Index HANDBOOK of MATHEMATICS
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INTRODUCTION to ALGEBRAIC TOPOLOGY 1 Category And
INTRODUCTION TO ALGEBRAIC TOPOLOGY (UPDATED June 2, 2020) SI LI AND YU QIU CONTENTS 1 Category and Functor 2 Fundamental Groupoid 3 Covering and fibration 4 Classification of covering 5 Limit and colimit 6 Seifert-van Kampen Theorem 7 A Convenient category of spaces 8 Group object and Loop space 9 Fiber homotopy and homotopy fiber 10 Exact Puppe sequence 11 Cofibration 12 CW complex 13 Whitehead Theorem and CW Approximation 14 Eilenberg-MacLane Space 15 Singular Homology 16 Exact homology sequence 17 Barycentric Subdivision and Excision 18 Cellular homology 19 Cohomology and Universal Coefficient Theorem 20 Hurewicz Theorem 21 Spectral sequence 22 Eilenberg-Zilber Theorem and Kunneth¨ formula 23 Cup and Cap product 24 Poincare´ duality 25 Lefschetz Fixed Point Theorem 1 1 CATEGORY AND FUNCTOR 1 CATEGORY AND FUNCTOR Category In category theory, we will encounter many presentations in terms of diagrams. Roughly speaking, a diagram is a collection of ‘objects’ denoted by A, B, C, X, Y, ··· , and ‘arrows‘ between them denoted by f , g, ··· , as in the examples f f1 A / B X / Y g g1 f2 h g2 C Z / W We will always have an operation ◦ to compose arrows. The diagram is called commutative if all the composite paths between two objects ultimately compose to give the same arrow. For the above examples, they are commutative if h = g ◦ f f2 ◦ f1 = g2 ◦ g1. Definition 1.1. A category C consists of 1◦. A class of objects: Obj(C) (a category is called small if its objects form a set). We will write both A 2 Obj(C) and A 2 C for an object A in C. -
The Mathematical Sciences at Clemson
BIOMATHEMATICS IS The Geometry of Biological Time m Arthur Winfree, Purdue University The Geometry of Biological Time explains periodic processes in living systems >< and their nonliving analogues in the abstract terms of systems theory. Emphasis is on phase singularities, waves, and mutual synchronization in -n tissues composed of many clocklike units. Also provided are detailed de- )5-._U scriptions of the most commonly used experimental systems, such as electrical oscillations and waves, circadian clocks, the cell division cycle, and the crystal-like regularities observed in the regeneration of severed limbs. z No theoretical background is assumed: required notions are introduced through an extensive collection of illustrations and easily understood o examples. 1979/approx. 576 pp./290 lllus./Cioth $32.00 _ (Biomathematics. Volume 8) ISBN 0-387-09373-7 z Mathematical Population Genetics G) Warren J. Ewens, University of Pennsylvania, Philadelphia Presents the mathematical theory of population genetics with emphasis on those aspects relevant to evolutionary studies. The opening chapter pro- vides an excellent general historical and biological background. Subsequent chapters treat deterministic and stochastic models, discrete and continuous time processes, theory concerning classical and molecular aspects, and one, two, and many loci in a concise and comprehensive manner, with ample references to additional literature. An essential working guide for population geneticists interested in the mathematical foundations of their field and mathematicians involved in genetic evolutionary processes. 1979/ approx. 330 pp./ 4111us/17 Tables/ Cloth $32.00 (Biomathematics. Volume 9) ISBN 0-387-09577-2 Diffusion and Ecological Problems: M~thematical Models Akira Okubo, State University of New York, Stony Brook The first comprehensive book on mathematical models of diffusion in an ecological context. -
Notes for Math 227A: Algebraic Topology
NOTES FOR MATH 227A: ALGEBRAIC TOPOLOGY KO HONDA 1. CATEGORIES AND FUNCTORS 1.1. Categories. A category C consists of: (1) A collection ob(C) of objects. (2) A set Hom(A, B) of morphisms for each ordered pair (A, B) of objects. A morphism f ∈ Hom(A, B) f is usually denoted by f : A → B or A → B. (3) A map Hom(A, B) × Hom(B,C) → Hom(A, C) for each ordered triple (A,B,C) of objects, denoted (f, g) 7→ gf. (4) An identity morphism idA ∈ Hom(A, A) for each object A. The morphisms satisfy the following properties: A. (Associativity) (fg)h = f(gh) if h ∈ Hom(A, B), g ∈ Hom(B,C), and f ∈ Hom(C, D). B. (Unit) idB f = f = f idA if f ∈ Hom(A, B). Examples: (HW: take a couple of examples and verify that all the axioms of a category are satisfied.) 1. Top = category of topological spaces and continuous maps. The objects are topological spaces X and the morphisms Hom(X,Y ) are continuous maps from X to Y . 2. Top• = category of pointed topological spaces. The objects are pairs (X,x) consisting of a topological space X and a point x ∈ X. Hom((X,x), (Y,y)) consist of continuous maps from X to Y that take x to y. Similarly define Top2 = category of pairs (X, A) where X is a topological space and A ⊂ X is a subspace. Hom((X, A), (Y,B)) consists of continuous maps f : X → Y such that f(A) ⊂ B. -
Arxiv:0704.1009V1 [Math.KT] 8 Apr 2007 Odo References
LECTURES ON DERIVED AND TRIANGULATED CATEGORIES BEHRANG NOOHI These are the notes of three lectures given in the International Workshop on Noncommutative Geometry held in I.P.M., Tehran, Iran, September 11-22. The first lecture is an introduction to the basic notions of abelian category theory, with a view toward their algebraic geometric incarnations (as categories of modules over rings or sheaves of modules over schemes). In the second lecture, we motivate the importance of chain complexes and work out some of their basic properties. The emphasis here is on the notion of cone of a chain map, which will consequently lead to the notion of an exact triangle of chain complexes, a generalization of the cohomology long exact sequence. We then discuss the homotopy category and the derived category of an abelian category, and highlight their main properties. As a way of formalizing the properties of the cone construction, we arrive at the notion of a triangulated category. This is the topic of the third lecture. Af- ter presenting the main examples of triangulated categories (i.e., various homo- topy/derived categories associated to an abelian category), we discuss the prob- lem of constructing abelian categories from a given triangulated category using t-structures. A word on style. In writing these notes, we have tried to follow a lecture style rather than an article style. This means that, we have tried to be very concise, keeping the explanations to a minimum, but not less (hopefully). The reader may find here and there certain remarks written in small fonts; these are meant to be side notes that can be skipped without affecting the flow of the material. -
Lecture Notes on Simplicial Homotopy Theory
Lectures on Homotopy Theory The links below are to pdf files, which comprise my lecture notes for a first course on Homotopy Theory. I last gave this course at the University of Western Ontario during the Winter term of 2018. The course material is widely applicable, in fields including Topology, Geometry, Number Theory, Mathematical Pysics, and some forms of data analysis. This collection of files is the basic source material for the course, and this page is an outline of the course contents. In practice, some of this is elective - I usually don't get much beyond proving the Hurewicz Theorem in classroom lectures. Also, despite the titles, each of the files covers much more material than one can usually present in a single lecture. More detail on topics covered here can be found in the Goerss-Jardine book Simplicial Homotopy Theory, which appears in the References. It would be quite helpful for a student to have a background in basic Algebraic Topology and/or Homological Algebra prior to working through this course. J.F. Jardine Office: Middlesex College 118 Phone: 519-661-2111 x86512 E-mail: [email protected] Homotopy theories Lecture 01: Homological algebra Section 1: Chain complexes Section 2: Ordinary chain complexes Section 3: Closed model categories Lecture 02: Spaces Section 4: Spaces and homotopy groups Section 5: Serre fibrations and a model structure for spaces Lecture 03: Homotopical algebra Section 6: Example: Chain homotopy Section 7: Homotopical algebra Section 8: The homotopy category Lecture 04: Simplicial sets Section 9: -
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces∗†
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces∗y Benjamin Paaßen Christina Göpfert Barbara Hammer This is a preprint of the publication [46] as provided by the authors. The original can be found at the DOI 10.1007/s11063-017-9684-5. Abstract Graph models are relevant in many fields, such as distributed com- puting, intelligent tutoring systems or social network analysis. In many cases, such models need to take changes in the graph structure into ac- count, i.e. a varying number of nodes or edges. Predicting such changes within graphs can be expected to yield important insight with respect to the underlying dynamics, e.g. with respect to user behaviour. However, predictive techniques in the past have almost exclusively focused on sin- gle edges or nodes. In this contribution, we attempt to predict the future state of a graph as a whole. We propose to phrase time series prediction as a regression problem and apply dissimilarity- or kernel-based regression techniques, such as 1-nearest neighbor, kernel regression and Gaussian process regression, which can be applied to graphs via graph kernels. The output of the regression is a point embedded in a pseudo-Euclidean space, which can be analyzed using subsequent dissimilarity- or kernel-based pro- cessing methods. We discuss strategies to speed up Gaussian Processes regression from cubic to linear time and evaluate our approach on two well-established theoretical models of graph evolution as well as two real data sets from the domain of intelligent tutoring systems. We find that simple regression methods, such as kernel regression, are sufficient to cap- ture the dynamics in the theoretical models, but that Gaussian process regression significantly improves the prediction error for real-world data. -
Global Existence for Quasilinear Diffusion Equations in Nondivergence Form
GLOBAL EXISTENCE FOR QUASILINEAR DIFFUSION EQUATIONS IN NONDIVERGENCE FORM WOLFGANG ARENDT AND RALPH CHILL A. We consider the quasilinear parabolic equation u β(t, x, u, u)∆u = f (t, x, u, u) t − ∇ ∇ in a cylindrical domain, together with initial-boundary conditions, where the quasilinearity operates on the diffusion coefficient of the Laplacian. Un- der suitable conditions we prove global existence of a solution in the energy space. Our proof depends on maximal regularity of a nonautonomous lin- ear parabolic equation which we use to provide us with compactness in order to apply Schaefer’s fixed point theorem. 1. I We prove global existence of a solution of the quasilinear diffusion prob- lem u β(t, x, u, u)∆u = f (t, x, u, u) in (0, ) Ω, t − ∇ ∇ ∞ × (1) u = 0 in (0, ) ∂Ω, ∞ × u(0, ) = u0( ) in Ω, · · where Ω Rd is an open set, u H1(Ω) and ⊂ 0 ∈ 0 1 β : (0, ) Ω R1+d [ε, ](ε (0, 1) is fixed) and ∞ × × → ε ∈ f : (0, ) Ω R1+d R ∞ × × → are measurable functions which are continuous with respect to the last vari- able, for every (t, x) (0, ) Ω. The function f satisfies in addition a linear growth condition with∈ respect∞ × to the last variable. We prove in fact existence of a solution in the space H1 ([0, ); L2(Ω)) L2 ([0, ); D(∆ )) C([0, ); H1(Ω)), loc ∞ ∩ loc ∞ D ∩ ∞ 0 2 where D(∆D) is the domain of the Dirichlet-Laplacian in L (Ω). Date: October 21, 2008. 2000 Mathematics Subject Classification. 35P05, 35J70, 35K65. -
The Complexity of Prime Number Tests
Die approbierte Originalversion dieser Diplom-/ Masterarbeit ist in der Hauptbibliothek der Tech- nischen Universität Wien aufgestellt und zugänglich. http://www.ub.tuwien.ac.at The approved original version of this diploma or master thesis is available at the main library of the Vienna University of Technology. http://www.ub.tuwien.ac.at/eng The Complexity of Prime Number Tests Diplomarbeit Ausgeführt am Institut für Diskrete Mathematik und Geometrie der Technischen Universität Wien unter der Anleitung von Univ.Prof. Dipl.-Ing. Dr.techn. Michael Drmota durch Theres Steiner, BSc Matrikelnummer: 01025110 Ort, Datum Unterschrift (Student) Unterschrift (Betreuer) The problem of distinguishing prime numbers from composite numbers and of re- solving the latter into their prime factors is known to be one of the most important and useful in arithmetic. Carl Friedrich Gauss, Disquisitiones Arithmeticae, 1801 Ron and Hermione have 2 children: Rose and Hugo. Vogon poetry is the 3rd worst in the universe. Acknowledgements First, I would like to thank my parents, Rudolf and Doris Steiner, without them I would not be where I am now. I would also like to thank my professor Michael Drmota for supporting me and helping me with my thesis. Throughout the writing process he was always there for me and his input was always helpful. I would also like to thank my colleagues who made this stage of my life truly amazing. Also, a special thanks to the people that gave me valuable input on my thesis, mathematically or grammatically. 4 5 is the 5th digit in π. Abstract Prime numbers have been a signicant focus of mathematics throughout the years. -
Functional Analysis TMA401/MMA400
Functional analysis TMA401/MMA400 Peter Kumlin 2018-09-21 1 Course diary — What has happened? Week 1 Discussion of introductory example, see section 1. Definition of real/complex vector space, remark on existence of unique zero vector and inverse vectors, example of real vector spaces (sequence spaces and function spaces). Hölder and Minkowski inequal- ities. Introducing (the to all students very well-known concepts) linear combination, linear independence, span of a set, (vector space-) basis (= Hamel basis) with examples. All vector spaces have basis (using Axiom of choice/Zorn’s lemma; it was not proven but stated). Introducing norms on vector spaces with examples, equivalent norms, con- vergence of sequences in normed spaces, showed that C([0; 1]) can be equipped with norms that are not equivalent. Stated and proved that all norms on finite-dimensional vector spaces are equivalent. A proof of this is supplied below. Also mentioned that all infinte-dimensional vector spaces can be equipped with norms that are not equivalent (easy to prove once we have a Hamel basis). Theorem 0.1. Suppose E is a vector space with dim(E) < 1. Then all norms on E are equivalent. Proof: We observe that the relation that two norms are equivalent is transitive, so it is enough to show that an arbitrary norm k · k on E is equivalent to a fixed norm k · k∗ on E. Let x1; x2; : : : ; xn, where n = dim(E), be a basis for E. This means that for every x 2 E there are uniquely defined scalars αk(x), k = 1; 2; : : : ; n, such that x = α1(x)x1 + α2(x)x2 + ::: + αn(x)xn: Set kxk∗ = jα1(x)j + jα2(x)j + ::: jαn(x)j for x 2 E. -
The Balance Sheet and the Assets-Claims on Assets Relationship in the Axiomatic Method
WSEAS TRANSACTIONS on MATHEMATICS Fernando Juárez The Balance Sheet and the Assets-Claims on Assets Relationship in the Axiomatic Method FERNANDO JUÁREZ Escuela de Administración Universidad del Rosario Autopista Norte, No. 200 COLOMBIA [email protected] Abstract: - The purpose of this study is to analyze the set structure of the balance sheet and assets-claims on assets relationship, considering the dual concept of monetary units, the axiomatic theory and accounting- specific axioms. The structure of the balance sheet and assets-claims on assets relationship are examined using a rationalistic, analytical and deductive method ; this method uses the axiomatic set theory and predicate logic to define a set of axioms and the logical rationale to apply them to any deductive proof. The method includes accounting primitives and axioms to use in combination with those of the axiomatic theory. A direct proof is applied to test the balance sheet fit to a hereditary set structure according to the axiomatic theory, and proof by contraposition is employed to examine the assets-claims on assets equality by comparing their elements. Results show that balance sheet has a set structure that can be defined and analyzed with the axiomatic method and fits a hereditary set structure. Also, by comparing the elements of assets and claims on assets and considering their financial classification, it is shown that these sets do not contain the same elements and, consequently, they are not equal under the postulates of the axiomatic method. Key-Words: Dual concept, accounting transactions, axiomatic method, assets, claims on assets, balance sheet. 1 Introduction difficulties in understanding the applications of this This paper addresses the issue of identifying a set method. -
1. Harmonic Functions 2. Perron's Method 3. Potential Theor
Elliptic and Parabolic Equations by J. Hulshof Elliptic equations: 1. Harmonic functions 2. Perron’s method 3. Potential theory 4. Existence results; the method of sub- and supersolutions 5. Classical maximum principles for elliptic equations 6. More regularity, Schauder’s theory for general elliptic operators 7. The weak solution approach in one space dimension 8. Eigenfunctions for the Sturm-Liouville problem 9. Generalization to more dimensions Parabolic equations: 10. Maximum principles for parabolic equations 11. Potential theory and existence results 12. Asymptotic behaviour of solutions to the semilinear heat equation Functional Analysis: A. Banach spaces B. Hilbert spaces C. Continous semigroups and Liapounov functionals 1 1. Harmonic functions Throughout this section, Ω ⊂ Rn is a bounded domain. 1.1 Definition A function u ∈ C2(Ω) is called subharmonic if ∆u ≥ 0 in Ω, harmonic if ∆u ≡ 0 in Ω, and superharmonic if ∆u ≤ 0 in Ω. 1.2 Notation The measure of the unit ball in Rn is Z n/2 n 2 2 2π ωn = |B1| = |{x ∈ R : x1 + ... + xn ≤ 1}| = dx = . B1 nΓ(n/2) The (n − 1)-dimensional measure of the boundary ∂B1 of B1 is equal to nωn. 1.3 Mean Value Theorem Let u ∈ C2(Ω) be subharmonic, and n BR(y) = {x ∈ R : |x − y| ≤ R} ⊂ Ω. Then 1 Z u(y) ≤ n−1 u(x)dS(x), nωnR ∂BR(y) where dS is the (n − 1)-dimensional surface element on ∂BR(y). Also 1 Z u(y) ≤ n u(x)dx. ωnR BR(y) Equalities hold if u is harmonic. Proof We may assume y = 0. -
Vector Space and Affine Space
Preliminary Mathematics of Geometric Modeling (1) Hongxin Zhang & Jieqing Feng State Key Lab of CAD&CG Zhejiang University Contents Coordinate Systems Vector and Affine Spaces Vector Spaces Points and Vectors Affine Combinations, Barycentric Coordinates and Convex Combinations Frames 11/20/2006 State Key Lab of CAD&CG 2 Coordinate Systems Cartesian coordinate system 11/20/2006 State Key Lab of CAD&CG 3 Coordinate Systems Frame Origin O Three Linear-Independent r rur Vectors ( uvw ,, ) 11/20/2006 State Key Lab of CAD&CG 4 Vector Spaces Definition A nonempty set ς of elements is called a vector space if in ς there are two algebraic operations, namely addition and scalar multiplication Examples of vector space Linear Independence and Bases 11/20/2006 State Key Lab of CAD&CG 5 Vector Spaces Addition Addition associates with every pair of vectors and a unique vector which is called the sum of and and is written For 2D vectors, the summation is componentwise, i.e., if and , then 11/20/2006 State Key Lab of CAD&CG 6 Vector Spaces Addition parallelogram illustration 11/20/2006 State Key Lab of CAD&CG 7 Addition Properties Commutativity Associativity Zero Vector Additive Inverse Vector Subtraction 11/20/2006 State Key Lab of CAD&CG 8 Commutativity for any two vectors and in ς , 11/20/2006 State Key Lab of CAD&CG 9 Associativity for any three vectors , and in ς, 11/20/2006 State Key Lab of CAD&CG 10 Zero Vector There is a unique vector in ς called the zero vector and denoted such that for every vector 11/20/2006 State Key Lab of CAD&CG 11 Additive