Two-Level Polytopes with a Prescribed Facet
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1 Lifts of Polytopes
Lecture 5: Lifts of polytopes and non-negative rank CSE 599S: Entropy optimality, Winter 2016 Instructor: James R. Lee Last updated: January 24, 2016 1 Lifts of polytopes 1.1 Polytopes and inequalities Recall that the convex hull of a subset X n is defined by ⊆ conv X λx + 1 λ x0 : x; x0 X; λ 0; 1 : ( ) f ( − ) 2 2 [ ]g A d-dimensional convex polytope P d is the convex hull of a finite set of points in d: ⊆ P conv x1;:::; xk (f g) d for some x1;:::; xk . 2 Every polytope has a dual representation: It is a closed and bounded set defined by a family of linear inequalities P x d : Ax 6 b f 2 g for some matrix A m d. 2 × Let us define a measure of complexity for P: Define γ P to be the smallest number m such that for some C s d ; y s ; A m d ; b m, we have ( ) 2 × 2 2 × 2 P x d : Cx y and Ax 6 b : f 2 g In other words, this is the minimum number of inequalities needed to describe P. If P is full- dimensional, then this is precisely the number of facets of P (a facet is a maximal proper face of P). Thinking of γ P as a measure of complexity makes sense from the point of view of optimization: Interior point( methods) can efficiently optimize linear functions over P (to arbitrary accuracy) in time that is polynomial in γ P . ( ) 1.2 Lifts of polytopes Many simple polytopes require a large number of inequalities to describe. -
Understanding the Formation of Pbse Honeycomb Superstructures by Dynamics Simulations
PHYSICAL REVIEW X 9, 021015 (2019) Understanding the Formation of PbSe Honeycomb Superstructures by Dynamics Simulations Giuseppe Soligno* and Daniel Vanmaekelbergh Condensed Matter and Interfaces, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, Utrecht 3584 CC, Netherlands (Received 28 October 2018; revised manuscript received 28 January 2019; published 23 April 2019) Using a coarse-grained molecular dynamics model, we simulate the self-assembly of PbSe nanocrystals (NCs) adsorbed at a flat fluid-fluid interface. The model includes all key forces involved: NC-NC short- range facet-specific attractive and repulsive interactions, entropic effects, and forces due to the NC adsorption at fluid-fluid interfaces. Realistic values are used for the input parameters regulating the various forces. The interface-adsorption parameters are estimated using a recently introduced sharp- interface numerical method which includes capillary deformation effects. We find that the final structure in which the NCs self-assemble is drastically affected by the input values of the parameters of our coarse- grained model. In particular, by slightly tuning just a few parameters of the model, we can induce NC self- assembly into either silicene-honeycomb superstructures, where all NCs have a f111g facet parallel to the fluid-fluid interface plane, or square superstructures, where all NCs have a f100g facet parallel to the interface plane. Both of these nanostructures have been observed experimentally. However, it is still not clear their formation mechanism, and, in particular, which are the factors directing the NC self-assembly into one or another structure. In this work, we identify and quantify such factors, showing illustrative assembled-phase diagrams obtained from our simulations. -
Topics in Algorithmic, Enumerative and Geometric Combinatorics
Thesis for the Degree of Doctor of Philosophy Topics in algorithmic, enumerative and geometric combinatorics Ragnar Freij Division of Mathematics Department of Mathematical Sciences Chalmers University of Technology and University of Gothenburg G¨oteborg, Sweden 2012 Topics in algorithmic, enumerative and geometric combinatorics Ragnar Freij ISBN 978-91-7385-668-3 c Ragnar Freij, 2012. Doktorsavhandlingar vid Chalmers Tekniska H¨ogskola Ny serie Nr 3349 ISSN 0346-718X Department of Mathematical Sciences Chalmers University of Technology and University of Gothenburg SE-412 96 GOTEBORG,¨ Sweden Phone: +46 (0)31-772 10 00 [email protected] Printed in G¨oteborg, Sweden, 2012 Topics in algorithmic, enumerative and geometric com- binatorics Ragnar Freij ABSTRACT This thesis presents five papers, studying enumerative and extremal problems on combinatorial structures. The first paper studies Forman’s discrete Morse theory in the case where a group acts on the underlying complex. We generalize the notion of a Morse matching, and obtain a theory that can be used to simplify the description of the G-homotopy type of a simplicial complex. As an application, we determine the S2 × Sn−2-homotopy type of the complex of non-connected graphs on n nodes. In the introduction, connections are drawn between the first paper and the evasiveness conjecture for monotone graph properties. In the second paper, we investigate Hansen polytopes of split graphs. By applying a partitioning technique, the number of nonempty faces is counted, and in particular we confirm Kalai’s 3d-conjecture for such polytopes. Further- more, a characterization of exactly which Hansen polytopes are also Hanner polytopes is given. -
The Minkowski Problem for Simplices
The Minkowski Problem for Simplices Daniel A. Klain Department of Mathematical Sciences University of Massachusetts Lowell Lowell, MA 01854 USA Daniel [email protected] Abstract The Minkowski existence Theorem for polytopes follows from Cramer’s Rule when attention is limited to the special case of simplices. It is easy to see that a convex polygon in R2 is uniquely determined (up to translation) by the directions and lengths of its edges. This suggests the following (less easily answered) question in higher dimensions: given a collection of proposed facet normals and facet areas, is there a convex polytope in Rn whose facets fit the given data, and, if so, is the resulting polytope unique? This question (along with its answer) is known as the Minkowski problem. For a polytope P in Rn denote by V (P ) the volume of P . If Q is a polytope in Rn having dimension strictly less than n, then denote v(Q) the (n ¡ 1)-dimensional volume of Q. For any u non-zero vector u, let P denote the face of P having u as an outward normal, and let Pu denote the orthogonal projection of P onto the hyperplane u?. The Minkowski problem for polytopes concerns the following specific question: Given a collection u1; : : : ; uk of unit vectors and ®1; : : : ; ®k > 0, under what condition does there exist a polytope P ui having the ui as its facet normals and the ®i as its facet areas; that is, such that v(P ) = ®i for each i? A necessary condition on the facet normals and facet areas is given by the following proposition [BF48, Sch93]. -
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 . -
Frequently Asked Questions in Polyhedral Computation
Frequently Asked Questions in Polyhedral Computation http://www.ifor.math.ethz.ch/~fukuda/polyfaq/polyfaq.html Komei Fukuda Swiss Federal Institute of Technology Lausanne and Zurich, Switzerland [email protected] Version June 18, 2004 Contents 1 What is Polyhedral Computation FAQ? 2 2 Convex Polyhedron 3 2.1 What is convex polytope/polyhedron? . 3 2.2 What are the faces of a convex polytope/polyhedron? . 3 2.3 What is the face lattice of a convex polytope . 4 2.4 What is a dual of a convex polytope? . 4 2.5 What is simplex? . 4 2.6 What is cube/hypercube/cross polytope? . 5 2.7 What is simple/simplicial polytope? . 5 2.8 What is 0-1 polytope? . 5 2.9 What is the best upper bound of the numbers of k-dimensional faces of a d- polytope with n vertices? . 5 2.10 What is convex hull? What is the convex hull problem? . 6 2.11 What is the Minkowski-Weyl theorem for convex polyhedra? . 6 2.12 What is the vertex enumeration problem, and what is the facet enumeration problem? . 7 1 2.13 How can one enumerate all faces of a convex polyhedron? . 7 2.14 What computer models are appropriate for the polyhedral computation? . 8 2.15 How do we measure the complexity of a convex hull algorithm? . 8 2.16 How many facets does the average polytope with n vertices in Rd have? . 9 2.17 How many facets can a 0-1 polytope with n vertices in Rd have? . 10 2.18 How hard is it to verify that an H-polyhedron PH and a V-polyhedron PV are equal? . -
Plenary Lectures
Plenary lectures A. D. Alexandrov and the Birth of the Theory of Tight Surfaces Thomas Banchoff Brown University, Providence, Rhode Island 02912, USA e-mail: Thomas [email protected] Alexander Danilovich Alexandrov was born in 1912, and just over 25 years later in 1938 (the year of my birth), he proved a rigidity theorem for real analytic surfaces of type T with minimal total absolute curvature. He showed in particular that that two real analytic tori of Type T in three-space that are iso- metric must be congruent. In 1963, twenty-five years after that original paper, Louis Nirenberg wrote the first generalization of that result, for five times differentiable surfaces satisfying some technical hypothe- ses necessary for applying techniques of ordinary and partial differential equations. Prof. Shiing-Shen Chern, my thesis advisor at the University of California, Berkeley, gave me this paper to present to his graduate seminar and challenged me to find a proof without these technical hypotheses. I read Konvexe Polyeder by A. D. Alexandrov and the works of Pogoreloff on rigidity for convex surfaces using polyhedral methods and I decided to try to find a rigidity theorem for Type T surfaces using similar techniques. I found a condition equivalent to minimal total absolute curvature for smooth surfaces, that also applied to polyhedral surfaces, namely the Two-Piece Property or TPP. An object in three- space has the TPP if every plane separates the object into at most two connected pieces. I conjectured a rigidity result similar to those of Alexandroff and Nirenberg, namely that two polyhedral surfaces in three-space with the TPP that are isometric would have to be congruent. -
A Note on Solid Coloring of Pure Simplicial Complexes Joseph O'rourke Smith College, [email protected]
Masthead Logo Smith ScholarWorks Computer Science: Faculty Publications Computer Science 12-17-2010 A Note on Solid Coloring of Pure Simplicial Complexes Joseph O'Rourke Smith College, [email protected] Follow this and additional works at: https://scholarworks.smith.edu/csc_facpubs Part of the Computer Sciences Commons, and the Discrete Mathematics and Combinatorics Commons Recommended Citation O'Rourke, Joseph, "A Note on Solid Coloring of Pure Simplicial Complexes" (2010). Computer Science: Faculty Publications, Smith College, Northampton, MA. https://scholarworks.smith.edu/csc_facpubs/37 This Article has been accepted for inclusion in Computer Science: Faculty Publications by an authorized administrator of Smith ScholarWorks. For more information, please contact [email protected] A Note on Solid Coloring of Pure Simplicial Complexes Joseph O'Rourke∗ December 21, 2010 Abstract We establish a simple generalization of a known result in the plane. d The simplices in any pure simplicial complex in R may be colored with d+1 colors so that no two simplices that share a (d−1)-facet have the same 2 color. In R this says that any planar map all of whose faces are triangles 3 may be 3-colored, and in R it says that tetrahedra in a collection may be \solid 4-colored" so that no two glued face-to-face receive the same color. 1 Introduction The famous 4-color theorem says that the regions of any planar map may be colored with four colors such that no two regions that share a positive-length border receive the same color. A lesser-known special case is that if all the regions are triangles, three colors suffice. -
Linear Programming and Polyhedral Combinatorics Summary of What Was Seen in the Introductory Lectures on Linear Programming and Polyhedral Combinatorics
Massachusetts Institute of Technology Handout 8 18.433: Combinatorial Optimization March 6th, 2007 Michel X. Goemans Linear Programming and Polyhedral Combinatorics Summary of what was seen in the introductory lectures on linear programming and polyhedral combinatorics. Definition 1 A halfspace in Rn is a set of the form fx 2 Rn : aT x ≤ bg for some vector a 2 Rn and b 2 R. Definition 2 A polyhedron is the intersection of finitely many halfspaces: P = fx 2 Rn : Ax ≤ bg. Definition 3 A polytope is a bounded polyhedron. n Definition 4 If P is a polyhedron in R , the projection Pk of P is defined as fy = (x1; x2; · · · ; xk−1; xk+1; · · · ; xn) : x 2 P for some xkg. We claim that Pk is also a polyhedron and this can be proved by giving an explicit description of Pk in terms of linear inequalities. For this purpose, one uses Fourier-Motzkin elimination. Let P = fx : Ax ≤ bg and let • S+ = fi : aik > 0g, • S− = fi : aik < 0g, • S0 = fi : aik = 0g. T Clearly, any element in Pk must satisfy the inequality ai x ≤ bi for all i 2 S0 (these inequal- ities do not involve xk). Similarly, we can take a linear combination of an inequality in S+ and one in S− to eliminate the coefficient of xk. This shows that the inequalities: aik aljxj − alk akjxj ≤ aikbl − alkbi (1) j ! j ! X X for i 2 S+ and l 2 S− are satisfied by all elements of Pk. Conversely, for any vector (x1; x2; · · · ; xk−1; xk+1; · · · ; xn) satisfying (1) for all i 2 S+ and l 2 S− and also T ai x ≤ bi for all i 2 S0 (2) we can find a value of xk such that the resulting x belongs to P (by looking at the bounds on xk that each constraint imposes, and showing that the largest lower bound is smaller than the smallest upper bound). -
Model Reduction in Geometric Tolerancing by Polytopes Vincent Delos, Santiago Arroyave-Tobón, Denis Teissandier
Model reduction in geometric tolerancing by polytopes Vincent Delos, Santiago Arroyave-Tobón, Denis Teissandier To cite this version: Vincent Delos, Santiago Arroyave-Tobón, Denis Teissandier. Model reduction in geometric tolerancing by polytopes. Computer-Aided Design, Elsevier, 2018. hal-01741395 HAL Id: hal-01741395 https://hal.archives-ouvertes.fr/hal-01741395 Submitted on 23 Mar 2018 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. Model reduction in geometric tolerancing by polytopes Vincent Delos, Santiago Arroyave-Tobon,´ Denis Teissandier Univ. Bordeaux, I2M, UMR 5295, F-33400 Talence, France Abstract There are several models used in mechanical design to study the behavior of mechanical systems involving geometric variations. By simulating defects with sets of constraints it is possible to study simultaneously all the configurations of mechanisms, whether over-constrained or not. Using this method, the accumulation of defects is calculated by summing sets of constraints derived from features (toleranced surfaces and joints) in the tolerance chain. These sets are usually unbounded objects (R6-polyhedra, 3 parameters for the small rotation, 3 for the small translation), due to the unbounded displacements associated with the degrees of freedom of features. -
Minimal Volume Product of Three Dimensional Convex Bodies with Various Discrete Symmetries
Minimal volume product of three dimensional convex bodies with various discrete symmetries Hiroshi Iriyeh ∗ Masataka Shibata † August 12, 2021 Abstract We give the sharp lower bound of the volume product of three dimensional convex bodies which are invariant under a discrete subgroup of O(3) in several cases. We also characterize the convex bodies with the minimal volume product in each case. In particular, this provides a new partial result of the non-symmetric version of Mahler’s conjecture in the three dimensional case. 1 Introduction and main results 1.1 Mahler’s conjecture and its generalization Let K be a convex body in Rn, i.e, K is a compact convex set in Rn with nonempty interior. Then K ⊂ Rn is said to be centrally symmetric if it satisfies that K = −K. Denote by Kn the set of all convex bodies in Rn equipped with the Hausdorff metric and n n by K0 the set of all K ∈ K which are centrally symmetric. The interior of K ∈ Kn is denoted by int K. For a point z ∈ int K, the polar body of K with respect to z is defined by z n K = {y ∈ R ;(y − z) · (x − z) ≤ 1 for any x ∈ K} , where · denotes the standard inner product on Rn. Then an affine invariant P(K) := min |K| |Kz| (1) z∈int K is called volume product of K, where |K| denotes the n-dimensional volume of K in Rn. arXiv:2007.08736v2 [math.MG] 8 Oct 2020 It is known that for each K ∈ Kn the minimum of (1) is attained at the unique point z on K, which is called Santaló point of K (see, e.g., [13]). -
Convex Hull in Higher Dimensions
Comp 163: Computational Geometry Professor Diane Souvaine Tufts University, Spring 2005 1991 Scribe: Gabor M. Czako, 1990 Scribe: Sesh Venugopal, 2004 Scrib Higher Dimensional Convex Hull Algorithms 1 Convex hulls 1.0.1 Definitions The following definitions will be used throughout. Define • Sd:Ad-Simplex The simplest convex polytope in Rd.Ad-simplex is always the convex hull of some d + 1 affinely independent points. For example, a line segment is a 1 − simplex i.e., the smallest convex subspace which con- tains two points. A triangle is a 2 − simplex and a tetrahedron is a 3 − simplex. • P: A Simplicial Polytope. A polytope where each facet is a d − 1 simplex. By our assumption, a convex hull in 3-D has triangular facets and in 4-D, a convex hull has tetrahedral facets. •P: number of facets of Pi • F : a facet of P • R:aridgeofF • G:afaceofP d+1 • fj(Pi ): The number of j-faces of P .Notethatfj(Sd)=C(j+1). 1.0.2 An Upper Bound on Time Complexity: Cyclic Polytope d 1 2 d Consider the curve Md in R defined as x(t)=(t ,t , ..., t ), t ∈ R.LetH be the hyperplane defined as a0 + a1x1 + a2x2 + ... + adxd = 0. The intersection 2 d of Md and H is the set of points that satisfy a0 + a1t + a2t + ...adt =0. This polynomial has at most d real roots and therefore d real solutions. → H intersects Md in at most d points. This brings us to the following definition: A convex polytope in Rd is a cyclic polytope if it is the convex hull of a 1 set of at least d +1pointsonMd.