Connections Between Graph Theory, Additive Combinatorics, and Finite
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Structure, Classification, and Conformal Symmetry, of Elementary
Lett Math Phys (2009) 89:171–182 DOI 10.1007/s11005-009-0351-2 Structure, Classification, and Conformal Symmetry, of Elementary Particles over Non-Archimedean Space–Time V. S. VARADARAJAN and JUKKA VIRTANEN Department of Mathematics, UCLA, Los Angeles, CA 90095-1555, USA. e-mail: [email protected]; [email protected] Received: 3 April 2009 / Revised: 12 September 2009 / Accepted: 12 September 2009 Publishedonline:23September2009–©TheAuthor(s)2009. This article is published with open access at Springerlink.com Abstract. It is known that no length or time measurements are possible in sub-Planckian regions of spacetime. The Volovich hypothesis postulates that the micro-geometry of space- time may therefore be assumed to be non-archimedean. In this letter, the consequences of this hypothesis for the structure, classification, and conformal symmetry of elementary particles, when spacetime is a flat space over a non-archimedean field such as the p-adic numbers, is explored. Both the Poincare´ and Galilean groups are treated. The results are based on a new variant of the Mackey machine for projective unitary representations of semidirect product groups which are locally compact and second countable. Conformal spacetime is constructed over p-adic fields and the impossibility of conformal symmetry of massive and eventually massive particles is proved. Mathematics Subject Classification (2000). 22E50, 22E70, 20C35, 81R05. Keywords. Volovich hypothesis, non-archimedean fields, Poincare´ group, Galilean group, semidirect product, cocycles, affine action, conformal spacetime, conformal symmetry, massive, eventually massive, massless particles. 1. Introduction In the 1970s many physicists, concerned about the divergences in quantum field theories, started exploring the micro-structure of space–time itself as a possible source of these problems. -
Study Guide for the Midterm. Topics: • Euclid • Incidence Geometry • Perspective Geometry • Neutral Geometry – Through Oct.18Th
Study guide for the midterm. Topics: • Euclid • Incidence geometry • Perspective geometry • Neutral geometry { through Oct.18th. You need to { Know definitions and examples. { Know theorems by names. { Be able to give a simple proof and justify every step. { Be able to explain those of Euclid's statements and proofs that appeared in the book, the problem set, the lecture, or the tutorial. Sources: • Class Notes • Problem Sets • Assigned reading • Notes on course website. The test. • Excerpts from Euclid will be provided if needed. • The incidence axioms will be provided if needed. • Postulates of neutral geometry will be provided if needed. • There will be at least one question that is similar or identical to a homework question. Tentative large list of terms. For each of the following terms, you should be able to write two sentences, in which you define it, state it, explain it, or discuss it. Euclid's geometry: - Euclid's definition of \right angle". - Euclid's definition of \parallel lines". - Euclid's \postulates" versus \common notions". - Euclid's working with geometric magnitudes rather than real numbers. - Congruence of segments and angles. - \All right angles are equal". - Euclid's fifth postulate. - \The whole is bigger than the part". - \Collapsing compass". - Euclid's reliance on diagrams. - SAS; SSS; ASA; AAS. - Base angles of an isosceles triangle. - Angles below the base of an isosceles triangle. - Exterior angle inequality. - Alternate interior angle theorem and its converse (we use the textbook's convention). - Vertical angle theorem. - The triangle inequality. - Pythagorean theorem. Incidence geometry: - collinear points. - concurrent lines. - Simple theorems of incidence geometry. - Interpretation/model for a theory. -
Arxiv:1609.06355V1 [Cs.CC] 20 Sep 2016 Outlaw Distributions And
Outlaw distributions and locally decodable codes Jop Bri¨et∗ Zeev Dvir† Sivakanth Gopi‡ September 22, 2016 Abstract Locally decodable codes (LDCs) are error correcting codes that allow for decoding of a single message bit using a small number of queries to a corrupted encoding. De- spite decades of study, the optimal trade-off between query complexity and codeword length is far from understood. In this work, we give a new characterization of LDCs using distributions over Boolean functions whose expectation is hard to approximate (in L∞ norm) with a small number of samples. We coin the term ‘outlaw distribu- tions’ for such distributions since they ‘defy’ the Law of Large Numbers. We show that the existence of outlaw distributions over sufficiently ‘smooth’ functions implies the existence of constant query LDCs and vice versa. We also give several candidates for outlaw distributions over smooth functions coming from finite field incidence geometry and from hypergraph (non)expanders. We also prove a useful lemma showing that (smooth) LDCs which are only required to work on average over a random message and a random message index can be turned into true LDCs at the cost of only constant factors in the parameters. 1 Introduction Error correcting codes (ECCs) solve the basic problem of communication over noisy channels. They encode a message into a codeword from which, even if the channel partially corrupts it, arXiv:1609.06355v1 [cs.CC] 20 Sep 2016 the message can later be retrieved. With one of the earliest applications of the probabilistic method, formally introduced by Erd˝os in 1947, pioneering work of Shannon [Sha48] showed the existence of optimal (capacity-achieving) ECCs. -
Noncommutative Geometry and the Spectral Model of Space-Time
S´eminaire Poincar´eX (2007) 179 – 202 S´eminaire Poincar´e Noncommutative geometry and the spectral model of space-time Alain Connes IHES´ 35, route de Chartres 91440 Bures-sur-Yvette - France Abstract. This is a report on our joint work with A. Chamseddine and M. Marcolli. This essay gives a short introduction to a potential application in physics of a new type of geometry based on spectral considerations which is convenient when dealing with noncommutative spaces i.e. spaces in which the simplifying rule of commutativity is no longer applied to the coordinates. Starting from the phenomenological Lagrangian of gravity coupled with matter one infers, using the spectral action principle, that space-time admits a fine structure which is a subtle mixture of the usual 4-dimensional continuum with a finite discrete structure F . Under the (unrealistic) hypothesis that this structure remains valid (i.e. one does not have any “hyperfine” modification) until the unification scale, one obtains a number of predictions whose approximate validity is a basic test of the approach. 1 Background Our knowledge of space-time can be summarized by the transition from the flat Minkowski metric ds2 = − dt2 + dx2 + dy2 + dz2 (1) to the Lorentzian metric 2 µ ν ds = gµν dx dx (2) of curved space-time with gravitational potential gµν . The basic principle is the Einstein-Hilbert action principle Z 1 √ 4 SE[ gµν ] = r g d x (3) G M where r is the scalar curvature of the space-time manifold M. This action principle only accounts for the gravitational forces and a full account of the forces observed so far requires the addition of new fields, and of corresponding new terms SSM in the action, which constitute the Standard Model so that the total action is of the form, S = SE + SSM . -
Keith E. Mellinger
Keith E. Mellinger Department of Mathematics home University of Mary Washington 1412 Kenmore Avenue 1301 College Avenue, Trinkle Hall Fredericksburg, VA 22401 Fredericksburg, VA 22401-5300 (540) 368-3128 ph: (540) 654-1333, fax: (540) 654-2445 [email protected] http://www.keithmellinger.com/ Professional Experience • Director of the Quality Enhancement Plan, 2013 { present. UMW. • Professor of Mathematics, 2014 { present. Department of Mathematics, UMW. • Interim Director, Office of Academic and Career Services, Fall 2013 { Spring 2014. UMW. • Associate Professor, 2008 { 2014. Department of Mathematics, UMW. • Department Chair, 2008 { 2013. Department of Mathematics, UMW. • Assistant Professor, 2003 { 2008. Department of Mathematics, UMW. • Research Assistant Professor (Vigre post-doc), 2001 - 2003. Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, 60607-7045. Position partially funded by a VIGRE grant from the National Science Foundation. Education • Ph.D. in Mathematics: August 2001, University of Delaware, Newark, DE. { Thesis: Mixed Partitions and Spreads of Projective Spaces • M.S. in Mathematics: May 1997, University of Delaware. • B.S. in Mathematics: May 1995, Millersville University, Millersville, PA. { minor in computer science, option in statistics Grants and Awards • Millersville University Outstanding Young Alumni Achievement Award, presented by the alumni association at MU, May 2013. • Mathematical Association of America's Carl B. Allendoerfer Award for the article, -
Finite Projective Geometries 243
FINITE PROJECTÎVEGEOMETRIES* BY OSWALD VEBLEN and W. H. BUSSEY By means of such a generalized conception of geometry as is inevitably suggested by the recent and wide-spread researches in the foundations of that science, there is given in § 1 a definition of a class of tactical configurations which includes many well known configurations as well as many new ones. In § 2 there is developed a method for the construction of these configurations which is proved to furnish all configurations that satisfy the definition. In §§ 4-8 the configurations are shown to have a geometrical theory identical in most of its general theorems with ordinary projective geometry and thus to afford a treatment of finite linear group theory analogous to the ordinary theory of collineations. In § 9 reference is made to other definitions of some of the configurations included in the class defined in § 1. § 1. Synthetic definition. By a finite projective geometry is meant a set of elements which, for sugges- tiveness, are called points, subject to the following five conditions : I. The set contains a finite number ( > 2 ) of points. It contains subsets called lines, each of which contains at least three points. II. If A and B are distinct points, there is one and only one line that contains A and B. HI. If A, B, C are non-collinear points and if a line I contains a point D of the line AB and a point E of the line BC, but does not contain A, B, or C, then the line I contains a point F of the line CA (Fig. -
1 Definition and Models of Incidence Geometry
1 Definition and Models of Incidence Geometry (1.1) Definition (geometry) A geometry is a set S of points and a set L of lines together with relationships between the points and lines. p 2 1. Find four points which belong to set M = f(x;y) 2 R jx = 5g: 2. Let M = f(x;y)jx;y 2 R;x < 0g: p (i) Find three points which belong to set N = f(x;y) 2 Mjx = 2g. − 4 L f 2 Mj 1 g (ii) Are points P (3;3), Q(6;4) and R( 2; 3 ) belong to set = (x;y) y = 3 x + 2 ? (1.2) Definition (Cartesian Plane) L Let E be the set of all vertical and non-vertical lines, La and Lk;n where vertical lines: f 2 2 j g La = (x;y) R x = a; a is fixed real number ; non-vertical lines: f 2 2 j g Lk;n = (x;y) R y = kx + n; k and n are fixed real numbers : C f 2 L g The model = R ; E is called the Cartesian Plane. C f 2 L g 3. Let = R ; E denote Cartesian Plane. (i) Find three different points which belong to Cartesian vertical line L7. (ii) Find three different points which belong to Cartesian non-vertical line L15;p2. C f 2 L g 4. Let P be some point in Cartesian Plane = R ; E . Show that point P cannot lie simultaneously on both L and L (where a a ). a a0 , 0 (1.3) Definition (Poincar´ePlane) L Let H be the set of all type I and type II lines, aL and pLr where type I lines: f 2 j g aL = (x;y) H x = a; a is a fixed real number ; type II lines: f 2 j − 2 2 2 2 g pLr = (x;y) H (x p) + y = r ; p and r are fixed R, r > 0 ; 2 H = f(x;y) 2 R jy > 0g: H f L g The model = H; H will be called the Poincar´ePlane. -
ON the POLYHEDRAL GEOMETRY of T–DESIGNS
ON THE POLYHEDRAL GEOMETRY OF t{DESIGNS A thesis presented to the faculty of San Francisco State University In partial fulfilment of The Requirements for The Degree Master of Arts In Mathematics by Steven Collazos San Francisco, California August 2013 Copyright by Steven Collazos 2013 CERTIFICATION OF APPROVAL I certify that I have read ON THE POLYHEDRAL GEOMETRY OF t{DESIGNS by Steven Collazos and that in my opinion this work meets the criteria for approving a thesis submitted in partial fulfillment of the requirements for the degree: Master of Arts in Mathematics at San Francisco State University. Matthias Beck Associate Professor of Mathematics Felix Breuer Federico Ardila Associate Professor of Mathematics ON THE POLYHEDRAL GEOMETRY OF t{DESIGNS Steven Collazos San Francisco State University 2013 Lisonek (2007) proved that the number of isomorphism types of t−(v; k; λ) designs, for fixed t, v, and k, is quasi{polynomial in λ. We attempt to describe a region in connection with this result. Specifically, we attempt to find a region F of Rd with d the following property: For every x 2 R , we have that jF \ Gxj = 1, where Gx denotes the G{orbit of x under the action of G. As an application, we argue that our construction could help lead to a new combinatorial reciprocity theorem for the quasi{polynomial counting isomorphism types of t − (v; k; λ) designs. I certify that the Abstract is a correct representation of the content of this thesis. Chair, Thesis Committee Date ACKNOWLEDGMENTS I thank my advisors, Dr. Matthias Beck and Dr. -
Matroid Enumeration for Incidence Geometry
Discrete Comput Geom (2012) 47:17–43 DOI 10.1007/s00454-011-9388-y Matroid Enumeration for Incidence Geometry Yoshitake Matsumoto · Sonoko Moriyama · Hiroshi Imai · David Bremner Received: 30 August 2009 / Revised: 25 October 2011 / Accepted: 4 November 2011 / Published online: 30 November 2011 © Springer Science+Business Media, LLC 2011 Abstract Matroids are combinatorial abstractions for point configurations and hy- perplane arrangements, which are fundamental objects in discrete geometry. Matroids merely encode incidence information of geometric configurations such as collinear- ity or coplanarity, but they are still enough to describe many problems in discrete geometry, which are called incidence problems. We investigate two kinds of inci- dence problem, the points–lines–planes conjecture and the so-called Sylvester–Gallai type problems derived from the Sylvester–Gallai theorem, by developing a new algo- rithm for the enumeration of non-isomorphic matroids. We confirm the conjectures of Welsh–Seymour on ≤11 points in R3 and that of Motzkin on ≤12 lines in R2, extend- ing previous results. With respect to matroids, this algorithm succeeds to enumerate a complete list of the isomorph-free rank 4 matroids on 10 elements. When geometric configurations corresponding to specific matroids are of interest in some incidence problems, they should be analyzed on oriented matroids. Using an encoding of ori- ented matroid axioms as a boolean satisfiability (SAT) problem, we also enumerate oriented matroids from the matroids of rank 3 on n ≤ 12 elements and rank 4 on n ≤ 9 elements. We further list several new minimal non-orientable matroids. Y. Matsumoto · H. Imai Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan Y. -
Set Theory. • Sets Have Elements, Written X ∈ X, and Subsets, Written a ⊆ X. • the Empty Set ∅ Has No Elements
Set theory. • Sets have elements, written x 2 X, and subsets, written A ⊆ X. • The empty set ? has no elements. • A function f : X ! Y takes an element x 2 X and returns an element f(x) 2 Y . The set X is its domain, and Y is its codomain. Every set X has an identity function idX defined by idX (x) = x. • The composite of functions f : X ! Y and g : Y ! Z is the function g ◦ f defined by (g ◦ f)(x) = g(f(x)). • The function f : X ! Y is a injective or an injection if, for every y 2 Y , there is at most one x 2 X such that f(x) = y (resp. surjective, surjection, at least; bijective, bijection, exactly). In other words, f is a bijection if and only if it is both injective and surjective. Being bijective is equivalent to the existence of an inverse function f −1 such −1 −1 that f ◦ f = idY and f ◦ f = idX . • An equivalence relation on a set X is a relation ∼ such that { (reflexivity) for every x 2 X, x ∼ x; { (symmetry) for every x; y 2 X, if x ∼ y, then y ∼ x; and { (transitivity) for every x; y; z 2 X, if x ∼ y and y ∼ z, then x ∼ z. The equivalence class of x 2 X under the equivalence relation ∼ is [x] = fy 2 X : x ∼ yg: The distinct equivalence classes form a partition of X, i.e., every element of X is con- tained in a unique equivalence class. Incidence geometry. -
Math 431 Solutions to Homework 3
Math 431 Solutions to Homework 3 1. Show that the following familiar interpretation is a model for incidence geometry. Note that in class we already showed that Axiom I-1 is satisfied, so you only need to show that I-2 and I-3 are satisfied. • The “points” are all ordered pairs (x, y) of real numbers. • A “line” is specified by an ordered triple (a, b, c) of real numbers such that either a 6= 0 or b 6= 0; it is defined as the set of all “points” (x, y) that satisfy the equation ax + by + c = 0. • “Incidence” is defined as set membership. Proof that I-1 is satisfied. This is an expanded version of what was done in class. Let P = (x1, y1) and Q = (x2, y2) be two distinct points. We need to show that there is a unique line passing through both of them. Case 1: Suppose that x1 = x2. In this case the line given by the equation x = x1 (1) passes through P and Q (since (x1, y1) and (x2, y2) satisfy this equation). To show that this line is unique, suppose we are given any line l passing through P and Q. Let ax + by + c = 0 be an equation for l. Since P and Q satisfy this equation, ax1 + by1 + c = 0, and ax2 + by2 + c = 0. Now we have ax1 + by1 + c = ax2 + by2 + c ⇐⇒ ax1 + by1 = ax2 + by2 ⇐⇒ ax1 − ax2 = by2 − by1 ⇐⇒ −a(x2 − x1) = b(y2 − y1). We know that y1 6= y2 (because x1 = x2 and P 6= Q). -
An Introduction to Finite Geometry
An introduction to Finite Geometry Geertrui Van de Voorde Ghent University, Belgium Pre-ICM International Convention on Mathematical Sciences Delhi INCIDENCE STRUCTURES EXAMPLES I Designs I Graphs I Linear spaces I Polar spaces I Generalised polygons I Projective spaces I ... Points, vertices, lines, blocks, edges, planes, hyperplanes . + incidence relation PROJECTIVE SPACES Many examples are embeddable in a projective space. V : Vector space PG(V ): Corresponding projective space FROM VECTOR SPACE TO PROJECTIVE SPACE FROM VECTOR SPACE TO PROJECTIVE SPACE The projective dimension of a projective space is the dimension of the corresponding vector space minus 1 PROPERTIES OF A PG(V ) OF DIMENSION d (1) Through every two points, there is exactly one line. PROPERTIES OF A PG(V ) OF DIMENSION d (2) Every two lines in one plane intersect, and they intersect in exactly one point. (3) There are d + 2 points such that no d + 1 of them are contained in a (d − 1)-dimensional projective space PG(d − 1, q). DEFINITION If d = 2, a space satisfying (1)-(2)-(3) is called a projective plane. WHICH SPACES SATISFY (1)-(2)-(3)? THEOREM (VEBLEN-YOUNG 1916) If d ≥ 3, a space satisfying (1)-(2)-(3) is a d-dimensional PG(V ). WHICH SPACES SATISFY (1)-(2)-(3)? THEOREM (VEBLEN-YOUNG 1916) If d ≥ 3, a space satisfying (1)-(2)-(3) is a d-dimensional PG(V ). DEFINITION If d = 2, a space satisfying (1)-(2)-(3) is called a projective plane. PROJECTIVE PLANES Points, lines and three axioms (a) ∀r 6= s ∃!L (b) ∀L 6= M ∃!r (c) ∃r, s, t, u If Π is a projective plane, then interchanging points and lines, we obtain the dual plane ΠD.