Growth Series for Rooted Trees Katholieke Universiteit Leuven 2 June 2014
|
|
- Samson Henderson
- 7 years ago
- Views:
Transcription
1 Growth Series for Rooted Trees Katholieke Universiteit Leuven 2 June 2014 recent research results by Ian Dalton and Eric Freden
2 Motivation 1: Growth series for groups are usually computed by finding normal forms (geodesic words) and counting them. Such normal forms can represent a spanning tree in the Cayley graph. Thus the growth series of the group is the growth series of a rooted tree, with all edges having weight 1, and vertex valences usually variable (but uniformly bounded). The figure shows such a partial spanning tree for Z Z.
3 Partial abstract spanning tree for Baumslag-Solitar BS(1,3) (not embedded in Cayley graph) showing color coded cone types
4 Motivation 2: The asymptotic growth rate ω for any Baumslag-Solitar group can be found by computing the growth series of the corresponding Bass-Serre tree. This tree has constant valence and non-constant (but uniformly bounded) edge weights that correspond to edge projections from Cayley graph to tree. Below is such a tree for BS(1,3). It has 3 cone types and ω=2 (exercise).
5 The tree for BS(2,4) has a much more complicated weighting scheme, with infinitely many cone types. Every cone contains a copy of every other cone. Our algorithm for assigning edge weights to this tree requires exponential space (essentially storing a weight scheme for each cone type). The computation of the growth series appears to rely on the edge weight schema.
6 Motivation 3: As an administrator in a small undergraduate university, I have limited time for research. My colleagues tend to be students who have not yet learned anything about cohomology, measure theory, representation theory, hyperbolic groups and non-positive curvature, varieties, etc. They have learned combinatorics, basic group theory, theory of computation, algorithm design, and some complex analysis.
7 Define a valence scheme as an algorithm that builds a rooted tree by recursively assigning leaf nodes/edges to existing leaves. For example, the standard valence scheme for a binary tree assigns two new leaves to each existing leaf. Define a weight scheme as an algorithm that recursively assigns edge weights to an already existing rooted tree. For example, our complicated algorithm for BS(2,4) assigns edge weights to a regular 5-ary tree (OK, the root has 6 children ). The growth series for a rooted tree is the generating function T (z)= r 0 τ r z r where τ r counts the nodes at weighted distance r from the root.
8 All the trees that we are interested in are infinite (indeed, have exponential growth) thus the full application of a valence scheme, weight scheme, or growth series will require infinite time. Define a valence, weight, or growth algorithm as Wilfian if its application to height h [or radius r] takes at most poly(h) [or poly(r)] many computational steps where poly(x) is a polynomial that depends on the specific instance. Some Wilfian examples include: a valence scheme for the regular rooted n-ary tree a weight scheme for the BS(1,3) Bass-Serre tree a valence/weight scheme for a tree with finitely many cone types the Taylor series for any D-finite function the Taylor series for the secant function
9 Every valence/weight scheme determines a unique growth series. What is the computational relationship here? Folklore: If a valence/weight scheme is Wilfian, so is the associated growth series. The idea is that nodes/edges must be partitioned into polynomially many equivalence classes upon which valences/weights are uniform. Show that these classes can be easily counted and correlated with radius. What about a converse? Given a Wilfian growth series is there a Wilfian valence and/or weight scheme for an associated rooted tree? Obviously, the series must have positive integer coefficients, be increasing, have 1 as constant coefficient, etc.
10 All edges have weight 1 These trees both have growth series 1+z+z 2 +4z 3 +4z 4 +4z 5 +16z 6 +16z There are many non-isomorphic trees with the same growth series.
11 An admissible growth series is trivially associated to a variable valence tree with constant edge weight 1 as per the previous slide, so If an admissible growth series is Wilfian, there exists an associated tree with valence/root scheme that is Wilfian. Open question: given an admissible Wilfian growth series is every associated valence/weight scheme on a rooted tree (equivalent to one that is) Wilfian? We have some partial results...
12 Proposition: Suppose T is a rooted tree with a finite set of edge weights {w 1, w 2,., w n } and finite set of vertex valences {v 1, v 2,.,v m }. Suppose that edge weights and vertex valences are constant on each height. Then the valence/weight scheme is Wilfian if and only if the growth series is Wilfian. Proof: ( ) In this situation, the r th nonzero growth series term is v 1 v 2 v r z w 1+w 2 + +w r where v i (respectively, w i ) is the vertex valence (respectively edge weight) at height i, for 1 i r. Formally divide by the (r-1) st term to recover v r and w r. This is accomplished in polynomial time by hypothesis. ( ) Is the folklore result mentioned earlier.
13 Unfortunately, constant valence and weight along heights is a strong assumption that rarely occurs. Rephrase: Given an admissible Wilfian growth series is every associated valence/weight scheme on a rooted tree Wilfian? as Can a computationally nice growth series have a computationally ugly tree? We address the latter question by a series of examples.
14 Perhaps a cleverly constructed non-wilfian weight scheme can produce a Wilfian growth series? Consider this basic example: The right side edges have weight sequence w 1, w 2, w 3, w 4,. All left trending edges are weighted 1. Color scheme shows self-similarity. There are infinitely many cone types, each containing every other.
15 Let R(z)=z w 1 + z w 1 + w 2+z w 1 + w 2 + w 3+ be the OGF for the 1+ R(z) variably weighted side.then T (z)= 1 zr( z).
16 Let R(z)=z w 1 + z w 1 + w 2+z w 1 + w 2 + w 3+ be the OGF for the 1+ R(z) variably weighted side.then T (z)= 1 zr( z). This leads to the same situation as the special case Proposition. If T(z) is Wilfian, so is R(z), and the weights are easily recoverable. The rational form for T(z) insinuates the self-similarity of cones, etc. Subexamples include: w k =1 for all k (standard binary tree) w k =1+k th bit in the binary expansion of any non-computable real number (R, hence T, is not computable) w k =2 if k is a triangular number, else 1 (R is lacunary, so T is Wilfian but not D-finite)
17 Eye Candy! Julia-type set for the sub example lacunary R(z) showing the structure of singularities on the unit circle.
18 How about starting with a rational growth series and trying to create an ugly weight scheme? Can we jam T(z) = 1/(1-2z) onto a regular ternary tree using edge weights 1 and 2? The root has the vertex at distance 0. We need two vertices at distance 1,
19 How about starting with a rational grow series and trying to create an ugly weight scheme? Can we jam T(z) = 1/(1-2z) onto a regular ternary tree using edge weights 1 and 2? The root has the vertex at distance 0. We need two vertices at distance 1, and four more at distance 2,
20 How about starting with a rational grow series and trying to create an ugly weight scheme? Can we jam T(z) = 1/(1-2z) onto a regular ternary tree using edge weights 1 and 2? The root has the vertex at distance 0. We need two vertices at distance 1, and four more at distance 2, and eight more at distance 3,
21 How about starting with a rational grow series and trying to create an ugly weight scheme? Can we jam T(z) = 1/(1-2z) onto a regular ternary tree using edge weights 1 and 2? The root has the vertex at distance 0. We need two vertices at distance 1, and four more at distance 2, and eight more at distance 3, and sixteen more at distance 4,...
22 This left-to-right deterministic weight scheme (the Dalton algorithm) can be continued indefinitely, produces infinitely many different cone types, and appears to require exponential time. However, it runs in linear time and space (in terms of weighted distance d) assuming that the growth coefficients are read from file and the tree is ternary. The Dalton algorithm can be applied to other growth series, in particular the transcendental Taylor series whose n th coefficient is floor(exp(n)). This has exponent ω = e.
23 Storage table for Dalton algorithm applied to tree growing like e
24 Does the Dalton algorithm work for the BS(2,4) tree? Given the first 36 growth series terms, weight set {1,2,3}, and a 5-ary tree, does the algorithm reconstruct the tree weightings correctly? No! Even with the addition of a finite set of initial conditions, non-deterministic choices are eventually required in order to create (an isomorphic copy of) the correct subtree of radius r. Making these choices deterministic appears to require using the original (exponential time/space) weight scheme! We conclude with some conjectures.
25 Conjecture: both the growth series and weight scheme for the BS(2,4) tree is non-wilfian. Conjecture: the same is true for BS(p,q) when 1<p<q. Conjecture: if there is no Wilfian method to produce a particular weight scheme for a rooted tree, then the induced growth series is not Wilfian. The ternary tree with constant weight 1 has ω=3. With constant weight 2, it grows as ω= 3. Conjecture Lemma: the Dalton algorithm can be applied to a ternary tree to get any exponential growth rate between 3 and 3.
26 Thank You! (especially the organizers)
GRAPH THEORY LECTURE 4: TREES
GRAPH THEORY LECTURE 4: TREES Abstract. 3.1 presents some standard characterizations and properties of trees. 3.2 presents several different types of trees. 3.7 develops a counting method based on a bijection
More informationFull and Complete Binary Trees
Full and Complete Binary Trees Binary Tree Theorems 1 Here are two important types of binary trees. Note that the definitions, while similar, are logically independent. Definition: a binary tree T is full
More informationExponential time algorithms for graph coloring
Exponential time algorithms for graph coloring Uriel Feige Lecture notes, March 14, 2011 1 Introduction Let [n] denote the set {1,..., k}. A k-labeling of vertices of a graph G(V, E) is a function V [k].
More information1. Nondeterministically guess a solution (called a certificate) 2. Check whether the solution solves the problem (called verification)
Some N P problems Computer scientists have studied many N P problems, that is, problems that can be solved nondeterministically in polynomial time. Traditionally complexity question are studied as languages:
More informationFactoring & Primality
Factoring & Primality Lecturer: Dimitris Papadopoulos In this lecture we will discuss the problem of integer factorization and primality testing, two problems that have been the focus of a great amount
More informationLecture 1: Course overview, circuits, and formulas
Lecture 1: Course overview, circuits, and formulas Topics in Complexity Theory and Pseudorandomness (Spring 2013) Rutgers University Swastik Kopparty Scribes: John Kim, Ben Lund 1 Course Information Swastik
More informationBinary Number System. 16. Binary Numbers. Base 10 digits: 0 1 2 3 4 5 6 7 8 9. Base 2 digits: 0 1
Binary Number System 1 Base 10 digits: 0 1 2 3 4 5 6 7 8 9 Base 2 digits: 0 1 Recall that in base 10, the digits of a number are just coefficients of powers of the base (10): 417 = 4 * 10 2 + 1 * 10 1
More informationMath 181 Handout 16. Rich Schwartz. March 9, 2010
Math 8 Handout 6 Rich Schwartz March 9, 200 The purpose of this handout is to describe continued fractions and their connection to hyperbolic geometry. The Gauss Map Given any x (0, ) we define γ(x) =
More informationThe Prime Numbers. Definition. A prime number is a positive integer with exactly two positive divisors.
The Prime Numbers Before starting our study of primes, we record the following important lemma. Recall that integers a, b are said to be relatively prime if gcd(a, b) = 1. Lemma (Euclid s Lemma). If gcd(a,
More information1 if 1 x 0 1 if 0 x 1
Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or
More informationGraphs without proper subgraphs of minimum degree 3 and short cycles
Graphs without proper subgraphs of minimum degree 3 and short cycles Lothar Narins, Alexey Pokrovskiy, Tibor Szabó Department of Mathematics, Freie Universität, Berlin, Germany. August 22, 2014 Abstract
More informationMathematics for Algorithm and System Analysis
Mathematics for Algorithm and System Analysis for students of computer and computational science Edward A. Bender S. Gill Williamson c Edward A. Bender & S. Gill Williamson 2005. All rights reserved. Preface
More informationDetermination of the normalization level of database schemas through equivalence classes of attributes
Computer Science Journal of Moldova, vol.17, no.2(50), 2009 Determination of the normalization level of database schemas through equivalence classes of attributes Cotelea Vitalie Abstract In this paper,
More informationInformation Theory and Coding Prof. S. N. Merchant Department of Electrical Engineering Indian Institute of Technology, Bombay
Information Theory and Coding Prof. S. N. Merchant Department of Electrical Engineering Indian Institute of Technology, Bombay Lecture - 17 Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding
More informationit is easy to see that α = a
21. Polynomial rings Let us now turn out attention to determining the prime elements of a polynomial ring, where the coefficient ring is a field. We already know that such a polynomial ring is a UF. Therefore
More informationDiscuss the size of the instance for the minimum spanning tree problem.
3.1 Algorithm complexity The algorithms A, B are given. The former has complexity O(n 2 ), the latter O(2 n ), where n is the size of the instance. Let n A 0 be the size of the largest instance that can
More informationTree-representation of set families and applications to combinatorial decompositions
Tree-representation of set families and applications to combinatorial decompositions Binh-Minh Bui-Xuan a, Michel Habib b Michaël Rao c a Department of Informatics, University of Bergen, Norway. buixuan@ii.uib.no
More informationLecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs
CSE599s: Extremal Combinatorics November 21, 2011 Lecture 15 An Arithmetic Circuit Lowerbound and Flows in Graphs Lecturer: Anup Rao 1 An Arithmetic Circuit Lower Bound An arithmetic circuit is just like
More informationU.C. Berkeley CS276: Cryptography Handout 0.1 Luca Trevisan January, 2009. Notes on Algebra
U.C. Berkeley CS276: Cryptography Handout 0.1 Luca Trevisan January, 2009 Notes on Algebra These notes contain as little theory as possible, and most results are stated without proof. Any introductory
More informationA Turán Type Problem Concerning the Powers of the Degrees of a Graph
A Turán Type Problem Concerning the Powers of the Degrees of a Graph Yair Caro and Raphael Yuster Department of Mathematics University of Haifa-ORANIM, Tivon 36006, Israel. AMS Subject Classification:
More information3. Linear Programming and Polyhedral Combinatorics
Massachusetts Institute of Technology Handout 6 18.433: Combinatorial Optimization February 20th, 2009 Michel X. Goemans 3. Linear Programming and Polyhedral Combinatorics Summary of what was seen in the
More informationEuclidean Minimum Spanning Trees Based on Well Separated Pair Decompositions Chaojun Li. Advised by: Dave Mount. May 22, 2014
Euclidean Minimum Spanning Trees Based on Well Separated Pair Decompositions Chaojun Li Advised by: Dave Mount May 22, 2014 1 INTRODUCTION In this report we consider the implementation of an efficient
More informationLecture 13 - Basic Number Theory.
Lecture 13 - Basic Number Theory. Boaz Barak March 22, 2010 Divisibility and primes Unless mentioned otherwise throughout this lecture all numbers are non-negative integers. We say that A divides B, denoted
More informationPrime Numbers and Irreducible Polynomials
Prime Numbers and Irreducible Polynomials M. Ram Murty The similarity between prime numbers and irreducible polynomials has been a dominant theme in the development of number theory and algebraic geometry.
More informationComputer Algorithms. NP-Complete Problems. CISC 4080 Yanjun Li
Computer Algorithms NP-Complete Problems NP-completeness The quest for efficient algorithms is about finding clever ways to bypass the process of exhaustive search, using clues from the input in order
More informationHow To Solve A K Path In Time (K)
What s next? Reductions other than kernelization Dániel Marx Humboldt-Universität zu Berlin (with help from Fedor Fomin, Daniel Lokshtanov and Saket Saurabh) WorKer 2010: Workshop on Kernelization Nov
More informationContinued Fractions and the Euclidean Algorithm
Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction
More informationData Structures. Chapter 8
Chapter 8 Data Structures Computer has to process lots and lots of data. To systematically process those data efficiently, those data are organized as a whole, appropriate for the application, called a
More informationGENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY
GENERIC COMPUTABILITY, TURING DEGREES, AND ASYMPTOTIC DENSITY CARL G. JOCKUSCH, JR. AND PAUL E. SCHUPP Abstract. Generic decidability has been extensively studied in group theory, and we now study it in
More informationEfficient Recovery of Secrets
Efficient Recovery of Secrets Marcel Fernandez Miguel Soriano, IEEE Senior Member Department of Telematics Engineering. Universitat Politècnica de Catalunya. C/ Jordi Girona 1 i 3. Campus Nord, Mod C3,
More informationA Non-Linear Schema Theorem for Genetic Algorithms
A Non-Linear Schema Theorem for Genetic Algorithms William A Greene Computer Science Department University of New Orleans New Orleans, LA 70148 bill@csunoedu 504-280-6755 Abstract We generalize Holland
More information2. (a) Explain the strassen s matrix multiplication. (b) Write deletion algorithm, of Binary search tree. [8+8]
Code No: R05220502 Set No. 1 1. (a) Describe the performance analysis in detail. (b) Show that f 1 (n)+f 2 (n) = 0(max(g 1 (n), g 2 (n)) where f 1 (n) = 0(g 1 (n)) and f 2 (n) = 0(g 2 (n)). [8+8] 2. (a)
More information11 Ideals. 11.1 Revisiting Z
11 Ideals The presentation here is somewhat different than the text. In particular, the sections do not match up. We have seen issues with the failure of unique factorization already, e.g., Z[ 5] = O Q(
More informationPrimality - Factorization
Primality - Factorization Christophe Ritzenthaler November 9, 2009 1 Prime and factorization Definition 1.1. An integer p > 1 is called a prime number (nombre premier) if it has only 1 and p as divisors.
More informationCMPSCI611: Approximating MAX-CUT Lecture 20
CMPSCI611: Approximating MAX-CUT Lecture 20 For the next two lectures we ll be seeing examples of approximation algorithms for interesting NP-hard problems. Today we consider MAX-CUT, which we proved to
More informationConnectivity and cuts
Math 104, Graph Theory February 19, 2013 Measure of connectivity How connected are each of these graphs? > increasing connectivity > I G 1 is a tree, so it is a connected graph w/minimum # of edges. Every
More informationCONTINUED FRACTIONS AND PELL S EQUATION. Contents 1. Continued Fractions 1 2. Solution to Pell s Equation 9 References 12
CONTINUED FRACTIONS AND PELL S EQUATION SEUNG HYUN YANG Abstract. In this REU paper, I will use some important characteristics of continued fractions to give the complete set of solutions to Pell s equation.
More informationCOMP 250 Fall 2012 lecture 2 binary representations Sept. 11, 2012
Binary numbers The reason humans represent numbers using decimal (the ten digits from 0,1,... 9) is that we have ten fingers. There is no other reason than that. There is nothing special otherwise about
More informationThe Goldberg Rao Algorithm for the Maximum Flow Problem
The Goldberg Rao Algorithm for the Maximum Flow Problem COS 528 class notes October 18, 2006 Scribe: Dávid Papp Main idea: use of the blocking flow paradigm to achieve essentially O(min{m 2/3, n 1/2 }
More informationSchemes for Deterministic Polynomial Factoring
Schemes for Deterministic Polynomial Factoring Gábor Ivanyos 1 Marek Karpinski 2 Nitin Saxena 3 1 Computer and Automation Research Institute, Budapest 2 Dept. of Computer Science, University of Bonn 3
More informationA NOTE ON OFF-DIAGONAL SMALL ON-LINE RAMSEY NUMBERS FOR PATHS
A NOTE ON OFF-DIAGONAL SMALL ON-LINE RAMSEY NUMBERS FOR PATHS PAWE L PRA LAT Abstract. In this note we consider the on-line Ramsey numbers R(P n, P m ) for paths. Using a high performance computing clusters,
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete
More informationMathematical Induction. Lecture 10-11
Mathematical Induction Lecture 10-11 Menu Mathematical Induction Strong Induction Recursive Definitions Structural Induction Climbing an Infinite Ladder Suppose we have an infinite ladder: 1. We can reach
More informationData Structure [Question Bank]
Unit I (Analysis of Algorithms) 1. What are algorithms and how they are useful? 2. Describe the factor on best algorithms depends on? 3. Differentiate: Correct & Incorrect Algorithms? 4. Write short note:
More informationCatalan Numbers. Thomas A. Dowling, Department of Mathematics, Ohio State Uni- versity.
7 Catalan Numbers Thomas A. Dowling, Department of Mathematics, Ohio State Uni- Author: versity. Prerequisites: The prerequisites for this chapter are recursive definitions, basic counting principles,
More informationarxiv:cs/0605141v1 [cs.dc] 30 May 2006
General Compact Labeling Schemes for Dynamic Trees Amos Korman arxiv:cs/0605141v1 [cs.dc] 30 May 2006 February 1, 2008 Abstract Let F be a function on pairs of vertices. An F- labeling scheme is composed
More informationGraph Theory Problems and Solutions
raph Theory Problems and Solutions Tom Davis tomrdavis@earthlink.net http://www.geometer.org/mathcircles November, 005 Problems. Prove that the sum of the degrees of the vertices of any finite graph is
More informationINDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS
INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS STEVEN P. LALLEY AND ANDREW NOBEL Abstract. It is shown that there are no consistent decision rules for the hypothesis testing problem
More informationLecture 17 : Equivalence and Order Relations DRAFT
CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion
More informationCAD Algorithms. P and NP
CAD Algorithms The Classes P and NP Mohammad Tehranipoor ECE Department 6 September 2010 1 P and NP P and NP are two families of problems. P is a class which contains all of the problems we solve using
More informationAn algorithmic classification of open surfaces
An algorithmic classification of open surfaces Sylvain Maillot January 8, 2013 Abstract We propose a formulation for the homeomorphism problem for open n-dimensional manifolds and use the Kerekjarto classification
More informationCycles and clique-minors in expanders
Cycles and clique-minors in expanders Benny Sudakov UCLA and Princeton University Expanders Definition: The vertex boundary of a subset X of a graph G: X = { all vertices in G\X with at least one neighbor
More informationStanford Math Circle: Sunday, May 9, 2010 Square-Triangular Numbers, Pell s Equation, and Continued Fractions
Stanford Math Circle: Sunday, May 9, 00 Square-Triangular Numbers, Pell s Equation, and Continued Fractions Recall that triangular numbers are numbers of the form T m = numbers that can be arranged in
More informationCycles in a Graph Whose Lengths Differ by One or Two
Cycles in a Graph Whose Lengths Differ by One or Two J. A. Bondy 1 and A. Vince 2 1 LABORATOIRE DE MATHÉMATIQUES DISCRÉTES UNIVERSITÉ CLAUDE-BERNARD LYON 1 69622 VILLEURBANNE, FRANCE 2 DEPARTMENT OF MATHEMATICS
More informationON INDUCED SUBGRAPHS WITH ALL DEGREES ODD. 1. Introduction
ON INDUCED SUBGRAPHS WITH ALL DEGREES ODD A.D. SCOTT Abstract. Gallai proved that the vertex set of any graph can be partitioned into two sets, each inducing a subgraph with all degrees even. We prove
More informationAlgebra 2 Chapter 1 Vocabulary. identity - A statement that equates two equivalent expressions.
Chapter 1 Vocabulary identity - A statement that equates two equivalent expressions. verbal model- A word equation that represents a real-life problem. algebraic expression - An expression with variables.
More informationInfluences in low-degree polynomials
Influences in low-degree polynomials Artūrs Bačkurs December 12, 2012 1 Introduction In 3] it is conjectured that every bounded real polynomial has a highly influential variable The conjecture is known
More informationarxiv:1112.0829v1 [math.pr] 5 Dec 2011
How Not to Win a Million Dollars: A Counterexample to a Conjecture of L. Breiman Thomas P. Hayes arxiv:1112.0829v1 [math.pr] 5 Dec 2011 Abstract Consider a gambling game in which we are allowed to repeatedly
More informationDegree distribution of random Apollonian network structures and Boltzmann sampling
Discrete Mathematics and Theoretical Computer Science (subm.), by the authors, 2 rev Degree distribution of random Apollonian network structures and Boltzmann sampling Alexis Darrasse and Michèle Soria
More informationGenerating models of a matched formula with a polynomial delay
Generating models of a matched formula with a polynomial delay Petr Savicky Institute of Computer Science, Academy of Sciences of Czech Republic, Pod Vodárenskou Věží 2, 182 07 Praha 8, Czech Republic
More informationHOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!
Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following
More informationEvery tree contains a large induced subgraph with all degrees odd
Every tree contains a large induced subgraph with all degrees odd A.J. Radcliffe Carnegie Mellon University, Pittsburgh, PA A.D. Scott Department of Pure Mathematics and Mathematical Statistics University
More informationMaster of Arts in Mathematics
Master of Arts in Mathematics Administrative Unit The program is administered by the Office of Graduate Studies and Research through the Faculty of Mathematics and Mathematics Education, Department of
More informationSecond Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.
Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard
More informationAnalysis of Algorithms, I
Analysis of Algorithms, I CSOR W4231.002 Eleni Drinea Computer Science Department Columbia University Thursday, February 26, 2015 Outline 1 Recap 2 Representing graphs 3 Breadth-first search (BFS) 4 Applications
More informationCompetitive Analysis of On line Randomized Call Control in Cellular Networks
Competitive Analysis of On line Randomized Call Control in Cellular Networks Ioannis Caragiannis Christos Kaklamanis Evi Papaioannou Abstract In this paper we address an important communication issue arising
More informationCOMBINATORIAL PROPERTIES OF THE HIGMAN-SIMS GRAPH. 1. Introduction
COMBINATORIAL PROPERTIES OF THE HIGMAN-SIMS GRAPH ZACHARY ABEL 1. Introduction In this survey we discuss properties of the Higman-Sims graph, which has 100 vertices, 1100 edges, and is 22 regular. In fact
More informationReading 13 : Finite State Automata and Regular Expressions
CS/Math 24: Introduction to Discrete Mathematics Fall 25 Reading 3 : Finite State Automata and Regular Expressions Instructors: Beck Hasti, Gautam Prakriya In this reading we study a mathematical model
More informationONLINE DEGREE-BOUNDED STEINER NETWORK DESIGN. Sina Dehghani Saeed Seddighin Ali Shafahi Fall 2015
ONLINE DEGREE-BOUNDED STEINER NETWORK DESIGN Sina Dehghani Saeed Seddighin Ali Shafahi Fall 2015 ONLINE STEINER FOREST PROBLEM An initially given graph G. s 1 s 2 A sequence of demands (s i, t i ) arriving
More informationHow To Prove The Dirichlet Unit Theorem
Chapter 6 The Dirichlet Unit Theorem As usual, we will be working in the ring B of algebraic integers of a number field L. Two factorizations of an element of B are regarded as essentially the same if
More informationCHAPTER 3. Methods of Proofs. 1. Logical Arguments and Formal Proofs
CHAPTER 3 Methods of Proofs 1. Logical Arguments and Formal Proofs 1.1. Basic Terminology. An axiom is a statement that is given to be true. A rule of inference is a logical rule that is used to deduce
More informationSolving Linear Systems, Continued and The Inverse of a Matrix
, Continued and The of a Matrix Calculus III Summer 2013, Session II Monday, July 15, 2013 Agenda 1. The rank of a matrix 2. The inverse of a square matrix Gaussian Gaussian solves a linear system by reducing
More information1 Definitions. Supplementary Material for: Digraphs. Concept graphs
Supplementary Material for: van Rooij, I., Evans, P., Müller, M., Gedge, J. & Wareham, T. (2008). Identifying Sources of Intractability in Cognitive Models: An Illustration using Analogical Structure Mapping.
More informationGROUP ALGEBRAS. ANDREI YAFAEV
GROUP ALGEBRAS. ANDREI YAFAEV We will associate a certain algebra to a finite group and prove that it is semisimple. Then we will apply Wedderburn s theory to its study. Definition 0.1. Let G be a finite
More informationLecture 3: Finding integer solutions to systems of linear equations
Lecture 3: Finding integer solutions to systems of linear equations Algorithmic Number Theory (Fall 2014) Rutgers University Swastik Kopparty Scribe: Abhishek Bhrushundi 1 Overview The goal of this lecture
More informationComplexity Theory. IE 661: Scheduling Theory Fall 2003 Satyaki Ghosh Dastidar
Complexity Theory IE 661: Scheduling Theory Fall 2003 Satyaki Ghosh Dastidar Outline Goals Computation of Problems Concepts and Definitions Complexity Classes and Problems Polynomial Time Reductions Examples
More informationEfficiency of algorithms. Algorithms. Efficiency of algorithms. Binary search and linear search. Best, worst and average case.
Algorithms Efficiency of algorithms Computational resources: time and space Best, worst and average case performance How to compare algorithms: machine-independent measure of efficiency Growth rate Complexity
More informationCORRELATED TO THE SOUTH CAROLINA COLLEGE AND CAREER-READY FOUNDATIONS IN ALGEBRA
We Can Early Learning Curriculum PreK Grades 8 12 INSIDE ALGEBRA, GRADES 8 12 CORRELATED TO THE SOUTH CAROLINA COLLEGE AND CAREER-READY FOUNDATIONS IN ALGEBRA April 2016 www.voyagersopris.com Mathematical
More informationLecture 7: NP-Complete Problems
IAS/PCMI Summer Session 2000 Clay Mathematics Undergraduate Program Basic Course on Computational Complexity Lecture 7: NP-Complete Problems David Mix Barrington and Alexis Maciel July 25, 2000 1. Circuit
More informationZero: If P is a polynomial and if c is a number such that P (c) = 0 then c is a zero of P.
MATH 11011 FINDING REAL ZEROS KSU OF A POLYNOMIAL Definitions: Polynomial: is a function of the form P (x) = a n x n + a n 1 x n 1 + + a x + a 1 x + a 0. The numbers a n, a n 1,..., a 1, a 0 are called
More information6.852: Distributed Algorithms Fall, 2009. Class 2
.8: Distributed Algorithms Fall, 009 Class Today s plan Leader election in a synchronous ring: Lower bound for comparison-based algorithms. Basic computation in general synchronous networks: Leader election
More informationIntroduction to Algorithms March 10, 2004 Massachusetts Institute of Technology Professors Erik Demaine and Shafi Goldwasser Quiz 1.
Introduction to Algorithms March 10, 2004 Massachusetts Institute of Technology 6.046J/18.410J Professors Erik Demaine and Shafi Goldwasser Quiz 1 Quiz 1 Do not open this quiz booklet until you are directed
More informationNetwork Algorithms for Homeland Security
Network Algorithms for Homeland Security Mark Goldberg and Malik Magdon-Ismail Rensselaer Polytechnic Institute September 27, 2004. Collaborators J. Baumes, M. Krishmamoorthy, N. Preston, W. Wallace. Partially
More information4. Expanding dynamical systems
4.1. Metric definition. 4. Expanding dynamical systems Definition 4.1. Let X be a compact metric space. A map f : X X is said to be expanding if there exist ɛ > 0 and L > 1 such that d(f(x), f(y)) Ld(x,
More informationSequence of Mathematics Courses
Sequence of ematics Courses Where do I begin? Associates Degree and Non-transferable Courses (For math course below pre-algebra, see the Learning Skills section of the catalog) MATH M09 PRE-ALGEBRA 3 UNITS
More informationDEGREES OF CATEGORICITY AND THE HYPERARITHMETIC HIERARCHY
DEGREES OF CATEGORICITY AND THE HYPERARITHMETIC HIERARCHY BARBARA F. CSIMA, JOHANNA N. Y. FRANKLIN, AND RICHARD A. SHORE Abstract. We study arithmetic and hyperarithmetic degrees of categoricity. We extend
More informationClassification of Cartan matrices
Chapter 7 Classification of Cartan matrices In this chapter we describe a classification of generalised Cartan matrices This classification can be compared as the rough classification of varieties in terms
More informationOn the k-path cover problem for cacti
On the k-path cover problem for cacti Zemin Jin and Xueliang Li Center for Combinatorics and LPMC Nankai University Tianjin 300071, P.R. China zeminjin@eyou.com, x.li@eyou.com Abstract In this paper we
More informationDegree distribution in random Apollonian networks structures
Degree distribution in random Apollonian networks structures Alexis Darrasse joint work with Michèle Soria ALÉA 2007 Plan 1 Introduction 2 Properties of real-life graphs Distinctive properties Existing
More informationEastern Washington University Department of Computer Science. Questionnaire for Prospective Masters in Computer Science Students
Eastern Washington University Department of Computer Science Questionnaire for Prospective Masters in Computer Science Students I. Personal Information Name: Last First M.I. Mailing Address: Permanent
More informationFUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES
FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES CHRISTOPHER HEIL 1. Cosets and the Quotient Space Any vector space is an abelian group under the operation of vector addition. So, if you are have studied
More informationDiscrete Mathematics: Homework 7 solution. Due: 2011.6.03
EE 2060 Discrete Mathematics spring 2011 Discrete Mathematics: Homework 7 solution Due: 2011.6.03 1. Let a n = 2 n + 5 3 n for n = 0, 1, 2,... (a) (2%) Find a 0, a 1, a 2, a 3 and a 4. (b) (2%) Show that
More informationMATHEMATICS: CONCEPTS, AND FOUNDATIONS Vol. III - Logic and Computer Science - Phokion G. Kolaitis
LOGIC AND COMPUTER SCIENCE Phokion G. Kolaitis Computer Science Department, University of California, Santa Cruz, CA 95064, USA Keywords: algorithm, Armstrong s axioms, complete problem, complexity class,
More informationLabeling outerplanar graphs with maximum degree three
Labeling outerplanar graphs with maximum degree three Xiangwen Li 1 and Sanming Zhou 2 1 Department of Mathematics Huazhong Normal University, Wuhan 430079, China 2 Department of Mathematics and Statistics
More informationSeminar. Path planning using Voronoi diagrams and B-Splines. Stefano Martina stefano.martina@stud.unifi.it
Seminar Path planning using Voronoi diagrams and B-Splines Stefano Martina stefano.martina@stud.unifi.it 23 may 2016 This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International
More informationMonogenic Fields and Power Bases Michael Decker 12/07/07
Monogenic Fields and Power Bases Michael Decker 12/07/07 1 Introduction Let K be a number field of degree k and O K its ring of integers Then considering O K as a Z-module, the nicest possible case is
More informationLinear Programming I
Linear Programming I November 30, 2003 1 Introduction In the VCR/guns/nuclear bombs/napkins/star wars/professors/butter/mice problem, the benevolent dictator, Bigus Piguinus, of south Antarctica penguins
More information(a) Write each of p and q as a polynomial in x with coefficients in Z[y, z]. deg(p) = 7 deg(q) = 9
Homework #01, due 1/20/10 = 9.1.2, 9.1.4, 9.1.6, 9.1.8, 9.2.3 Additional problems for study: 9.1.1, 9.1.3, 9.1.5, 9.1.13, 9.2.1, 9.2.2, 9.2.4, 9.2.5, 9.2.6, 9.3.2, 9.3.3 9.1.1 (This problem was not assigned
More informationWhat mathematical optimization can, and cannot, do for biologists. Steven Kelk Department of Knowledge Engineering (DKE) Maastricht University, NL
What mathematical optimization can, and cannot, do for biologists Steven Kelk Department of Knowledge Engineering (DKE) Maastricht University, NL Introduction There is no shortage of literature about the
More informationDiscrete Mathematics & Mathematical Reasoning Chapter 10: Graphs
Discrete Mathematics & Mathematical Reasoning Chapter 10: Graphs Kousha Etessami U. of Edinburgh, UK Kousha Etessami (U. of Edinburgh, UK) Discrete Mathematics (Chapter 6) 1 / 13 Overview Graphs and Graph
More information