrch 23, 2015 REpresenttionl Stte Trnsfer, n rchitecturl style tht cn be used in building networked pplictions, is becoming incresingly

More information

3.5.1 Single slit diffraction

3.5.1 Single slit diffraction 3..1 Single slit diffrction ves pssing through single slit will lso diffrct nd produce n interference pttern. The reson for this is to do with the finite width of the slit. e will consider this lter. Tke

More information

Basic Geometry and Topology

Basic Geometry and Topology Bsic Geometry nd Topology Stephn Stolz Septemer 7, 2015 Contents 1 Pointset Topology 1 1.1 Metric spces................................... 1 1.2 Topologicl spces................................ 5 1.3 Constructions

More information

CSCI 104. Rafael Ferreira da Silva. Slides adapted from: Mark Redekopp and David Kempe

CSCI 104. Rafael Ferreira da Silva. Slides adapted from: Mark Redekopp and David Kempe CSCI 0 fel Ferreir d Silv rfsilv@isi.edu Slides dpted from: Mrk edekopp nd Dvid Kempe LOG STUCTUED MEGE TEES Series Summtion eview Let n = + + + + k $ = #%& #. Wht is n? n = k+ - Wht is log () + log ()

More information

Mid-term exam. Scores. Fall term 2012 KAIST EE209 Programming Structures for EE. Thursday Oct 25, Student's name: Student ID:

Mid-term exam. Scores. Fall term 2012 KAIST EE209 Programming Structures for EE. Thursday Oct 25, Student's name: Student ID: Fll term 2012 KAIST EE209 Progrmming Structures for EE Mid-term exm Thursdy Oct 25, 2012 Student's nme: Student ID: The exm is closed book nd notes. Red the questions crefully nd focus your nswers on wht

More information

Ma/CS 6b Class 1: Graph Recap

Ma/CS 6b Class 1: Graph Recap M/CS 6 Clss 1: Grph Recp By Adm Sheffer Course Detils Instructor: Adm Sheffer. TA: Cosmin Pohot. 1pm Mondys, Wednesdys, nd Fridys. http://mth.cltech.edu/~2015-16/2term/m006/ Min ook: Introduction to Grph

More information

Grade 7/8 Math Circles Geometric Arithmetic October 31, 2012

Grade 7/8 Math Circles Geometric Arithmetic October 31, 2012 Fculty of Mthemtics Wterloo, Ontrio N2L 3G1 Grde 7/8 Mth Circles Geometric Arithmetic Octoer 31, 2012 Centre for Eduction in Mthemtics nd Computing Ancient Greece hs given irth to some of the most importnt

More information

UNIVERSITY OF EDINBURGH COLLEGE OF SCIENCE AND ENGINEERING SCHOOL OF INFORMATICS INFORMATICS 1 COMPUTATION & LOGIC INSTRUCTIONS TO CANDIDATES

UNIVERSITY OF EDINBURGH COLLEGE OF SCIENCE AND ENGINEERING SCHOOL OF INFORMATICS INFORMATICS 1 COMPUTATION & LOGIC INSTRUCTIONS TO CANDIDATES UNIVERSITY OF EDINBURGH COLLEGE OF SCIENCE AND ENGINEERING SCHOOL OF INFORMATICS INFORMATICS COMPUTATION & LOGIC Sturdy st April 7 : to : INSTRUCTIONS TO CANDIDATES This is tke-home exercise. It will not

More information

arxiv: v1 [cs.cg] 9 Dec 2016

arxiv: v1 [cs.cg] 9 Dec 2016 Some Counterexmples for Comptible Tringultions rxiv:62.0486v [cs.cg] 9 Dec 206 Cody Brnson Dwn Chndler 2 Qio Chen 3 Christin Chung 4 Andrew Coccimiglio 5 Sen L 6 Lily Li 7 Aïn Linn 8 Ann Lubiw 9 Clre Lyle

More information

Algorithms for embedded graphs

Algorithms for embedded graphs Algorithms for embedded grphs Éric Colin de Verdière October 4, 2017 ALGORITHMS FOR EMBEDDED GRAPHS Foreword nd introduction Foreword This document is the overlpping union of some course notes tht the

More information

Slides for Data Mining by I. H. Witten and E. Frank

Slides for Data Mining by I. H. Witten and E. Frank Slides for Dt Mining y I. H. Witten nd E. Frnk Simplicity first Simple lgorithms often work very well! There re mny kinds of simple structure, eg: One ttriute does ll the work All ttriutes contriute eqully

More information

A Tautology Checker loosely related to Stålmarck s Algorithm by Martin Richards

A Tautology Checker loosely related to Stålmarck s Algorithm by Martin Richards A Tutology Checker loosely relted to Stålmrck s Algorithm y Mrtin Richrds mr@cl.cm.c.uk http://www.cl.cm.c.uk/users/mr/ University Computer Lortory New Museum Site Pemroke Street Cmridge, CB2 3QG Mrtin

More information

This notebook investigates the properties of non-integer differential operators using Fourier analysis.

This notebook investigates the properties of non-integer differential operators using Fourier analysis. Frctionl erivtives.nb Frctionl erivtives by Fourier ecomposition by Eric Thrne 4/9/6 This notebook investigtes the properties of non-integer differentil opertors using Fourier nlysis. In[]:=

More information