Combinatorial Invariants of Rational Polytopes
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7 LATTICE POINTS and LATTICE POLYTOPES Alexander Barvinok
7 LATTICE POINTS AND LATTICE POLYTOPES Alexander Barvinok INTRODUCTION Lattice polytopes arise naturally in algebraic geometry, analysis, combinatorics, computer science, number theory, optimization, probability and representation the- ory. They possess a rich structure arising from the interaction of algebraic, convex, analytic, and combinatorial properties. In this chapter, we concentrate on the the- ory of lattice polytopes and only sketch their numerous applications. We briefly discuss their role in optimization and polyhedral combinatorics (Section 7.1). In Section 7.2 we discuss the decision problem, the problem of finding whether a given polytope contains a lattice point. In Section 7.3 we address the counting problem, the problem of counting all lattice points in a given polytope. The asymptotic problem (Section 7.4) explores the behavior of the number of lattice points in a varying polytope (for example, if a dilation is applied to the polytope). Finally, in Section 7.5 we discuss problems with quantifiers. These problems are natural generalizations of the decision and counting problems. Whenever appropriate we address algorithmic issues. For general references in the area of computational complexity/algorithms see [AB09]. We summarize the computational complexity status of our problems in Table 7.0.1. TABLE 7.0.1 Computational complexity of basic problems. PROBLEM NAME BOUNDED DIMENSION UNBOUNDED DIMENSION Decision problem polynomial NP-hard Counting problem polynomial #P-hard Asymptotic problem polynomial #P-hard∗ Problems with quantifiers unknown; polynomial for ∀∃ ∗∗ NP-hard ∗ in bounded codimension, reduces polynomially to volume computation ∗∗ with no quantifier alternation, polynomial time 7.1 INTEGRAL POLYTOPES IN POLYHEDRAL COMBINATORICS We describe some combinatorial and computational properties of integral polytopes. -
A Parallelepiped Based Approach
3D Modelling Using Geometric Constraints: A Parallelepiped Based Approach Marta Wilczkowiak, Edmond Boyer, and Peter Sturm MOVI–GRAVIR–INRIA Rhˆone-Alpes, 38330 Montbonnot, France, [email protected], http://www.inrialpes.fr/movi/people/Surname Abstract. In this paper, efficient and generic tools for calibration and 3D reconstruction are presented. These tools exploit geometric con- straints frequently present in man-made environments and allow cam- era calibration as well as scene structure to be estimated with a small amount of user interactions and little a priori knowledge. The proposed approach is based on primitives that naturally characterize rigidity con- straints: parallelepipeds. It has been shown previously that the intrinsic metric characteristics of a parallelepiped are dual to the intrinsic charac- teristics of a perspective camera. Here, we generalize this idea by taking into account additional redundancies between multiple images of multiple parallelepipeds. We propose a method for the estimation of camera and scene parameters that bears strongsimilarities with some self-calibration approaches. Takinginto account prior knowledgeon scene primitives or cameras, leads to simpler equations than for standard self-calibration, and is expected to improve results, as well as to allow structure and mo- tion recovery in situations that are otherwise under-constrained. These principles are illustrated by experimental calibration results and several reconstructions from uncalibrated images. 1 Introduction This paper is about using partial information on camera parameters and scene structure, to simplify and enhance structure from motion and (self-) calibration. We are especially interested in reconstructing man-made environments for which constraints on the scene structure are usually easy to provide. -
Area, Volume and Surface Area
The Improving Mathematics Education in Schools (TIMES) Project MEASUREMENT AND GEOMETRY Module 11 AREA, VOLUME AND SURFACE AREA A guide for teachers - Years 8–10 June 2011 YEARS 810 Area, Volume and Surface Area (Measurement and Geometry: Module 11) For teachers of Primary and Secondary Mathematics 510 Cover design, Layout design and Typesetting by Claire Ho The Improving Mathematics Education in Schools (TIMES) Project 2009‑2011 was funded by the Australian Government Department of Education, Employment and Workplace Relations. The views expressed here are those of the author and do not necessarily represent the views of the Australian Government Department of Education, Employment and Workplace Relations. © The University of Melbourne on behalf of the international Centre of Excellence for Education in Mathematics (ICE‑EM), the education division of the Australian Mathematical Sciences Institute (AMSI), 2010 (except where otherwise indicated). This work is licensed under the Creative Commons Attribution‑NonCommercial‑NoDerivs 3.0 Unported License. http://creativecommons.org/licenses/by‑nc‑nd/3.0/ The Improving Mathematics Education in Schools (TIMES) Project MEASUREMENT AND GEOMETRY Module 11 AREA, VOLUME AND SURFACE AREA A guide for teachers - Years 8–10 June 2011 Peter Brown Michael Evans David Hunt Janine McIntosh Bill Pender Jacqui Ramagge YEARS 810 {4} A guide for teachers AREA, VOLUME AND SURFACE AREA ASSUMED KNOWLEDGE • Knowledge of the areas of rectangles, triangles, circles and composite figures. • The definitions of a parallelogram and a rhombus. • Familiarity with the basic properties of parallel lines. • Familiarity with the volume of a rectangular prism. • Basic knowledge of congruence and similarity. • Since some formulas will be involved, the students will need some experience with substitution and also with the distributive law. -
Evaporationin Icparticles
The JapaneseAssociationJapanese Association for Crystal Growth (JACG){JACG) Small Metallic ParticlesProduced by Evaporation in lnert Gas at Low Pressure Size distributions, crystal morphologyand crystal structures KazuoKimoto physiosLaboratory, Department of General Educatien, Nago)ra University Various experimental results ef the studies on fine 1. Introduction particles produced by evaperation and subsequent conden$ation in inert gas at low pressure are reviewed. Small particles of metals and semi-metals can A brief historical survey is given and experimental be produced by evaporation and subsequent arrangements for the production of the particles are condensation in the free space of an inert gas at described. The structure of the stnoke, the qualitative low pressure, a very simple technique, recently particle size clistributions, small particle statistios and "gas often referred to as evaporation technique"i) the crystallographic aspccts ofthe particles are consid- ered in some detail. Emphasis is laid on the crystal (GET). When the pressure of an inert is in the inorphology and the related crystal structures ef the gas range from about one to several tens of Torr, the particles efsome 24 elements. size of the particles produced by GET is in thc range from several to several thousand nm, de- pending on the materials evaporated, the naturc of the inert gas and various other evaporation conditions. One of the most characteristic fea- tures of the particles thus produced is that the particles have, generally speaking, very well- defined crystal habits when the particle size is in the range from about ten to several hundred nm. The crystal morphology and the relevant crystal structures of these particles greatly interested sDme invcstigators in Japan, 4nd encouraged them to study these propenies by means of elec- tron microscopy and electron difliraction. -
Combinatorial and Discrete Problems in Convex Geometry
COMBINATORIAL AND DISCRETE PROBLEMS IN CONVEX GEOMETRY A dissertation submitted to Kent State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy by Matthew R. Alexander September, 2017 Dissertation written by Matthew R. Alexander B.S., Youngstown State University, 2011 M.A., Kent State University, 2013 Ph.D., Kent State University, 2017 Approved by Dr. Artem Zvavitch , Co-Chair, Doctoral Dissertation Committee Dr. Matthieu Fradelizi , Co-Chair Dr. Dmitry Ryabogin , Members, Doctoral Dissertation Committee Dr. Fedor Nazarov Dr. Feodor F. Dragan Dr. Jonathan Maletic Accepted by Dr. Andrew Tonge , Chair, Department of Mathematical Sciences Dr. James L. Blank , Dean, College of Arts and Sciences TABLE OF CONTENTS LIST OF FIGURES . vi ACKNOWLEDGEMENTS ........................................ vii NOTATION ................................................. viii I Introduction 1 1 This Thesis . .2 2 Preliminaries . .4 2.1 Convex Geometry . .4 2.2 Basic functions and their properties . .5 2.3 Classical theorems . .6 2.4 Polarity . .8 2.5 Volume Product . .8 II The Discrete Slicing Problem 11 3 The Geometry of Numbers . 12 3.1 Introduction . 12 3.2 Lattices . 12 3.3 Minkowski's Theorems . 14 3.4 The Ehrhart Polynomial . 15 4 Geometric Tomography . 17 4.1 Introduction . 17 iii 4.2 Projections of sets . 18 4.3 Sections of sets . 19 4.4 The Isomorphic Busemann-Petty Problem . 20 5 The Discrete Slicing Problem . 22 5.1 Introduction . 22 5.2 Solution in Z2 ............................................. 23 5.3 Approach via Discrete F. John Theorem . 23 5.4 Solution using known inequalities . 26 5.5 Solution for Unconditional Bodies . 27 5.6 Discrete Brunn's Theorem . -
Classification of Ehrhart Polynomials of Integral Simplices Akihiro Higashitani
Classification of Ehrhart polynomials of integral simplices Akihiro Higashitani To cite this version: Akihiro Higashitani. Classification of Ehrhart polynomials of integral simplices. 24th International Conference on Formal Power Series and Algebraic Combinatorics (FPSAC 2012), 2012, Nagoya, Japan. pp.587-594. hal-01283113 HAL Id: hal-01283113 https://hal.archives-ouvertes.fr/hal-01283113 Submitted on 5 Mar 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. FPSAC 2012, Nagoya, Japan DMTCS proc. AR, 2012, 587–594 Classification of Ehrhart polynomials of integral simplices Akihiro Higashitani y Department of Pure and Applied Mathematics, Graduate School of Information Science and Technology, Osaka University, Toyonaka, Osaka 560-0043, Japan Abstract. Let δ(P) = (δ0; δ1; : : : ; δd) be the δ-vector of an integral convex polytope P of dimension d. First, by Pd using two well-known inequalities on δ-vectors, we classify the possible δ-vectors with i=0 δi ≤ 3. Moreover, by Pd means of Hermite normal forms of square matrices, we also classify the possible δ-vectors with i=0 δi = 4. In Pd Pd addition, for i=0 δi ≥ 5, we characterize the δ-vectors of integral simplices when i=0 δi is prime. -
Crystallography Ll Lattice N-Dimensional, Infinite, Periodic Array of Points, Each of Which Has Identical Surroundings
crystallography ll Lattice n-dimensional, infinite, periodic array of points, each of which has identical surroundings. use this as test for lattice points A2 ("bcc") structure lattice points Lattice n-dimensional, infinite, periodic array of points, each of which has identical surroundings. use this as test for lattice points CsCl structure lattice points Choosing unit cells in a lattice Want very small unit cell - least complicated, fewer atoms Prefer cell with 90° or 120°angles - visualization & geometrical calculations easier Choose cell which reflects symmetry of lattice & crystal structure Choosing unit cells in a lattice Sometimes, a good unit cell has more than one lattice point 2-D example: Primitive cell (one lattice pt./cell) has End-centered cell (two strange angle lattice pts./cell) has 90° angle Choosing unit cells in a lattice Sometimes, a good unit cell has more than one lattice point 3-D example: body-centered cubic (bcc, or I cubic) (two lattice pts./cell) The primitive unit cell is not a cube 14 Bravais lattices Allowed centering types: P I F C primitive body-centered face-centered C end-centered Primitive R - rhombohedral rhombohedral cell (trigonal) centering of trigonal cell 14 Bravais lattices Combine P, I, F, C (A, B), R centering with 7 crystal systems Some combinations don't work, some don't give new lattices - C tetragonal C-centering destroys cubic = P tetragonal symmetry 14 Bravais lattices Only 14 possible (Bravais, 1848) System Allowed centering Triclinic P (primitive) Monoclinic P, I (innerzentiert) Orthorhombic P, I, F (flächenzentiert), A (end centered) Tetragonal P, I Cubic P, I, F Hexagonal P Trigonal P, R (rhombohedral centered) Choosing unit cells in a lattice Unit cell shape must be: 2-D - parallelogram (4 sides) 3-D - parallelepiped (6 faces) Not a unit cell: Choosing unit cells in a lattice Unit cell shape must be: 2-D - parallelogram (4 sides) 3-D - parallelepiped (6 faces) Not a unit cell: correct cell Stereographic projections Show or represent 3-D object in 2-D Procedure: 1. -
Unimodular Triangulations of Dilated 3-Polytopes
Trudy Moskov. Matem. Obw. Trans. Moscow Math. Soc. Tom 74 (2013), vyp. 2 2013, Pages 293–311 S 0077-1554(2014)00220-X Article electronically published on April 9, 2014 UNIMODULAR TRIANGULATIONS OF DILATED 3-POLYTOPES F. SANTOS AND G. M. ZIEGLER Abstract. A seminal result in the theory of toric varieties, by Knudsen, Mumford and Waterman (1973), asserts that for every lattice polytope P there is a positive integer k such that the dilated polytope kP has a unimodular triangulation. In dimension 3, Kantor and Sarkaria (2003) have shown that k = 4 works for every polytope. But this does not imply that every k>4 works as well. We here study the values of k for which the result holds, showing that: (1) It contains all composite numbers. (2) It is an additive semigroup. These two properties imply that the only values of k that may not work (besides 1 and 2, which are known not to work) are k ∈{3, 5, 7, 11}.Withanad-hocconstruc- tion we show that k =7andk = 11 also work, except in this case the triangulation cannot be guaranteed to be “standard” in the boundary. All in all, the only open cases are k =3andk =5. § 1. Introduction Let Λ ⊂ Rd be an affine lattice. A lattice polytope (or an integral polytope [4]) is a polytope P with all its vertices in Λ. We are particularly interested in lattice (full- dimensional) simplices. The vertices of a lattice simplex Δ are an affine basis for Rd, hence they induce a sublattice ΛΔ of Λ of index equal to the normalized volume of Δ with respect to Λ. -
Cross Product Review
12.4 Cross Product Review: The dot product of uuuu123, , and v vvv 123, , is u v uvuvuv 112233 uv u u u u v u v cos or cos uv u and v are orthogonal if and only if u v 0 u uv uv compvu projvuv v v vv projvu cross product u v uv23 uv 32 i uv 13 uv 31 j uv 12 uv 21 k u v is orthogonal to both u and v. u v u v sin Geometric description of the cross product of the vectors u and v The cross product of two vectors is a vector! • u x v is perpendicular to u and v • The length of u x v is u v u v sin • The direction is given by the right hand side rule Right hand rule Place your 4 fingers in the direction of the first vector, curl them in the direction of the second vector, Your thumb will point in the direction of the cross product Algebraic description of the cross product of the vectors u and v The cross product of uu1, u 2 , u 3 and v v 1, v 2 , v 3 is uv uv23 uvuv 3231,, uvuv 1312 uv 21 check (u v ) u 0 and ( u v ) v 0 (u v ) u uv23 uvuv 3231 , uvuv 1312 , uv 21 uuu 123 , , uvu231 uvu 321 uvu 312 uvu 132 uvu 123 uvu 213 0 similary: (u v ) v 0 length u v u v sin is a little messier : 2 2 2 2 2 2 2 2uv 2 2 2 uvuv sin22 uv 1 cos uv 1 uvuv 22 uv now need to show that u v2 u 2 v 2 u v2 (try it..) An easier way to remember the formula for the cross products is in terms of determinants: ab 12 2x2 determinant: ad bc 4 6 2 cd 34 3x3 determinants: An example Copy 1st 2 columns 1 6 2 sum of sum of 1 6 2 1 6 forward backward 3 1 3 3 1 3 3 1 diagonal diagonal 4 5 2 4 5 2 4 5 products products determinant = 2 72 30 8 15 36 40 59 19 recall: uv uv23 uvuv 3231, uvuv 1312 , uv 21 i j k i j k i j u1 u 2 u 3 u 1 u 2 now we claim that uvu1 u 2 u 3 v1 v 2 v 3 v 1 v 2 v1 v 2 v 3 iuv23 j uv 31 k uv 12 k uv 21 i uv 32 j uv 13 u v uv23 uv 32 i uv 13 uv 31 j uv 12 uv 21 k uv uv23 uvuv 3231,, uvuv 1312 uv 21 Example: Let u1, 2,1 and v 3,1, 2 Find u v. -
The $ H^* $-Polynomial of the Order Polytope of the Zig-Zag Poset
THE h∗-POLYNOMIAL OF THE ORDER POLYTOPE OF THE ZIG-ZAG POSET JANE IVY COONS AND SETH SULLIVANT Abstract. We describe a family of shellings for the canonical tri- angulation of the order polytope of the zig-zag poset. This gives a new combinatorial interpretation for the coefficients in the numer- ator of the Ehrhart series of this order polytope in terms of the swap statistic on alternating permutations. 1. Introduction and Preliminaries The zig-zag poset Zn on ground set {z1,...,zn} is the poset with exactly the cover relations z1 < z2 > z3 < z4 > . That is, this partial order satisfies z2i−1 < z2i and z2i > z2i+1 for all i between n−1 1 and ⌊ 2 ⌋. The order polytope of Zn, denoted O(Zn) is the set n of all n-tuples (x1,...,xn) ∈ R that satisfy 0 ≤ xi ≤ 1 for all i and xi ≤ xj whenever zi < zj in Zn. In this paper, we introduce the “swap” permutation statistic on alternating permutations to give a new combinatorial interpretation of the numerator of the Ehrhart series of O(Zn). We began studying this problem in relation to combinatorial proper- ties of the Cavender-Farris-Neyman model with a molecular clock (or CFN-MC model) from mathematical phylogenetics [4]. We were inter- ested in the polytope associated to the toric variety obtained by ap- plying the discrete Fourier transform to the Cavender-Farris-Neyman arXiv:1901.07443v2 [math.CO] 1 Apr 2020 model with a molecular clock on a given rooted binary phylogenetic tree. We call this polytope the CFN-MC polytope. -
15 BASIC PROPERTIES of CONVEX POLYTOPES Martin Henk, J¨Urgenrichter-Gebert, and G¨Unterm
15 BASIC PROPERTIES OF CONVEX POLYTOPES Martin Henk, J¨urgenRichter-Gebert, and G¨unterM. Ziegler INTRODUCTION Convex polytopes are fundamental geometric objects that have been investigated since antiquity. The beauty of their theory is nowadays complemented by their im- portance for many other mathematical subjects, ranging from integration theory, algebraic topology, and algebraic geometry to linear and combinatorial optimiza- tion. In this chapter we try to give a short introduction, provide a sketch of \what polytopes look like" and \how they behave," with many explicit examples, and briefly state some main results (where further details are given in subsequent chap- ters of this Handbook). We concentrate on two main topics: • Combinatorial properties: faces (vertices, edges, . , facets) of polytopes and their relations, with special treatments of the classes of low-dimensional poly- topes and of polytopes \with few vertices;" • Geometric properties: volume and surface area, mixed volumes, and quer- massintegrals, including explicit formulas for the cases of the regular simplices, cubes, and cross-polytopes. We refer to Gr¨unbaum [Gr¨u67]for a comprehensive view of polytope theory, and to Ziegler [Zie95] respectively to Gruber [Gru07] and Schneider [Sch14] for detailed treatments of the combinatorial and of the convex geometric aspects of polytope theory. 15.1 COMBINATORIAL STRUCTURE GLOSSARY d V-polytope: The convex hull of a finite set X = fx1; : : : ; xng of points in R , n n X i X P = conv(X) := λix λ1; : : : ; λn ≥ 0; λi = 1 : i=1 i=1 H-polytope: The solution set of a finite system of linear inequalities, d T P = P (A; b) := x 2 R j ai x ≤ bi for 1 ≤ i ≤ m ; with the extra condition that the set of solutions is bounded, that is, such that m×d there is a constant N such that jjxjj ≤ N holds for all x 2 P . -
Triangulations of Integral Polytopes, Examples and Problems
数理解析研究所講究録 955 巻 1996 年 133-144 133 Triangulations of integral polytopes, examples and problems Jean-Michel KANTOR We are interested in polytopes in real space of arbitrary dimension, having vertices with integral co- ordinates: integral polytopes. The recent increase of interest for the study of these $\mathrm{p}\mathrm{o}\mathrm{l}\mathrm{y}$ topes and their triangulations has various motivations; let us mention the main ones: . the beautiful theory of toric varieties has built a bridge between algebraic geometry and the combina- torics of these integral polytopes [12]. Triangulations of cones and polytopes occur naturally for example in problems of existence of crepant resolution of singularities $[1,5]$ . The work of the school of $\mathrm{I}.\mathrm{M}$ . Gelfand on secondary polytopes gives a new insight on triangulations, with applications to algebraic geometry and group theory [13]. In statistical physics, random tilings lead to some interesting problems dealing with triangulations of order polytopes $[6,29]$ . With these motivations in mind, we introduce new tools: Generalizations of the Ehrhart polynomial (counting points “modulo congruence”), discrete length between integral points (and studying the geometry associated to it), arithmetic Euler-Poincar\'e formula which gives, in dimension 3, the Ehrhart polynomial in terms of the $\mathrm{f}$-vector of a minimal triangulation of the polytope (Theorem 7). Finally, let us mention the results in dimension 2 of the late Peter Greenberg, they led us to the study of “Arithmetical $\mathrm{P}\mathrm{L}$-topology” which, we believe with M. Gromov, D. Sullivan, and P. Vogel, has not yet revealed all its beauties.