The Comb Poset and the Parsewords Function 1
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On Scattered Convex Geometries
ON SCATTERED CONVEX GEOMETRIES KIRA ADARICHEVA AND MAURICE POUZET Abstract. A convex geometry is a closure space satisfying the anti-exchange axiom. For several types of algebraic convex geometries we describe when the collection of closed sets is order scat- tered, in terms of obstructions to the semilattice of compact elements. In particular, a semilattice Ω(η), that does not appear among minimal obstructions to order-scattered algebraic modular lattices, plays a prominent role in convex geometries case. The connection to topological scat- teredness is established in convex geometries of relatively convex sets. 1. Introduction We call a pair X; φ of a non-empty set X and a closure operator φ 2X 2X on X a convex geometry[6], if it is a zero-closed space (i.e. ) and φ satisfies the anti-exchange axiom: ( ) ∶ → x A y and x∅ =A∅imply that y A x for all x y in X and all closed A X: ∈ ∪ { } ∉ ∉ ∪ { } The study of convex geometries in finite≠ case was inspired by their⊆ frequent appearance in mod- eling various discrete structures, as well as by their juxtaposition to matroids, see [20, 21]. More recently, there was a number of publications, see, for example, [4, 43, 44, 45, 48, 7] brought up by studies in infinite convex geometries. A convex geometry is called algebraic, if the closure operator φ is finitary. Most of interesting infinite convex geometries are algebraic, such as convex geometries of relatively convex sets, sub- semilattices of a semilattice, suborders of a partial order or convex subsets of a partially ordered set. -
SIGNED TREE ASSOCIAHEDRA Vincent PILAUD (CNRS & LIX)
SIGNED TREE ASSOCIAHEDRA Vincent PILAUD (CNRS & LIX) 1 2 3 4 4 2 1 3 POLYTOPES FROM COMBINATORICS POLYTOPES & COMBINATORICS polytope = convex hull of a finite set of Rd = bounded intersection of finitely many half-spaces face = intersection with a supporting hyperplane face lattice = all the faces with their inclusion relations Given a set of points, determine the face lattice of its convex hull. Given a lattice, is there a polytope which realizes it? PERMUTAHEDRON Permutohedron Perm(n) = conv f(σ(1); : : : ; σ(n + 1)) j σ 2 Σn+1g \ ≥ 321 = H \ H (J) ?6=J([n+1] 312 231 x1=x3 213 132 x1=x2 123 x2=x3 PERMUTAHEDRON Permutohedron Perm(n) = conv f(σ(1); : : : ; σ(n + 1)) j σ 2 Σn+1g 4321 \ = \ H≥(J) 2211 4312 H 3421 6=J [n+1] 3412 ? ( 4213 k-faces of Perm(n) 2212 ≡ ordered partitions of [n + 1] 2431 1211 into n + 1 − k parts 2413 ≡ surjections from [n + 1] 2341 3214 to [n + 1 − k] 1221 1432 2314 1423 1212 3124 1342 1222 1112 1324 2134 1243 1234 PERMUTAHEDRON Permutohedron Perm(n) = conv f(σ(1); : : : ; σ(n + 1)) j σ 2 Σn+1g 4321 \ = \ H≥(J) 2211 4312 H 3421 6=J [n+1] 3412 ? ( 4213 k-faces of Perm(n) 2212 ≡ ordered partitions of [n + 1] 2431 1211 into n + 1 − k parts 2413 ≡ surjections from [n + 1] 2341 3214 to [n + 1 − k] 1221 1432 2314 1423 1212 3124 connections to • inversion sets 1342 1222 1112 • weak order 1324 • reduced expressions 2134 1243 • braid moves 1234 • cosets of the symmetric group ASSOCIAHEDRA ASSOCIAHEDRON Associahedron = polytope whose face lattice is isomorphic to the lattice of crossing-free sets of internal diagonals of a convex (n + 3)-gon, ordered by reverse inclusion vertices $ triangulations vertices $ binary trees edges $ flips edges $ rotations faces $ dissections faces $ Schr¨oder trees VARIOUS ASSOCIAHEDRA Associahedron = polytope whose face lattice is isomorphic to the lattice of crossing-free sets of internal diagonals of a convex (n + 3)-gon, ordered by reverse inclusion (Pictures by Ceballos-Santos-Ziegler) Lee ('89), Gel'fand-Kapranov-Zelevinski ('94), Billera-Filliman-Sturmfels ('90), . -
Advanced Discrete Mathematics Mm-504 &
1 ADVANCED DISCRETE MATHEMATICS M.A./M.Sc. Mathematics (Final) MM-504 & 505 (Option-P3) Directorate of Distance Education Maharshi Dayanand University ROHTAK – 124 001 2 Copyright © 2004, Maharshi Dayanand University, ROHTAK All Rights Reserved. No part of this publication may be reproduced or stored in a retrieval system or transmitted in any form or by any means; electronic, mechanical, photocopying, recording or otherwise, without the written permission of the copyright holder. Maharshi Dayanand University ROHTAK – 124 001 Developed & Produced by EXCEL BOOKS PVT. LTD., A-45 Naraina, Phase 1, New Delhi-110 028 3 Contents UNIT 1: Logic, Semigroups & Monoids and Lattices 5 Part A: Logic Part B: Semigroups & Monoids Part C: Lattices UNIT 2: Boolean Algebra 84 UNIT 3: Graph Theory 119 UNIT 4: Computability Theory 202 UNIT 5: Languages and Grammars 231 4 M.A./M.Sc. Mathematics (Final) ADVANCED DISCRETE MATHEMATICS MM- 504 & 505 (P3) Max. Marks : 100 Time : 3 Hours Note: Question paper will consist of three sections. Section I consisting of one question with ten parts covering whole of the syllabus of 2 marks each shall be compulsory. From Section II, 10 questions to be set selecting two questions from each unit. The candidate will be required to attempt any seven questions each of five marks. Section III, five questions to be set, one from each unit. The candidate will be required to attempt any three questions each of fifteen marks. Unit I Formal Logic: Statement, Symbolic representation, totologies, quantifiers, pradicates and validity, propositional logic. Semigroups and Monoids: Definitions and examples of semigroups and monoids (including those pertaining to concentration operations). -
On a Remark of Loday About the Associahedron and Algebraic K-Theory
An. S¸t. Univ. Ovidius Constant¸a Vol. 16(1), 2008, 5–18 On a remark of Loday about the Associahedron and Algebraic K-Theory Gefry Barad Abstract In his 2006 Cyclic Homology Course from Poland, J.L. Loday stated that the edges of the associahedron of any dimension can be labelled by elements of the Steinberg Group such that any 2-dimensional face represents a relation in the Steinberg Group. We prove his statement. We define a new group R(n) relevant in the study of the rotation distance between rooted planar binary trees . 1 Introduction 1.1 Combinatorics: binary rooted trees and the associahedron Our primary objects of study are planar rooted binary trees. By definition, they are connected graphs without cycles, with n trivalent vertices and n+2 univalent vertices, one of them being marked as the root. 1 2n There are n+1 n binary trees with n internal vertices. Key Words: Rooted binary trees; Associahedron; Algebraic K-Theory, Combinatorics. Mathematics Subject Classification: 05-99; 19Cxx; 19M05; 05C05 Received: October, 2007 Accepted: January, 2008 5 6 Gefry Barad Figure 1. The associahedron Kn is an (n − 1)-dimensional convex polytope whose vertices are labelled by rooted planar binary trees with n internal vertices. Two labelled vertices are connected by an edge if and only if the corresponding trees are connected by an elementary move called rotation. Two trees are connected by a rotation if they are identical, except the zones from the figure below, where one edge is moved into another position; we erase an internal edge and one internal vertex and we glue it again in a different location, to get a rooted binary tree. -
Trivial Meet and Join Within the Lattice of Monotone Triangles John Engbers Marquette University, [email protected]
Marquette University e-Publications@Marquette Mathematics, Statistics and Computer Science Mathematics, Statistics and Computer Science, Faculty Research and Publications Department of 1-1-2014 Trivial Meet and Join within the Lattice of Monotone Triangles John Engbers Marquette University, [email protected] Adam Hammett Bethel College - Mishawaka Published version. Electronic Journal of Combinatorics, Vol. 21, No. 3 (2014). Permalink. © 2014 The Authors. Used with permission. Trivial Meet and Join within the Lattice of Monotone Triangles John Engbers Department of Mathematics, Statistics and Computer Science Marquette University Milwaukee, WI, U.S.A. [email protected] Adam Hammett Department of Mathematical Sciences Bethel College Mishawaka, IN, U.S.A. [email protected] Submitted: Jan 22, 2014; Accepted: Jul 10, 2014; Published: Jul 21, 2014 Mathematics Subject Classifications: 05A05, 05A16, 06A20 Abstract The lattice of monotone triangles (Mn; 6) ordered by entry-wise comparisons is studied. Let τmin denote the unique minimal element in this lattice, and τmax the unique maximum. The number of r-tuples of monotone triangles (τ1; : : : ; τr) with minimal infimum τmin (maximal supremum τmax, resp.) is shown to asymptotically r−1 approach rjMnj as n ! 1. Thus, with high probability this event implies that one of the τi is τmin (τmax, resp.). Higher-order error terms are also discussed. Keywords: monotone triangles; permutations; square ice; alternating sign matri- ces; meet; join 1 Introduction and statement -
Completely Representable Lattices
Completely representable lattices Robert Egrot and Robin Hirsch Abstract It is known that a lattice is representable as a ring of sets iff the lattice is distributive. CRL is the class of bounded distributive lattices (DLs) which have representations preserving arbitrary joins and meets. jCRL is the class of DLs which have representations preserving arbitrary joins, mCRL is the class of DLs which have representations preserving arbitrary meets, and biCRL is defined to be jCRL ∩ mCRL. We prove CRL ⊂ biCRL = mCRL ∩ jCRL ⊂ mCRL =6 jCRL ⊂ DL where the marked inclusions are proper. Let L be a DL. Then L ∈ mCRL iff L has a distinguishing set of complete, prime filters. Similarly, L ∈ jCRL iff L has a distinguishing set of completely prime filters, and L ∈ CRL iff L has a distinguishing set of complete, completely prime filters. Each of the classes above is shown to be pseudo-elementary hence closed under ultraproducts. The class CRL is not closed under elementary equivalence, hence it is not elementary. 1 Introduction An atomic representation h of a Boolean algebra B is a representation h: B → ℘(X) (some set X) where h(1) = {h(a): a is an atom of B}. It is known that a representation of a Boolean algebraS is a complete representation (in the sense of a complete embedding into a field of sets) if and only if it is an atomic repre- sentation and hence that the class of completely representable Boolean algebras is precisely the class of atomic Boolean algebras, and hence is elementary [6]. arXiv:1201.2331v3 [math.RA] 30 Aug 2016 This result is not obvious as the usual definition of a complete representation is thoroughly second order. -
On Birkhoff's Common Abstraction Problem
F. Paoli On Birkho®'s Common C. Tsinakis Abstraction Problem Abstract. In his milestone textbook Lattice Theory, Garrett Birkho® challenged his readers to develop a \common abstraction" that includes Boolean algebras and lattice- ordered groups as special cases. In this paper, after reviewing the past attempts to solve the problem, we provide our own answer by selecting as common generalization of BA and LG their join BA_LG in the lattice of subvarieties of FL (the variety of FL-algebras); we argue that such a solution is optimal under several respects and we give an explicit equational basis for BA_LG relative to FL. Finally, we prove a Holland-type representation theorem for a variety of FL-algebras containing BA _ LG. Keywords: Residuated lattice, FL-algebra, Substructural logics, Boolean algebra, Lattice- ordered group, Birkho®'s problem, History of 20th C. algebra. 1. Introduction In his milestone textbook Lattice Theory [2, Problem 108], Garrett Birkho® challenged his readers by suggesting the following project: Develop a common abstraction that includes Boolean algebras (rings) and lattice ordered groups as special cases. Over the subsequent decades, several mathematicians tried their hands at Birkho®'s intriguing problem. Its very formulation, in fact, intrinsically seems to call for reiterated attempts: unlike most problems contained in the book, for which it is manifest what would count as a correct solution, this one is stated in su±ciently vague terms as to leave it open to debate whether any proposed answer is really adequate. It appears to us that Rama Rao puts things right when he remarks [28, p. -
Partial Orders — Basics
Partial Orders — Basics Edward A. Lee UC Berkeley — EECS EECS 219D — Concurrent Models of Computation Last updated: January 23, 2014 Outline Sets Join (Least Upper Bound) Relations and Functions Meet (Greatest Lower Bound) Notation Example of Join and Meet Directed Sets, Bottom Partial Order What is Order? Complete Partial Order Strict Partial Order Complete Partial Order Chains and Total Orders Alternative Definition Quiz Example Partial Orders — Basics Sets Frequently used sets: • B = {0, 1}, the set of binary digits. • T = {false, true}, the set of truth values. • N = {0, 1, 2, ···}, the set of natural numbers. • Z = {· · · , −1, 0, 1, 2, ···}, the set of integers. • R, the set of real numbers. • R+, the set of non-negative real numbers. Edward A. Lee | UC Berkeley — EECS3/32 Partial Orders — Basics Relations and Functions • A binary relation from A to B is a subset of A × B. • A partial function f from A to B is a relation where (a, b) ∈ f and (a, b0) ∈ f =⇒ b = b0. Such a partial function is written f : A*B. • A total function or just function f from A to B is a partial function where for all a ∈ A, there is a b ∈ B such that (a, b) ∈ f. Edward A. Lee | UC Berkeley — EECS4/32 Partial Orders — Basics Notation • A binary relation: R ⊆ A × B. • Infix notation: (a, b) ∈ R is written aRb. • A symbol for a relation: • ≤⊂ N × N • (a, b) ∈≤ is written a ≤ b. • A function is written f : A → B, and the A is called its domain and the B its codomain. -
Associahedron
Associahedron Jean-Louis Loday CNRS, Strasbourg April 23rd, 2005 Clay Mathematics Institute 2005 Colloquium Series Polytopes 7T 4 × 7TTTT 4 ×× 77 TT 44 × 7 simplex 4 ×× 77 44 × 7 ··· 4 ×× 77 ×× 7 o o ooo ooo cube o o ··· oo ooo oo?? ooo ?? ? ?? ? ?? OOO OO ooooOOO oooooo OO? ?? oOO ooo OOO o OOO oo?? permutohedron OOooo ? ··· OO o ? O O OOO ooo ?? OOO o OOO ?? oo OO ?ooo n = 2 3 ··· Permutohedron := convex hull of (n+1)! points n+1 (σ(1), . , σ(n + 1)) ∈ R Parenthesizing X= topological space with product (a, b) 7→ ab Not associative but associative up to homo- topy (ab)c • ) • a(bc) With four elements: ((ab)c)d H jjj HH jjjj HH jjjj HH tjj HH (a(bc))d HH HH HH HH H$ vv (ab)(cd) vv vv vv vv (( ) ) TTT vv a bc d TTTT vv TTT vv TTTz*vv a(b(cd)) We suppose that there is a homotopy between the two composite paths, and so on. Jim Stasheff Staheff’s result (1963): There exists a cellular complex such that – vertices in bijection with the parenthesizings – edges in bijection with the homotopies – 2-cells in bijection with homotopies of com- posite homotopies – etc, and which is homeomorphic to a ball. Problem: construct explicitely the Stasheff com- plex in any dimension. oo?? ooo ?? ?? ?? • OOO OO n = 0 1 2 3 Planar binary trees (see R. Stanley’s notes p. 189) Planar binary trees with n + 1 leaves, that is n internal vertices: n o ? ?? ? ?? ?? ?? Y0 = { | } ,Y1 = ,Y2 = ? , ? , ( ) ? ? ? ? ? ? ? ? ? ? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ?? ? ?? ? Y3 = ? , ? , ? , ? , ? . Bijection between planar binary trees and paren- thesizings: x0 x1 x2 x3 x4 RRR ll ll RRR ll RRlRll lll RRlll RRR lll lll lRRR lll RRR lll RRlll (((x0x1)x2)(x3x4)) The notion of grafting s t 3 33 t ∨ s = 3 Associahedron n To t ∈ Yn we associate M(t) ∈ R : n M(t) := (a1b1, ··· , aibi, ··· , anbn) ∈ R ai = # leaves on the left side of the ith vertex bi = # leaves on the right side of the ith vertex Examples: ? ? ?? ?? ?? ?? M( ) = (1),M ? = (1, 2),M ? = (2, 1), ? ? ? ?? ?? ?? ?? M ? = (1, 2, 3),M ? = (1, 4, 1). -
Hopf Monoids of Ordered Simplicial Complexes
HOPF MONOIDS OF ORDERED SIMPLICIAL COMPLEXES FEDERICO CASTILLO, JEREMY L. MARTIN, AND JOSE´ A. SAMPER ABSTRACT. We study pure ordered simplicial complexes (i.e., simplicial complexes with a linear order on their ground sets) from the Hopf-theoretic point of view. We define a Hopf class to be a family of pure ordered simplicial complexes that give rise to a Hopf monoid under join and deletion/contraction. The prototypical Hopf class is the family of ordered matroids. The idea of a Hopf class allows us to give a systematic study of simpli- cial complexes related to matroids, including shifted complexes, broken-circuit complexes, and unbounded matroids (which arise from unbounded generalized permutohedra with 0/1 coordinates). We compute the antipodes in two cases: facet-initial complexes (a much larger class than shifted complexes) and unbounded ordered matroids. In the latter case, we embed the Hopf monoid of ordered matroids into the Hopf monoid of ordered generalized permuto- hedra, enabling us to compute the antipode using the topological method of Aguiar and Ardila. The calculation is complicated by the appearance of certain auxiliary simplicial complexes that we call Scrope complexes, whose Euler characteristics control certain coeffi- cients of the antipode. The resulting antipode formula is multiplicity-free and cancellation- free. CONTENTS 1. Introduction2 1.1. Background: Matroids and combinatorial Hopf theory2 1.2. Ordered simplicial complexes3 1.3. Polyhedra5 1.4. Antipodes6 2. Background and notation7 2.1. Simplicial complexes8 2.2. Matroids9 2.3. Set compositions, preposets, and the braid fan9 2.4. Generalized permutohedra 11 2.5. Species and Hopf monoids 14 2.6. -
Lattice Duality: the Origin of Probability and Entropy
, 1 Lattice Duality: The Origin of Probability and Entropy Kevin H. Knuth NASA Ames Research Center, Mail Stop 269-3, Moffett Field CA 94035-1000, USA Abstract Bayesian probability theory is an inference calculus, which originates from a gen- eralization of inclusion on the Boolean lattice of logical assertions to a degree of inclusion represented by a real number. Dual to this lattice is the distributive lat- tice of questions constructed from the ordered set of down-sets of assertions, which forms the foundation of the calculus of inquiry-a generalization of information theory. In this paper we introduce this novel perspective on these spaces in which machine learning is performed and discuss the relationship between these results and several proposed generalizations of information theory in the literature. Key words: probability, entropy, lattice, information theory, Bayesian inference, inquiry PACS: 1 Introduction It has been known for some time that probability theory can be derived as a generalization of Boolean implication to degrees of implication repre- sented by real numbers [11,12]. Straightforward consistency requirements dic- tate the form of the sum and product rules of probability, and Bayes’ thee rem [11,12,47,46,20,34],which forms the basis of the inferential calculus, also known as inductive inference. However, in machine learning applications it is often times more useful to rely on information theory [45] in the design of an algorithm. On the surface, the connection between information theory and probability theory seems clear-information depends on entropy and entropy Email address: kevin.h. [email protected] (Kevin H. -
On Comparability of Random Permutations
ON COMPARABILITY OF RANDOM PERMUTATIONS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of the Ohio State University By Adam Hammett, B.S. ***** The Ohio State University 2007 Dissertation Committee: Approved by Dr. Boris Pittel, Advisor Dr. Gerald Edgar Advisor Dr. Akos Seress Graduate Program in Mathematics ABSTRACT Two permutations of [n] := {1, 2, . , n} are comparable in the Bruhat order if one can be obtained from the other by a sequence of transpositions decreasing the number of inversions. We show that the total number of pairs of permutations (π, σ) with π ≤ σ is of order (n!)2/n2 at most. Equivalently, if π, σ are chosen uniformly at random and independently of each other, then P (π ≤ σ) is of order n−2 at most. By a direct probabilistic argument we prove P (π ≤ σ) is of order (0.708)n at least, so that there is currently a wide qualitative gap between the upper and lower bounds. Next, emboldened by a connection with Ferrers diagrams and plane partitions implicit in Bressoud’s book [13], we return to the Bruhat order upper bound and show that for n-permutations π1, . , πr selected independently and uniformly at random, −r(r−1) P (π1 ≤ · · · ≤ πr) = O n , thus providing an extension of our result for pairs of permutations to chains of length r > 2. Turning to the related weak order “” – when only adjacent transpositions are ∗ admissible – we use a non-inversion set criterion to prove that Pn := P (π σ) is pn ∗ submultiplicative, thus showing existence of ρ = lim Pn .