Online Linear Discrepancy of Partially Ordered Sets
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UNIVERSITY of CALIFORNIA, IRVINE DISSERTATION Submitted
UNIVERSITY OF CALIFORNIA, IRVINE THREE ESSAYS ON THE FOUNDATIONS OF SCIENCE DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Social Science – Mathematical Behavioral Sciences by Rolf Henry Johansson Dissertation Committee: Professor Louis Narens, Chair Professor Donald Saari Professor Kent Johnson 2014 © 2014 Rolf Henry Johansson DEDICATION For my mother Lalla and my father Kurt for their continuing support. ii TABLE OF CONTENTS Page ACKNOWLEDGEMENTS iv CURRICULUM VITAE v ABTRACT OF THE DISSERTATION viii ESSAY 1: THE UNIQUENESS PROBLEM FOR FINITE SEMIORDERS Abstract 1 1. Introduction 2 2. Preliminaries 8 3. Representation Problems for Semiorders 17 4. Theorems 24 5. Discussion 37 Appendix 40 References 45 ESSAY 2: TROUBLES WITH CONVENTION T Abstract 48 1. Introduction: Convention T and Natural Languages 50 2. Hintikka‟s Counterexample 55 3. Hintikka-Type Counterexamples 59 4. Proposed Solutions 63 4.1 On ambiguity versus context-sensitivity 64 4.2 Formalizing the metalanguage 70 4.3 Paraprasing the conditional 73 4.4 Dispensing with disquotation 76 5. Discussion 78 References 82 ESSAY 3: ELEMENTARY FORMULAS FOR THE nTH PRIME AND FOR THE NUMBER OF PRIMES UP TO A GIVEN LIMIT Abstract 84 1. Introduction 86 2. A Brief History of Prime Representing Functions 89 3. Formulas Based on Wilson‟s Theorem 93 4. Formulas Based on the Sieve of Eratosthenes 96 5. Elementary Formulas for Primes 100 References 107 iii ACKNOWLEDGEMENTS I would like to express my deepest gratitude to my committee chair, Louis Narens, for many stimulating conversations over the years and for guidance throughout my graduate education. -
2/3 Conjecture
PROGRESS ON THE 1=3 − 2=3 CONJECTURE By Emily Jean Olson A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Mathematics | Doctor of Philosophy 2017 ABSTRACT PROGRESS ON THE 1=3 − 2=3 CONJECTURE By Emily Jean Olson Let (P; ≤) be a finite partially ordered set, also called a poset, and let n denote the cardinality of P . Fix a natural labeling on P so that the elements of P correspond to [n] = f1; 2; : : : ; ng. A linear extension is an order-preserving total order x1 ≺ x2 ≺ · · · ≺ xn on the elements of P , and more compactly, we can view this as the permutation x1x2 ··· xn in one-line notation. For distinct elements x; y 2 P , we define P(x ≺ y) to be the proportion 1 of linear extensions of P in which x comes before y. For 0 ≤ α ≤ 2, we say (x; y) is an α-balanced pair if α ≤ P(x ≺ y) ≤ 1 − α: The 1=3 − 2=3 Conjecture states that every finite partially ordered set that is not a chain has a 1=3-balanced pair. This dissertation focuses on showing the conjecture is true for certain types of partially ordered sets. We begin by discussing a special case, namely when a partial order is 1=2-balanced. For example, this happens when the poset has an automorphism with a cycle of length 2. We spend the remainder of the text proving the conjecture is true for some lattices, including Boolean, set partition, and subspace lattices; partial orders that arise from a Young diagram; and some partial orders of dimension 2. -
On Hybric Order Dimensions 1 Introduction
On hybric order dimensions Athanasios Andrikopoulos Abstract The notion of interval order was introduced by Norbert Wiener [28] in order to clarify the relation between the notion of an instant of time and that of a period of time. This was a problem on which Bertrand Russell [18] worked at the time. Interval orders play an impor- tant role in many areas of pure and applied mathematics, graph theory, computer science and engineering. Special cases of interval order are the semiorder and linear order. All of these notions are especially important in the study of linear-interval and linear-semiorder dimension of a binary relation. This kind of dimension, which we call hybric order dimension, gives a common generalization of linear order and interval order (semiorder) dimension and is ar- guably the most important measure of ordered set complexity. In this paper, we give three main results of the theory of hybric order dimension. More precicely, we obtain necessary and sufficient conditions for a binary relation to have an interval order (resp. linear-interval order, linear-simiorder) extension as well as a realizer of interval orders (resp. linear-interval orders, linear-simiorders). We also obtain a characterization of the interval order (resp. linear-interval order, linear-simiorder) dimension. Since the hybric order dimension of a binary relation is less than its (linear) order dimension, these results will be able to improve known results in graph theory and computer science by finding more efficient algorithms. Keywords: Graph, Extension theorems, Linear-interval order, Linear-semiorder, Realizer, Dimension. 1 Introduction Zeno’s paradox posed for first time the question of whether time should be represented by a discrete or a continuous variable. -
Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo
The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) Counting Linear Extensions in Practice: MCMC versus Exponential Monte Carlo Topi Talvitie Kustaa Kangas Teppo Niinimaki¨ Mikko Koivisto Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science Dept. of Computer Science University of Helsinki Aalto University Aalto University University of Helsinki topi.talvitie@helsinki.fi juho-kustaa.kangas@aalto.fi teppo.niinimaki@aalto.fi mikko.koivisto@helsinki.fi Abstract diagram (Kangas et al. 2016), or the treewidth of the incom- parability graph (Eiben et al. 2016). Counting the linear extensions of a given partial order is a If an approximation with given probability is sufficient, #P-complete problem that arises in numerous applications. For polynomial-time approximation, several Markov chain the problem admits a polynomial-time solution for all posets Monte Carlo schemes have been proposed; however, little is using Markov chain Monte Carlo (MCMC) methods. The known of their efficiency in practice. This work presents an first fully-polynomial time approximation scheme of this empirical evaluation of the state-of-the-art schemes and in- kind for was based on algorithms for approximating the vol- vestigates a number of ideas to enhance their performance. In umes of convex bodies (Dyer, Frieze, and Kannan 1991). addition, we introduce a novel approximation scheme, adap- The later improvements were based on rapidly mixing tive relaxation Monte Carlo (ARMC), that leverages exact Markov chains in the set of linear extensions (Karzanov exponential-time counting algorithms. We show that approx- and Khachiyan 1991; Bubley and Dyer 1999) combined imate counting is feasible up to a few hundred elements on with Monte Carlo counting schemes (Brightwell and Win- various classes of partial orders, and within this range ARMC kler 1991; Banks et al. -
The Dimension of Semiorders a Partially Ordered Set Or Poset Is An
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector JOURNAL OF COMBINATORIAL THEORY, Series A25, 5&61 (1978) The Dimension of Semiorders I. RABINOVITCH * Department of Statistics, Uniuersity of Waterloo, Waterfoo, Ontario Communicated by the Managing Editors Received December 26. 1974 The structure of semiorders and interval orders is investigated and various characterizations are given. These ideas are then applied to prove that the dimen- sion of a semiorder is at most 3, to characterize semiorders of dimension 3 and height 2, and to prove Hiraguchi’s Theorem. 1. PRELIMINARIES A partially ordered set or poset is an ordered pair (X, P) where P is an irreflexive, asymmetric, and transitive relation on X. In this paper X will always be a finite set. If Y C X then (Y, P Iy) is called the restriction of (X, P) to Y where P Iy = P n (Y x Y). If P and Q are both partial orders on the same set X with P C Q then Q is called an extension of P and P is called a subrelation of Q. Two elements x and y of X are incomparable if neither (x, I?) E P nor ( y, X) E P. This is written x izr y. An antichain of (X, P) is a subset of pairwise incomparable elements. A chain is a subset with no two elements incomparable. The height of (X, P), written h(P), is one less than the number of elements in a chain of maximum size. -
Counting Linear Extensions of Restricted Posets
COUNTING LINEAR EXTENSIONS OF RESTRICTED POSETS SAMUEL DITTMER? AND IGOR PAK? Abstract. The classical 1991 result by Brightwell and Winkler [BW91] states that the number of linear extensions of a poset is #P-complete. We extend this result to posets with certain restrictions. First, we prove that the number of linear extension for posets of height two is #P-complete. Furthermore, we prove that this holds for incidence posets of graphs. Finally, we prove that the number of linear extensions for posets of dimension two is #P-complete. 1. Introduction Counting linear extensions (#LE) of a finite poset is a fundamental problem in both Combinatorics and Computer Science, with connections and applications ranging from Sta- tistics to Optimization, to Social Choice Theory. It is primarily motivated by the following basic question: given a partial information of preferences between various objects, what are the chances of other comparisons? In 1991, Brightwell and Winkler showed that #LE is #P-complete [BW91], but for var- ious restricted classes of posets the problem remains unresolved. Notably, they conjectured that the following problem is #P-complete: #H2LE (Number of linear extensions of height-2 posets) Input: A partially ordered set P of height 2. Output: The number e(P ) of linear extensions. Here height two means that P has two levels, i.e. no chains of length 3. This problem has been open for 27 years, most recently reiterated in [Hub14, LS17]. Its solution is the first result in this paper. Theorem 1.1. #H2LE is #P-complete. Our second result is an extension of Theorem 1.1. -
Choice, Extension, Conservation. from Transfinite to finite Methods in Abstract Algebra
Choice, extension, conservation. From transfinite to finite methods in abstract algebra Daniel Wessel Universita` degli Studi di Trento Universita` degli Studi di Verona December 3, 2017 Doctoral thesis in Mathematics Joint doctoral programme in Mathematics, 30th cycle Department of Mathematics, University of Trento Department of Computer Science, University of Verona Academic year 2017/18 Supervisor: Peter Schuster, University of Verona Trento, Italy December 3, 2017 Abstract Maximality principles such as the ones going back to Kuratowski and Zorn ensure the existence of higher type ideal objects the use of which is commonly held indispensable for mathematical practice. The modern turn towards computational methods, which can be witnessed to have a strong influence on contemporary foundational studies, encourages a reassessment within a constructive framework of the methodological intricacies that go along with invocations of maximality principles. The common thread that can be followed through the chapters of this thesis is explained by the attempt to put the widespread use of ideal objects under constructive scrutiny. It thus walks the tracks of a revised Hilbert's programme which has inspired a reapproach to constructive algebra by finitary means, and for which Scott's entailment relations have already shown to provide a vital and utmost versatile tool. In this thesis several forms of the Kuratowski-Zorn Lemma are introduced and proved equivalent over constructive set theory; the notion of Jacobson radical is brought from com- mutative -
Counting Linear Extensions of Sparse Posets⇤
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) Counting Linear Extensions of Sparse Posets⇤ Kustaa Kangas Teemu Hankala Teppo Niinimaki¨ Mikko Koivisto University of Helsinki, Department of Computer Science, Helsinki Institute for Information Technology HIIT, Finland jwkangas,tjhankal,tzniinim,mkhkoivi @cs.helsinki.fi { } Abstract sparse, which raises the question if sparsity can be exploited for counting linear extensions faster. We present two algorithms for computing the num- In this work we present two approaches to counting linear ber of linear extensions of a given n-element poset. n extensions that target sparse posets in particular. In Section 2 Our first approach builds upon an O(2 n)-time we augment the dynamic programming algorithm by splitting dynamic programming algorithm by splitting sub- each upset into connected components and then computing problems into connected components and recursing the number of linear extensions by recursing on each com- on them independently. The recursion may run over ponent independently. We also survey previously proposed two alternative subproblem spaces, and we provide recursive techniques for comparison. heuristics for choosing the more efficient one. Our In Section 3 we show that the problem is solvable in time second algorithm is based on variable elimination t+4 t+4 O(n ), where t is the treewidth of the cover graph. While via inclusion–exclusion and runs in time O(n ), our result stems from a well-known method of nonserial dy- where t is the treewidth of the cover graph. We namic programming [Bertele` and Brioschi, 1972], known demonstrate experimentally that these new algo- as variable elimination and by other names [Dechter, 1999; rithms outperform previously suggested ones for a Koller and Friedman, 2009, Chap. -
Counting Linear Extensions of a Partial Order
Counting Linear Extensions of a Partial Order Seth Harris March 16, 2011 1 Introduction A partially ordered set (P; <) is a set P together with an irreflexive, transitive relation. A linear extension of (P; <) is a relation (P; ≺) such that (1) for all a; b 2 P either a ≺ b or a = b or b ≺ a, and (2) if a < b then a ≺ b; in other words, a total order that preserves the original partial order. We define Λ(P ) as the set of all linear extensions of P , and define N(P ) = jΛ(P )j. Throughout this paper, we will only be considering finite partial orders on n vertices. The problem of counting linear extensions is not only important in its home field of order theory, but is intimately connected to the theory of sorting. After all, if one is performing a comparison sort, one often starts with incomplete data (a partially sorted set) and must decide what alternatives exist for a total sorting, and whether there is an optimal pair of elements to compare next. Clearly one needs to know the number of possible extensions in order to proceed. It is also common to have partial data but to be unable to compare every pair of data points, in which case one must estimate a total ranking of the set, for instance by ranking the \average height" of an element, its mean rank over all linear extensions. This has widespread applications in the social sciences, such as in ranking lists of consumer products or athletic competitors. But again, to have any hope of calculating this, one must know the (approximate) number of extensions. -
Arxiv:1907.07845V2 [Cs.DM] 10 May 2021 Reigcaatrzto
LINEAR-SEMIORDERS AND THEIR INCOMPARABILITY GRAPHS ASAHI TAKAOKA Abstract. A linear-interval order is the intersection of a linear order and an interval order. For this class of orders, several structural results have been known. This paper introduces a new subclass of linear-interval orders. We call a partial order a linear-semiorder if it is the intersection of a linear order and a semiorder. We show a characterization and a polynomial-time recognition algorithm for linear-semiorders. We also prove that being a linear-semiorder is a comparability invariant, showing that incomparability graphs of linear-semiorders can be recognized in polynomial time. 1. Introduction A graph is an intersection graph if there is a set of objects such that each vertex corresponds to an object and two vertices are adjacent if and only if the corresponding objects have a nonempty intersection. The set of objects is called a representation of the graph. Intersection graphs of geometric objects have been widely investigated because of their interesting structures and applications [5,13,23]. Well-known examples of intersection graphs are interval graphs and permutation graphs. An interval graph is the intersection graph of intervals on the real line. Let L1 and L2 be two horizontal lines in the xy-plane with L1 above L2. A permutation graph is the intersection graph of line segments joining a point on L1 and a point on L2. A common generalization of the two graph classes is trapezoid graphs [8,9]. An interval on L1 and an interval on L2 define a trapezoid between L1 and L2.A trapezoid graph is the intersection graph of such trapezoids. -
GEOMETRIC EXTENSIONS and the 1/3 — 2/3 CONJECTURE As a Thesis Presented to the Faculty of San Francisco State University P
GEOMETRIC EXTENSIONS AND THE 1/3 — 2/3 CONJECTURE A s A thesis presented to the faculty of San Francisco State University P I g In partial fulfilment of The Requirements for The Degree Master of Arts In Mathematics by Sam Sehayek San Francisco, California May 2018 Copyright by Sam Sehayek CERTIFICATION OF APPROVAL I certify that I have read GEOMETRIC EXTENSIONS AND THE 1/3 — 2/S CONJECTURE by Sam Sehayek and that in my opinion this work meets the criteria for approving a thesis submitted in partial fulfill ment of the requirements for the degree: Master of Arts in Mathematics at San Francisco State University. Joseph Gubeladze Professor of Mathematics Matthias Beck Professor of Mathematics Federico Ardila Professor of Mathematics GEOMETRIC EXTENSIONS AND THE 1/3 — 2/3 CONJECTURE Sam Sehayek San Francisco State University 2018 The 1/3—2/3 Conjecture is a famous open problem that deals with partially ordered sets, called posets. Understanding the linear extensions of a poset can unlock hidden structure with interesting applications and further questions. The conjecture says that in every finite poset that is not totally ordered there is a pair x and y, such that x < y in 1/3 to 2/3 of all the linear extensions. Such pairs are called balanced pairs. We develop a geometric version of the conjecture, amenable to computational analysis by considering one dimensions projections of Euclidean realizations of the poset. We confirm the geometric 1/3— 2/3 conjecture for certain classes of posets, for which the original 1/3— 2/3 conjecture is currently out of reach. -
Lipics-Aofa-2018-14.Pdf (0.5
Beyond Series-Parallel Concurrent Systems: The Case of Arch Processes Olivier Bodini Laboratoire d’Informatique de Paris-Nord, CNRS UMR 7030 - Institut Galilée - Université Paris-Nord, 99, avenue Jean-Baptiste Clément, 93430 Villetaneuse, France. [email protected] Matthieu Dien Institute of Statistical Science, Academia Sinica, Taipei 115, Taiwan. [email protected] Antoine Genitrini Sorbonne Université, CNRS, Laboratoire d’Informatique de Paris 6 -LIP6- UMR 7606, F-75005 Paris, France. [email protected] Alfredo Viola Universidad de la República, Montevideo, Uruguay. viola@fing.edu.uy Abstract In this paper we focus on concurrent processes built on synchronization by means of futures. This concept is an abstraction for processes based on a main execution thread but allowing to delay some computations. The structure of a general concurrent process is a directed acyclic graph (DAG). Since the quantitative study of increasingly labeled DAG (directly related to processes) seems out of reach (this is a ]P-complete problem), we restrict ourselves to the study of arch processes, a simplistic model of processes with futures. They are based on two parameters related to their sizes and their numbers of arches. The increasingly labeled structures seems not to be specifiable in the classical sense of Analytic Combinatorics, but we manage to derive a recurrence equation for the enumeration. For this model we first exhibit an exact and an asymptotic formula for the number of runs of a given process. The second main contribution is composed of a uniform random sampler algorithm and an unranking one that allow efficient generation and exhaustive enumeration of the runs of a given arch process.