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Formal Power Series - Wikipedia, the Free Encyclopedia
Formal power series - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Formal_power_series Formal power series From Wikipedia, the free encyclopedia In mathematics, formal power series are a generalization of polynomials as formal objects, where the number of terms is allowed to be infinite; this implies giving up the possibility to substitute arbitrary values for indeterminates. This perspective contrasts with that of power series, whose variables designate numerical values, and which series therefore only have a definite value if convergence can be established. Formal power series are often used merely to represent the whole collection of their coefficients. In combinatorics, they provide representations of numerical sequences and of multisets, and for instance allow giving concise expressions for recursively defined sequences regardless of whether the recursion can be explicitly solved; this is known as the method of generating functions. Contents 1 Introduction 2 The ring of formal power series 2.1 Definition of the formal power series ring 2.1.1 Ring structure 2.1.2 Topological structure 2.1.3 Alternative topologies 2.2 Universal property 3 Operations on formal power series 3.1 Multiplying series 3.2 Power series raised to powers 3.3 Inverting series 3.4 Dividing series 3.5 Extracting coefficients 3.6 Composition of series 3.6.1 Example 3.7 Composition inverse 3.8 Formal differentiation of series 4 Properties 4.1 Algebraic properties of the formal power series ring 4.2 Topological properties of the formal power series -
5. Polynomial Rings Let R Be a Commutative Ring. a Polynomial of Degree N in an Indeterminate (Or Variable) X with Coefficients
5. polynomial rings Let R be a commutative ring. A polynomial of degree n in an indeterminate (or variable) x with coefficients in R is an expression of the form f = f(x)=a + a x + + a xn, 0 1 ··· n where a0, ,an R and an =0.Wesaythata0, ,an are the coefficients of f and n ··· ∈ ̸ ··· that anx is the highest degree term of f. A polynomial is determined by its coeffiecients. m i n i Two polynomials f = i=0 aix and g = i=1 bix are equal if m = n and ai = bi for i =0, 1, ,n. ! ! Degree··· of a polynomial is a non-negative integer. The polynomials of degree zero are just the elements of R, these are called constant polynomials, or simply constants. Let R[x] denote the set of all polynomials in the variable x with coefficients in R. The addition and 2 multiplication of polynomials are defined in the usual manner: If f(x)=a0 + a1x + a2x + a x3 + and g(x)=b + b x + b x2 + b x3 + are two elements of R[x], then their sum is 3 ··· 0 1 2 3 ··· f(x)+g(x)=(a + b )+(a + b )x +(a + b )x2 +(a + b )x3 + 0 0 1 1 2 2 3 3 ··· and their product is defined by f(x) g(x)=a b +(a b + a b )x +(a b + a b + a b )x2 +(a b + a b + a b + a b )x3 + · 0 0 0 1 1 0 0 2 1 1 2 0 0 3 1 2 2 1 3 0 ··· Let 1 denote the constant polynomial 1 and 0 denote the constant polynomial zero. -
Computations in Algebraic Geometry with Macaulay 2
Computations in algebraic geometry with Macaulay 2 Editors: D. Eisenbud, D. Grayson, M. Stillman, and B. Sturmfels Preface Systems of polynomial equations arise throughout mathematics, science, and engineering. Algebraic geometry provides powerful theoretical techniques for studying the qualitative and quantitative features of their solution sets. Re- cently developed algorithms have made theoretical aspects of the subject accessible to a broad range of mathematicians and scientists. The algorith- mic approach to the subject has two principal aims: developing new tools for research within mathematics, and providing new tools for modeling and solv- ing problems that arise in the sciences and engineering. A healthy synergy emerges, as new theorems yield new algorithms and emerging applications lead to new theoretical questions. This book presents algorithmic tools for algebraic geometry and experi- mental applications of them. It also introduces a software system in which the tools have been implemented and with which the experiments can be carried out. Macaulay 2 is a computer algebra system devoted to supporting research in algebraic geometry, commutative algebra, and their applications. The reader of this book will encounter Macaulay 2 in the context of concrete applications and practical computations in algebraic geometry. The expositions of the algorithmic tools presented here are designed to serve as a useful guide for those wishing to bring such tools to bear on their own problems. A wide range of mathematical scientists should find these expositions valuable. This includes both the users of other programs similar to Macaulay 2 (for example, Singular and CoCoA) and those who are not interested in explicit machine computations at all. -
Formal Power Series Rings, Inverse Limits, and I-Adic Completions of Rings
Formal power series rings, inverse limits, and I-adic completions of rings Formal semigroup rings and formal power series rings We next want to explore the notion of a (formal) power series ring in finitely many variables over a ring R, and show that it is Noetherian when R is. But we begin with a definition in much greater generality. Let S be a commutative semigroup (which will have identity 1S = 1) written multi- plicatively. The semigroup ring of S with coefficients in R may be thought of as the free R-module with basis S, with multiplication defined by the rule h k X X 0 0 X X 0 ( risi)( rjsj) = ( rirj)s: i=1 j=1 s2S 0 sisj =s We next want to construct a much larger ring in which infinite sums of multiples of elements of S are allowed. In order to insure that multiplication is well-defined, from now on we assume that S has the following additional property: (#) For all s 2 S, f(s1; s2) 2 S × S : s1s2 = sg is finite. Thus, each element of S has only finitely many factorizations as a product of two k1 kn elements. For example, we may take S to be the set of all monomials fx1 ··· xn : n (k1; : : : ; kn) 2 N g in n variables. For this chocie of S, the usual semigroup ring R[S] may be identified with the polynomial ring R[x1; : : : ; xn] in n indeterminates over R. We next construct a formal semigroup ring denoted R[[S]]: we may think of this ring formally as consisting of all functions from S to R, but we shall indicate elements of the P ring notationally as (possibly infinite) formal sums s2S rss, where the function corre- sponding to this formal sum maps s to rs for all s 2 S. -
Math Matters
MATH MATTERS CORNELL UNIVERSITY JANUARY 2020 Letter From The Chair Ravi Ramakrishna ’88 s is the case every year, our beginning of their first year with Department (along with all others studentsA and faculty are participat- their advisor, in the College) recently reclassi- ing a rich tapestry of mathematical and then as fied all its courses under the new events and scholarship. From needed. This system, with two falling under running conferences and summer often meant the Statistics and Data Science schools to supervising undergradu- never. The new (SDS) heading and the rest under ate research to (of course) proving model has a the Symbolic and Mathematical wonderful theorems, Cornell math- group of 10 first Reasoning (SMR) heading. We are ematicians at all levels are doing semester stu- curious to see how the new clas- great things. dents meeting sifications and requirements will Ravi Ramakrishna As you will read throughout with their advisor affect our enrollments, especially this issue of Math Matters, they once a week for 9 weeks. The at the first-year and sophomore are also being recognized for their intent is to orient students to the levels. outstanding accomplishments. College and break down the barri- Speaking of enrollments, we Our faculty have in the last year ers between faculty and students. will this year graduate about 95 won two College-wide teaching 2019 was the first year where the math majors. We now have the awards, three National Science seminar served all incoming A&S fifth most majors in the College. Foundation CAREER awards, a students and seven Math faculty Our enrollments at junior and Sloan Fellowship, two Simons participated. -
The Method of Coalgebra: Exercises in Coinduction
The Method of Coalgebra: exercises in coinduction Jan Rutten CWI & RU [email protected] Draft d.d. 8 July 2018 (comments are welcome) 2 Draft d.d. 8 July 2018 Contents 1 Introduction 7 1.1 The method of coalgebra . .7 1.2 History, roughly and briefly . .7 1.3 Exercises in coinduction . .8 1.4 Enhanced coinduction: algebra and coalgebra combined . .8 1.5 Universal coalgebra . .8 1.6 How to read this book . .8 1.7 Acknowledgements . .9 2 Categories { where coalgebra comes from 11 2.1 The basic definitions . 11 2.2 Category theory in slogans . 12 2.3 Discussion . 16 3 Algebras and coalgebras 19 3.1 Algebras . 19 3.2 Coalgebras . 21 3.3 Discussion . 23 4 Induction and coinduction 25 4.1 Inductive and coinductive definitions . 25 4.2 Proofs by induction and coinduction . 28 4.3 Discussion . 32 5 The method of coalgebra 33 5.1 Basic types of coalgebras . 34 5.2 Coalgebras, systems, automata ::: ....................... 34 6 Dynamical systems 37 6.1 Homomorphisms of dynamical systems . 38 6.2 On the behaviour of dynamical systems . 41 6.3 Discussion . 44 3 4 Draft d.d. 8 July 2018 7 Stream systems 45 7.1 Homomorphisms and bisimulations of stream systems . 46 7.2 The final system of streams . 52 7.3 Defining streams by coinduction . 54 7.4 Coinduction: the bisimulation proof method . 59 7.5 Moessner's Theorem . 66 7.6 The heart of the matter: circularity . 72 7.7 Discussion . 76 8 Deterministic automata 77 8.1 Basic definitions . 78 8.2 Homomorphisms and bisimulations of automata . -
Coalgebras from Formulas
Coalgebras from Formulas Serban Raianu California State University Dominguez Hills Department of Mathematics 1000 E Victoria St Carson, CA 90747 e-mail:[email protected] Abstract Nichols and Sweedler showed in [5] that generic formulas for sums may be used for producing examples of coalgebras. We adopt a slightly different point of view, and show that the reason why all these constructions work is the presence of certain representative functions on some (semi)group. In particular, the indeterminate in a polynomial ring is a primitive element because the identity function is representative. Introduction The title of this note is borrowed from the title of the second section of [5]. There it is explained how each generic addition formula naturally gives a formula for the action of the comultiplication in a coalgebra. Among the examples chosen in [5], this situation is probably best illus- trated by the following two: Let C be a k-space with basis {s, c}. We define ∆ : C −→ C ⊗ C and ε : C −→ k by ∆(s) = s ⊗ c + c ⊗ s ∆(c) = c ⊗ c − s ⊗ s ε(s) = 0 ε(c) = 1. 1 Then (C, ∆, ε) is a coalgebra called the trigonometric coalgebra. Now let H be a k-vector space with basis {cm | m ∈ N}. Then H is a coalgebra with comultiplication ∆ and counit ε defined by X ∆(cm) = ci ⊗ cm−i, ε(cm) = δ0,m. i=0,m This coalgebra is called the divided power coalgebra. Identifying the “formulas” in the above examples is not hard: the for- mulas for sin and cos applied to a sum in the first example, and the binomial formula in the second one. -
Revised August 2014 DAVID EISENBUD VITA Born April 8, 1947
Revised August 2014 DAVID EISENBUD VITA Born April 8, 1947, New York City US Citizen Married, with two children EDUCATION B. S. University of Chicago 1966 M. S. University of Chicago 1967 Ph. D. University of Chicago 1970 Advisors: Saunders MacLane, J. C. Robson Thesis: Torsion Modules over Dedekind Prime Rings POSITIONS HELD Lecturer, Brandeis University 1970{72 Assistant Professor, Brandeis University 1972{73 Sloan Foundation Fellow 1973{75 Visiting scholar, Harvard University 1973{74 Fellow, I. H. E. S. (Bures-Sur-Yvette) 1974{75 Associate Professor, Brandeis University 1976{80 Visiting Researcher, University of Bonn (SFB 40) 1979{80 Professor, Brandeis University 1980{1998 Research Professor, Mathematical Sciences Research Institute, Berkeley 1986{87 Visiting Professor, Harvard University 1987{88 and Fall 1994 Chercheur Associ´e`al'Institut Henri Poincar´e(CNRS), Paris, Spring 1995. Professor, University of California at Berkeley, 1997{ Director, Mathematical Sciences Research Institute, 1997{ 2007 Director for Mathematics and the Physical Sciences, Simons Foundation, 2010{2012 HONORS, PRIZES Elected Fellow of the American Academy of Arts and Sciences, 2006 Leroy P. Steele Prize for Exposition, American Mathematical Society, 2010 CURRENT RESEARCH INTERESTS Algebraic Geometry Commutative Algebra Computational Methods 1 OTHER LONG-TERM MATHEMATICAL INTERESTS • Noncommutative Rings • Singularity Theory • Knot Theory and Topology 2 Professional Activities American Mathematical Society Council 1978{1982 (as member of the editorial board -
Download a PDF of the Program
Department of Mathematics 2021 Awards Tonight’s Program Welcome + Opening Remarks Professor Jeremy Tyson Chair, Department of Mathematics Land-Grant Statement + College of LAS Remarks Professor Matt Ando Associate Dean for Life and Physical Sciences, College of LAS Alumni Award Recognition + Remarks Steven Armstrong (BS ’92) 2020 Actuarial Science Program Alumnus of the Year Undergraduate Awards Professor Randy McCarthy Director of Undergraduate Studies Alumni Award Recognition + Remarks Danyel Graves Larsen (BA ’04) 2021 Alumni Humanitarian Award Illinois Geometry Lab Awards Professor Philipp Hieronymi Director of Illinois Geometry Lab Graduate Awards Professor Lee DeVille Director of Graduate Studies Alumni Award Recognition + Remarks Michael Stillman (BA ’78) 2021 Outstanding Achievement Award Faculty + Staff Awards Professor Jeremy Tyson Alumni Award Recognition + Remarks Judy Leavitt Walker (MS ’92, Ph.D. ’96) 2021 Outstanding Achievement Award Closing Remarks Professor Jeremy Tyson Undergraduate Awards H. Roy Brahana Prize Salma Wanna Memorial Award The H. Roy Brahana Prize is named for a distinguished The Salma Wanna Memorial Award honors the member of our mathematics faculty and recognizes memory of Salma Wanna, who received her PhD the student with “the most exceptional undergraduate from the University of Illinois in 1976. It is given for mathematics career.” “exceptional performance in mathematics to the Presented with honor to David Brewster, a senior most outstanding continuing student.” mathematics major. Presented with honor to Ariel Lerman, a sophomore mathematics major. Ariel received the Elsie Thomas Most Outstanding Major Awards Fraser Award in 2020 and was recently named a Barry In 1996, the department established the Major Awards M. Goldwater Scholar. He enjoys playing the cello, to recognize the most outstanding undergraduate creative writing and gaming. -
Math 476 - Abstract Algebra 1 Day 33 Group Assignment Name
Math 476 - Abstract Algebra 1 Day 33 Group Assignment Name: Polynomial Rings n n−1 Definition 11.2 Let R be a commutative ring. A polynomial in x over R is an expression of the form: anx +an−1x + 2 1 0 ··· + a2x + a1x + a0x , where n is a non-negative integer, and an,an−1, ··· ,a2,a1,a0 are elements of R. The set of all polynomials over the ring R will be denoted by R[x]. We will generally assume that an =6 0. • The symbol x is called an indeterminate. It is to be regarded as a formal symbol and not as an element of the ring 0 1 2 n R. In effect, the symbols x ,x ,x , ··· ,x serve as placeholders alongside the ring elements a0,a1, ··· ,an. k • The expressions akx are called the terms of the polynomial. The elements a0,a1, ··· ,an in the ring R are called k the coefficients of the polynomial p(x). We call ak the coefficient of x in the representation of p(x). • When working with a polynomial, instead of writing x1, we simply write x. In addition, we usually do not write x0 and 0 we will write a0x simply as a0 (does this make sense when R does not have an element 1R?). Using these conventions, n n−1 2 we can write p(x) in the form p(x) = anx + an−1x + ··· + a2x + a1x + a0, where n is a non-negative integer, an,an−1, ··· ,a2,a1,a0 are elements of R, and an =6 0. -
BOUNDS and DEFINABILITY in POLYNOMIAL RINGS Introduction the Main Theme of This Article Is the Existence of Bounds for Basic
BOUNDS AND DEFINABILITY IN POLYNOMIAL RINGS MATTHIAS ASCHENBRENNER Abstract. We study questions around the existence of bounds and the de- pendence on parameters for linear-algebraic problems in polynomial rings over rings of an arithmetic flavor. In particular, we show that the module of syzy- gies of polynomials f1, . , fn ∈ R[X1,...,XN ] with coefficients in a Pr¨ufer domain R can be generated by elements whose degrees are bounded by a num- ber only depending on N, n and the degree of the fj . This implies that if R is a B´ezout domain, then the generators can be parametrized in terms of the coefficients of f1, . , fn using the ring operations and a certain division function, uniformly in R. Introduction The main theme of this article is the existence of bounds for basic operations of linear algebra in polynomial rings over (commutative) rings of an arithmetic nature. The following result, shown in Section 3 below, is typical. Theorem A. Given integers N, d, n > 0 there exists an integer β = β(N, d, n) with the following property: for every Pr¨ufer domain R and polynomials f1, . , fn ∈ n R[X] = R[X1,...,XN ] of (total) degree 6 d, the R[X]-submodule of R[X] con- sisting of all solutions to the linear homogeneous equation f1y1 + ··· + fnyn = 0 can be generated by (finitely many) solutions whose components have degree 6 β. A classical theorem due to G. Hermann [24] states that Theorem A is true if we replace “Pr¨ufer domain” by “field”. In this case, it is easy to see that β can be chosen independent of n; Seidenberg [36] computed an explicit (doubly exponential) bound β. -
Vector Spaces
Chapter 2 Vector Spaces 2.1 INTRODUCTION In various practical and theoretical problems, we come across a set V whose elements may be vectors in two or three dimensions or real-valued functions, which can be added and multi- plied by a constant (number) in a natural way, the result being again an element of V. Such concrete situations suggest the concept of a vector space. Vector spaces play an important role in many branches of mathematics and physics. In analysis infinite dimensional vector spaces (in fact, normed vector spaces) are more important than finite dimensional vector spaces while in linear algebra finite dimensional vector spaces are used, because they are simple and linear transformations on them can be represented by matrices. This chapter mainly deals with finite dimensional vector spaces. 2.2 DEFINITION AND EXAMPLES VECTOR SPACE. An algebraic structure (V, F, ⊕, ) consisting of a non-void set V , a field F, a binary operation ⊕ on V and an external mapping : F ×V → V associating each a ∈ F,v ∈ V to a unique element a v ∈ V is said to be a vector space over field F, if the following axioms are satisfied: V -1 (V, ⊕) is an abelian group. V -2 For all u, v ∈ V and a, b ∈ F, we have (i) a (u ⊕ v)=a u ⊕ a v, (ii) (a + b) u = a u ⊕ b u, (iii) (ab) u = a (b u), (iv) 1 u = u. The elements of V are called vectors and those of F are called scalars. The mapping is called scalar multiplication and the binary operation ⊕ is termed vector addition.