Finite Semifields and Nonsingular Tensors
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
An Introduction to Quantum Field Theory
AN INTRODUCTION TO QUANTUM FIELD THEORY By Dr M Dasgupta University of Manchester Lecture presented at the School for Experimental High Energy Physics Students Somerville College, Oxford, September 2009 - 1 - - 2 - Contents 0 Prologue....................................................................................................... 5 1 Introduction ................................................................................................ 6 1.1 Lagrangian formalism in classical mechanics......................................... 6 1.2 Quantum mechanics................................................................................... 8 1.3 The Schrödinger picture........................................................................... 10 1.4 The Heisenberg picture............................................................................ 11 1.5 The quantum mechanical harmonic oscillator ..................................... 12 Problems .............................................................................................................. 13 2 Classical Field Theory............................................................................. 14 2.1 From N-point mechanics to field theory ............................................... 14 2.2 Relativistic field theory ............................................................................ 15 2.3 Action for a scalar field ............................................................................ 15 2.4 Plane wave solution to the Klein-Gordon equation ........................... -
The Quaternionic Commutator Bracket and Its Implications
S S symmetry Article The Quaternionic Commutator Bracket and Its Implications Arbab I. Arbab 1,† and Mudhahir Al Ajmi 2,* 1 Department of Physics, Faculty of Science, University of Khartoum, P.O. Box 321, Khartoum 11115, Sudan; [email protected] 2 Department of Physics, College of Science, Sultan Qaboos University, P.O. Box 36, P.C. 123, Muscat 999046, Sultanate of Oman * Correspondence: [email protected] † Current address: Department of Physics, College of Science, Qassim University, Qassim 51452, Saudi Arabia. Received: 11 August 2018; Accepted: 9 October 2018; Published: 16 October 2018 Abstract: A quaternionic commutator bracket for position and momentum shows that the i ~ quaternionic wave function, viz. ye = ( c y0 , y), represents a state of a particle with orbital angular momentum, L = 3 h¯ , resulting from the internal structure of the particle. This angular momentum can be attributed to spin of the particle. The vector y~ , points in an opposite direction of~L. When a charged particle is placed in an electromagnetic field, the interaction energy reveals that the magnetic moments interact with the electric and magnetic fields giving rise to terms similar to Aharonov–Bohm and Aharonov–Casher effects. Keywords: commutator bracket; quaternions; magnetic moments; angular momentum; quantum mechanics 1. Introduction In quantum mechanics, particles are described by relativistic or non-relativistic wave equations. Each equation associates a spin state of the particle to its wave equation. For instance, the Schrödinger equation applies to the spinless particles in the non-relativistic domain, while the appropriate relativistic equation for spin-0 particles is the Klein–Gordon equation. -
Littlewood–Richardson Coefficients and Birational Combinatorics
Littlewood{Richardson coefficients and birational combinatorics Darij Grinberg 28 August 2020 [corrected version] Algebraic and Combinatorial Perspectives in the Mathematical Sciences slides: http: //www.cip.ifi.lmu.de/~grinberg/algebra/acpms2020.pdf paper: arXiv:2008.06128 aka http: //www.cip.ifi.lmu.de/~grinberg/algebra/lrhspr.pdf 1 / 43 The proof is a nice example of birational combinatorics: the use of birational transformations in elementary combinatorics (specifically, here, in finding and proving a bijection). Manifest I shall review the Littlewood{Richardson coefficients and some of their classical properties. I will then state a \hidden symmetry" conjectured by Pelletier and Ressayre (arXiv:2005.09877) and outline how I proved it. 2 / 43 Manifest I shall review the Littlewood{Richardson coefficients and some of their classical properties. I will then state a \hidden symmetry" conjectured by Pelletier and Ressayre (arXiv:2005.09877) and outline how I proved it. The proof is a nice example of birational combinatorics: the use of birational transformations in elementary combinatorics (specifically, here, in finding and proving a bijection). 2 / 43 Manifest I shall review the Littlewood{Richardson coefficients and some of their classical properties. I will then state a \hidden symmetry" conjectured by Pelletier and Ressayre (arXiv:2005.09877) and outline how I proved it. The proof is a nice example of birational combinatorics: the use of birational transformations in elementary combinatorics (specifically, here, in finding and proving a bijection). 2 / 43 Chapter 1 Chapter 1 Littlewood{Richardson coefficients References (among many): Richard Stanley, Enumerative Combinatorics, vol. 2, Chapter 7. Darij Grinberg, Victor Reiner, Hopf Algebras in Combinatorics, arXiv:1409.8356. -
Commutator Groups of Monomial Groups
Pacific Journal of Mathematics COMMUTATOR GROUPS OF MONOMIAL GROUPS CALVIN VIRGIL HOLMES Vol. 10, No. 4 December 1960 COMMUTATOR GROUPS OF MONOMIAL GROUPS C. V. HOLMES This paper is a study of the commutator groups of certain general- ized permutation groups called complete monomial groups. In [2] Ore has shown that every element of the infinite permutation group is itsself a commutator of this group. Here it is shown that every element of the infinite complete monomial group is the product of at most two commutators of the infinite complete monomial group. The commutator subgroup of the infinite complete monomial group is itself, as is the case in the infinite symmetric group, [2]. The derived series is determined for a wide class of monomial groups. Let H be an arbitrary group, and S a set of order B, B ^ d, cZ = ^0. Then one obtains a monomial group after the manner described in [1], A monomial substitution over H is a linear transformation mapping each element x of S in a one-to-one manner onto some element of S multi- plied by an element h of H, the multiplication being formal. The ele- ment h is termed a factor of the substitution. If substitution u maps xi into hjXj, while substitution v maps xό into htxt, then the substitution uv maps xt into hόhtxt. A substitution all of whose factor are the iden- tity β of H is called a permutation and the set of all permutations is a subgroup which is isomorphic to the symmetric group on B objects. -
Commutator Theory for Congruence Modular Varieties Ralph Freese
Commutator Theory for Congruence Modular Varieties Ralph Freese and Ralph McKenzie Contents Introduction 1 Chapter 1. The Commutator in Groups and Rings 7 Exercise 10 Chapter 2. Universal Algebra 11 Exercises 19 Chapter 3. Several Commutators 21 Exercises 22 Chapter 4. One Commutator in Modular Varieties;Its Basic Properties 25 Exercises 33 Chapter 5. The Fundamental Theorem on Abelian Algebras 35 Exercises 43 Chapter 6. Permutability and a Characterization ofModular Varieties 47 Exercises 49 Chapter 7. The Center and Nilpotent Algebras 53 Exercises 57 Chapter 8. Congruence Identities 59 Exercises 68 Chapter 9. Rings Associated With Modular Varieties: Abelian Varieties 71 Exercises 87 Chapter 10. Structure and Representationin Modular Varieties 89 1. Birkhoff-J´onsson Type Theorems For Modular Varieties 89 2. Subdirectly Irreducible Algebras inFinitely Generated Varieties 92 3. Residually Small Varieties 97 4. Chief Factors and Simple Algebras 102 Exercises 103 Chapter 11. Joins and Products of Modular Varieties 105 Chapter 12. Strictly Simple Algebras 109 iii iv CONTENTS Chapter 13. Mal’cev Conditions for Lattice Equations 115 Exercises 120 Chapter 14. A Finite Basis Result 121 Chapter 15. Pure Lattice Congruence Identities 135 1. The Arguesian Equation 139 Related Literature 141 Solutions To The Exercises 147 Chapter 1 147 Chapter 2 147 Chapter 4 148 Chapter 5 150 Chapter 6 152 Chapter 7 156 Chapter 8 158 Chapter 9 161 Chapter 10 165 Chapter 13 165 Bibliography 169 Index 173 Introduction In the theory of groups, the important concepts of Abelian group, solvable group, nilpotent group, the center of a group and centraliz- ers, are all defined from the binary operation [x, y]= x−1y−1xy. -
Commutator Formulas
Commutator formulas Jack Schmidt This expository note mentions some interesting formulas using commutators. It touches on Hall's collection process and the associated Hall polynomials. It gives an alternative expression that is linear in the number of commutators and shows how to find such a formula using staircase diagrams. It also shows the shortest possible such expression. Future versions could touch on isoperimetric inequalities in geometric group theory, powers of commutators and Culler's identity as well as its effect on Schur's inequality between [G : Z(G)] and jG0j. 1 Powers of products versus products of powers In an abelian group one has (xy)n = xnyn so in a general group one has (xy)n = n n x y dn(x; y) for some product of commutators dn(x; y). This section explores formulas for dn(x; y). 1.1 A nice formula in a special case is given by certain binomial coefficients: n (n) (n) (n) (n) (n) (n) (xy) = x 1 y 1 [y; x] 2 [[y; x]; x] 3 [[[y; x]; x]; x] 4 ··· [y; n−1x] n The special case is G0 is abelian and commutes with y. The commutators involved are built inductively: From y and x, one gets [y; x]. From [y; x] and x, one gets [[y; x]; x]. From [y; n−2x] and x, one gets [y; n−1; x]. In general, one would also need to consider [y; x] and [[y; x]; x], but the special case assumes commutators commute, so [[y; x]; [[y; x]; x]] = 1. In general, one would also need to consider [y; x] and y, but the special case assumes commutators commute with y, so [[y; x]; y] = 1. -
Kernel Methods for Knowledge Structures
Kernel Methods for Knowledge Structures Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften der Universität Karlsruhe (TH) genehmigte DISSERTATION von Dipl.-Inform.-Wirt. Stephan Bloehdorn Tag der mündlichen Prüfung: 10. Juli 2008 Referent: Prof. Dr. Rudi Studer Koreferent: Prof. Dr. Dr. Lars Schmidt-Thieme 2008 Karlsruhe Abstract Kernel methods constitute a new and popular field of research in the area of machine learning. Kernel-based machine learning algorithms abandon the explicit represen- tation of data items in the vector space in which the sought-after patterns are to be detected. Instead, they implicitly mimic the geometry of the feature space by means of the kernel function, a similarity function which maintains a geometric interpreta- tion as the inner product of two vectors. Knowledge structures and ontologies allow to formally model domain knowledge which can constitute valuable complementary information for pattern discovery. For kernel-based machine learning algorithms, a good way to make such prior knowledge about the problem domain available to a machine learning technique is to incorporate it into the kernel function. This thesis studies the design of such kernel functions. First, this thesis provides a theoretical analysis of popular similarity functions for entities in taxonomic knowledge structures in terms of their suitability as kernel func- tions. It shows that, in a general setting, many taxonomic similarity functions can not be guaranteed to yield valid kernel functions and discusses the alternatives. Secondly, the thesis addresses the design of expressive kernel functions for text mining applications. A first group of kernel functions, Semantic Smoothing Kernels (SSKs) retain the Vector Space Models (VSMs) representation of textual data as vec- tors of term weights but employ linguistic background knowledge resources to bias the original inner product in such a way that cross-term similarities adequately con- tribute to the kernel result. -
Geometry, Combinatorial Designs and Cryptology Fourth Pythagorean Conference
Geometry, Combinatorial Designs and Cryptology Fourth Pythagorean Conference Sunday 30 May to Friday 4 June 2010 Index of Talks and Abstracts Main talks 1. Simeon Ball, On subsets of a finite vector space in which every subset of basis size is a basis 2. Simon Blackburn, Honeycomb arrays 3. G`abor Korchm`aros, Curves over finite fields, an approach from finite geometry 4. Cheryl Praeger, Basic pregeometries 5. Bernhard Schmidt, Finiteness of circulant weighing matrices of fixed weight 6. Douglas Stinson, Multicollision attacks on iterated hash functions Short talks 1. Mari´en Abreu, Adjacency matrices of polarity graphs and of other C4–free graphs of large size 2. Marco Buratti, Combinatorial designs via factorization of a group into subsets 3. Mike Burmester, Lightweight cryptographic mechanisms based on pseudorandom number generators 4. Philippe Cara, Loops, neardomains, nearfields and sets of permutations 5. Ilaria Cardinali, On the structure of Weyl modules for the symplectic group 6. Bill Cherowitzo, Parallelisms of quadrics 7. Jan De Beule, Large maximal partial ovoids of Q−(5, q) 8. Bart De Bruyn, On extensions of hyperplanes of dual polar spaces 1 9. Frank De Clerck, Intriguing sets of partial quadrangles 10. Alice Devillers, Symmetry properties of subdivision graphs 11. Dalibor Froncek, Decompositions of complete bipartite graphs into generalized prisms 12. Stelios Georgiou, Self-dual codes from circulant matrices 13. Robert Gilman, Cryptology of infinite groups 14. Otokar Groˇsek, The number of associative triples in a quasigroup 15. Christoph Hering, Latin squares, homologies and Euler’s conjecture 16. Leanne Holder, Bilinear star flocks of arbitrary cones 17. Robert Jajcay, On the geometry of cages 18. -
Parametrizations of Canonical Bases and Totally Positive Matrices Arkady Berenstein
Advances in Mathematics AI1567 advances in mathematics 122, 49149 (1996) article no. 0057 Parametrizations of Canonical Bases and Totally Positive Matrices Arkady Berenstein Department of Mathematics, Northeastern University, Boston, Massachusetts 02115 Sergey Fomin* Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139; and Theory of Algorithms Laboratory, St. Petersburg Institute of Informatics, Russian Academy of Sciences, St. Petersburg, Russia and Andrei Zelevinsky- Department of Mathematics, Northeastern University, Boston, Massachusetts 02115 Received October 24, 1995; accepted November 27, 1995 Contents. 1. Introduction and main results. 2. Lusztig variety and Chamber Ansatz. 2.1. Semifields and subtraction-free rational expressions. 2.2. Lusztig variety. 2.3. Pseudo-line arrangements. 2.4. Minors and the nilTemperleyLieb algebra. 2.5. Chamber Ansatz. 2.6. Solutions of the 3-term relations. 2.7. An alternative description of the Lusztig variety. 2.8. Trans- 0 n n ition from n . 2.9. Polynomials T J and Za . 2.10. Formulas for T J . 2.11. Sym- metries of the Lusztig variety. 3. Total positivity criteria. 3.1. Factorization of unitriangular matrices. 3.2. General- izations of Fekete's criterion. 3.3. Polynomials TJ (x). 3.4. The action of the four- group on N >0. 3.5. The multi-filtration in the coordinate ring of N. 3.6. The S3 _ZÂ2Z symmetry. 3.7. Dual canonical basis and positivity theorem. 4. Piecewise-linear minimization formulas. 4.1. Polynomials over the tropical semi- field. 4.2. Multisegment duality. 4.3. Nested normal orderings. 4.4. Quivers and boundary pseudo-line arrangements. 5. The case of an arbitrary permutation. -
2.2 Kernel and Range of a Linear Transformation
2.2 Kernel and Range of a Linear Transformation Performance Criteria: 2. (c) Determine whether a given vector is in the kernel or range of a linear trans- formation. Describe the kernel and range of a linear transformation. (d) Determine whether a transformation is one-to-one; determine whether a transformation is onto. When working with transformations T : Rm → Rn in Math 341, you found that any linear transformation can be represented by multiplication by a matrix. At some point after that you were introduced to the concepts of the null space and column space of a matrix. In this section we present the analogous ideas for general vector spaces. Definition 2.4: Let V and W be vector spaces, and let T : V → W be a transformation. We will call V the domain of T , and W is the codomain of T . Definition 2.5: Let V and W be vector spaces, and let T : V → W be a linear transformation. • The set of all vectors v ∈ V for which T v = 0 is a subspace of V . It is called the kernel of T , And we will denote it by ker(T ). • The set of all vectors w ∈ W such that w = T v for some v ∈ V is called the range of T . It is a subspace of W , and is denoted ran(T ). It is worth making a few comments about the above: • The kernel and range “belong to” the transformation, not the vector spaces V and W . If we had another linear transformation S : V → W , it would most likely have a different kernel and range. -
23. Kernel, Rank, Range
23. Kernel, Rank, Range We now study linear transformations in more detail. First, we establish some important vocabulary. The range of a linear transformation f : V ! W is the set of vectors the linear transformation maps to. This set is also often called the image of f, written ran(f) = Im(f) = L(V ) = fL(v)jv 2 V g ⊂ W: The domain of a linear transformation is often called the pre-image of f. We can also talk about the pre-image of any subset of vectors U 2 W : L−1(U) = fv 2 V jL(v) 2 Ug ⊂ V: A linear transformation f is one-to-one if for any x 6= y 2 V , f(x) 6= f(y). In other words, different vector in V always map to different vectors in W . One-to-one transformations are also known as injective transformations. Notice that injectivity is a condition on the pre-image of f. A linear transformation f is onto if for every w 2 W , there exists an x 2 V such that f(x) = w. In other words, every vector in W is the image of some vector in V . An onto transformation is also known as an surjective transformation. Notice that surjectivity is a condition on the image of f. 1 Suppose L : V ! W is not injective. Then we can find v1 6= v2 such that Lv1 = Lv2. Then v1 − v2 6= 0, but L(v1 − v2) = 0: Definition Let L : V ! W be a linear transformation. The set of all vectors v such that Lv = 0W is called the kernel of L: ker L = fv 2 V jLv = 0g: 1 The notions of one-to-one and onto can be generalized to arbitrary functions on sets. -
Hamilton Equations, Commutator, and Energy Conservation †
quantum reports Article Hamilton Equations, Commutator, and Energy Conservation † Weng Cho Chew 1,* , Aiyin Y. Liu 2 , Carlos Salazar-Lazaro 3 , Dong-Yeop Na 1 and Wei E. I. Sha 4 1 College of Engineering, Purdue University, West Lafayette, IN 47907, USA; [email protected] 2 College of Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; [email protected] 3 Physics Department, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; [email protected] 4 College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310058, China; [email protected] * Correspondence: [email protected] † Based on the talk presented at the 40th Progress In Electromagnetics Research Symposium (PIERS, Toyama, Japan, 1–4 August 2018). Received: 12 September 2019; Accepted: 3 December 2019; Published: 9 December 2019 Abstract: We show that the classical Hamilton equations of motion can be derived from the energy conservation condition. A similar argument is shown to carry to the quantum formulation of Hamiltonian dynamics. Hence, showing a striking similarity between the quantum formulation and the classical formulation. Furthermore, it is shown that the fundamental commutator can be derived from the Heisenberg equations of motion and the quantum Hamilton equations of motion. Also, that the Heisenberg equations of motion can be derived from the Schrödinger equation for the quantum state, which is the fundamental postulate. These results are shown to have important bearing for deriving the quantum Maxwell’s equations. Keywords: quantum mechanics; commutator relations; Heisenberg picture 1. Introduction In quantum theory, a classical observable, which is modeled by a real scalar variable, is replaced by a quantum operator, which is analogous to an infinite-dimensional matrix operator.