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Modules and Vector Spaces
Modules and Vector Spaces R. C. Daileda October 16, 2017 1 Modules Definition 1. A (left) R-module is a triple (R; M; ·) consisting of a ring R, an (additive) abelian group M and a binary operation · : R × M ! M (simply written as r · m = rm) that for all r; s 2 R and m; n 2 M satisfies • r(m + n) = rm + rn ; • (r + s)m = rm + sm ; • r(sm) = (rs)m. If R has unity we also require that 1m = m for all m 2 M. If R = F , a field, we call M a vector space (over F ). N Remark 1. One can show that as a consequence of this definition, the zeros of R and M both \act like zero" relative to the binary operation between R and M, i.e. 0Rm = 0M and r0M = 0M for all r 2 R and m 2 M. H Example 1. Let R be a ring. • R is an R-module using multiplication in R as the binary operation. • Every (additive) abelian group G is a Z-module via n · g = ng for n 2 Z and g 2 G. In fact, this is the only way to make G into a Z-module. Since we must have 1 · g = g for all g 2 G, one can show that n · g = ng for all n 2 Z. Thus there is only one possible Z-module structure on any abelian group. • Rn = R ⊕ R ⊕ · · · ⊕ R is an R-module via | {z } n times r(a1; a2; : : : ; an) = (ra1; ra2; : : : ; ran): • Mn(R) is an R-module via r(aij) = (raij): • R[x] is an R-module via X i X i r aix = raix : i i • Every ideal in R is an R-module. -
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. -
6. Localization
52 Andreas Gathmann 6. Localization Localization is a very powerful technique in commutative algebra that often allows to reduce ques- tions on rings and modules to a union of smaller “local” problems. It can easily be motivated both from an algebraic and a geometric point of view, so let us start by explaining the idea behind it in these two settings. Remark 6.1 (Motivation for localization). (a) Algebraic motivation: Let R be a ring which is not a field, i. e. in which not all non-zero elements are units. The algebraic idea of localization is then to make more (or even all) non-zero elements invertible by introducing fractions, in the same way as one passes from the integers Z to the rational numbers Q. Let us have a more precise look at this particular example: in order to construct the rational numbers from the integers we start with R = Z, and let S = Znf0g be the subset of the elements of R that we would like to become invertible. On the set R×S we then consider the equivalence relation (a;s) ∼ (a0;s0) , as0 − a0s = 0 a and denote the equivalence class of a pair (a;s) by s . The set of these “fractions” is then obviously Q, and we can define addition and multiplication on it in the expected way by a a0 as0+a0s a a0 aa0 s + s0 := ss0 and s · s0 := ss0 . (b) Geometric motivation: Now let R = A(X) be the ring of polynomial functions on a variety X. In the same way as in (a) we can ask if it makes sense to consider fractions of such polynomials, i. -
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. -
On Semifields of Type
I I G ◭◭ ◮◮ ◭ ◮ On semifields of type (q2n,qn,q2,q2,q), n odd page 1 / 19 ∗ go back Giuseppe Marino Olga Polverino Rocco Tromebtti full screen Abstract 2n n 2 2 close A semifield of type (q , q , q , q , q) (with n > 1) is a finite semi- field of order q2n (q a prime power) with left nucleus of order qn, right 2 quit and middle nuclei both of order q and center of order q. Semifields of type (q6, q3, q2, q2, q) have been completely classified by the authors and N. L. Johnson in [10]. In this paper we determine, up to isotopy, the form n n of any semifield of type (q2 , q , q2, q2, q) when n is an odd integer, proving n−1 that there exist 2 non isotopic potential families of semifields of this type. Also, we provide, with the aid of the computer, new examples of semifields of type (q14, q7, q2, q2, q), when q = 2. Keywords: semifield, isotopy, linear set MSC 2000: 51A40, 51E20, 12K10 1. Introduction A finite semifield S is a finite algebraic structure satisfying all the axioms for a skew field except (possibly) associativity. The subsets Nl = {a ∈ S | (ab)c = a(bc), ∀b, c ∈ S} , Nm = {b ∈ S | (ab)c = a(bc), ∀a, c ∈ S} , Nr = {c ∈ S | (ab)c = a(bc), ∀a, b ∈ S} and K = {a ∈ Nl ∩ Nm ∩ Nr | ab = ba, ∀b ∈ S} are fields and are known, respectively, as the left nucleus, the middle nucleus, the right nucleus and the center of the semifield. -
11. Finitely-Generated Modules
11. Finitely-generated modules 11.1 Free modules 11.2 Finitely-generated modules over domains 11.3 PIDs are UFDs 11.4 Structure theorem, again 11.5 Recovering the earlier structure theorem 11.6 Submodules of free modules 1. Free modules The following definition is an example of defining things by mapping properties, that is, by the way the object relates to other objects, rather than by internal structure. The first proposition, which says that there is at most one such thing, is typical, as is its proof. Let R be a commutative ring with 1. Let S be a set. A free R-module M on generators S is an R-module M and a set map i : S −! M such that, for any R-module N and any set map f : S −! N, there is a unique R-module homomorphism f~ : M −! N such that f~◦ i = f : S −! N The elements of i(S) in M are an R-basis for M. [1.0.1] Proposition: If a free R-module M on generators S exists, it is unique up to unique isomorphism. Proof: First, we claim that the only R-module homomorphism F : M −! M such that F ◦ i = i is the identity map. Indeed, by definition, [1] given i : S −! M there is a unique ~i : M −! M such that ~i ◦ i = i. The identity map on M certainly meets this requirement, so, by uniqueness, ~i can only be the identity. Now let M 0 be another free module on generators S, with i0 : S −! M 0 as in the definition. -
Commutative Algebra
Commutative Algebra Andrew Kobin Spring 2016 / 2019 Contents Contents Contents 1 Preliminaries 1 1.1 Radicals . .1 1.2 Nakayama's Lemma and Consequences . .4 1.3 Localization . .5 1.4 Transcendence Degree . 10 2 Integral Dependence 14 2.1 Integral Extensions of Rings . 14 2.2 Integrality and Field Extensions . 18 2.3 Integrality, Ideals and Localization . 21 2.4 Normalization . 28 2.5 Valuation Rings . 32 2.6 Dimension and Transcendence Degree . 33 3 Noetherian and Artinian Rings 37 3.1 Ascending and Descending Chains . 37 3.2 Composition Series . 40 3.3 Noetherian Rings . 42 3.4 Primary Decomposition . 46 3.5 Artinian Rings . 53 3.6 Associated Primes . 56 4 Discrete Valuations and Dedekind Domains 60 4.1 Discrete Valuation Rings . 60 4.2 Dedekind Domains . 64 4.3 Fractional and Invertible Ideals . 65 4.4 The Class Group . 70 4.5 Dedekind Domains in Extensions . 72 5 Completion and Filtration 76 5.1 Topological Abelian Groups and Completion . 76 5.2 Inverse Limits . 78 5.3 Topological Rings and Module Filtrations . 82 5.4 Graded Rings and Modules . 84 6 Dimension Theory 89 6.1 Hilbert Functions . 89 6.2 Local Noetherian Rings . 94 6.3 Complete Local Rings . 98 7 Singularities 106 7.1 Derived Functors . 106 7.2 Regular Sequences and the Koszul Complex . 109 7.3 Projective Dimension . 114 i Contents Contents 7.4 Depth and Cohen-Macauley Rings . 118 7.5 Gorenstein Rings . 127 8 Algebraic Geometry 133 8.1 Affine Algebraic Varieties . 133 8.2 Morphisms of Affine Varieties . 142 8.3 Sheaves of Functions . -
Definition: a Semiring S Is Said to Be Semi-Isomorphic to the Semiring The
118 MA THEMA TICS: S. BO URNE PROC. N. A. S. that the dodecahedra are too small to accommodate the chlorine molecules. Moreover, the tetrakaidecahedra are barely long enough to hold the chlorine molecules along the polar axis; the cos2 a weighting of the density of the spherical shells representing the centers of the chlorine atoms.thus appears to be justified. On the basis of this structure for chlorine hydrate, the empirical formula is 6Cl2. 46H20, or C12. 72/3H20. This is in fair agreement with the gener- ally accepted formula C12. 8H20, for which Harris7 has recently provided further support. For molecules slightly smaller than chlorine, which could occupy the dodecahedra also, the predicted formula is M * 53/4H20. * Contribution No. 1652. 1 Davy, H., Phil. Trans. Roy. Soc., 101, 155 (1811). 2 Faraday, M., Quart. J. Sci., 15, 71 (1823). 3 Fiat Review of German Science, Vol. 26, Part IV. 4 v. Stackelberg, M., Gotzen, O., Pietuchovsky, J., Witscher, O., Fruhbuss, H., and Meinhold, W., Fortschr. Mineral., 26, 122 (1947); cf. Chem. Abs., 44, 9846 (1950). 6 Claussen, W. F., J. Chem. Phys., 19, 259, 662 (1951). 6 v. Stackelberg, M., and Muller, H. R., Ibid., 19, 1319 (1951). 7 In June, 1951, a brief description of the present structure was communicated by letter to Prof. W. H. Rodebush and Dr. W. F. Claussen. The structure was then in- dependently constructed by Dr. Claussen, who has published a note on it (J. Chem. Phys., 19, 1425 (1951)). Dr. Claussen has kindly informed us that the structure has also been discovered by H. -
The Kernel of a Derivation
Journal of Pure and Applied Algebra I34 (1993) 13-16 13 North-Holland The kernel of a derivation H.G.J. Derksen Department of Mathematics, CathoCk University Nijmegen, Nijmegen, The h’etherlands Communicated by C.A. Weibel Receircd 12 November 1991 Revised 22 April 1992 Derksen, H.G.J., The kernel of a deriv+ Jn, Journal of Pure and Applied Algebra 84 (1993) 13-i6. Let K be a field of characteristic 0. Nagata and Nowicki have shown that the kernel of a derivation on K[X, , . , X,,] is of F.&e type over K if n I 3. We construct a derivation of a polynomial ring in 32 variables which kernel is not of finite type over K. Furthermore we show that for every field extension L over K of finite transcendence degree, every intermediate field which is algebraically closed in 6. is the kernel of a K-derivation of L. 1. The counterexample In this section we construct a derivation on a polynomial ring in 32 variables, based on Nagata’s counterexample to the fourteenth problem of Hilbert. For the reader’s convenience we recari the f~ia~~z+h problem of iX~ert and Nagata’:: counterexample (cf. [l-3]). Hilbert’s fourteenth problem. Let L be a subfield of @(X,, . , X,, ) a Is the ring Lnc[x,,.. , X,] of finite type over @? Nagata’s counterexample. Let R = @[Xl, . , X,, Y, , . , YrJ, t = 1; Y2 - l = yy and vi =tXilYi for ~=1,2,. ,r. Choose for j=1,2,3 and i=1,2,. e ,I ele- ments aj i E @ algebraically independent over Q. -
Lecture 7.3: Ring Homomorphisms
Lecture 7.3: Ring homomorphisms Matthew Macauley Department of Mathematical Sciences Clemson University http://www.math.clemson.edu/~macaule/ Math 4120, Modern Algebra M. Macauley (Clemson) Lecture 7.3: Ring homomorphisms Math 4120, Modern algebra 1 / 10 Motivation (spoilers!) Many of the big ideas from group homomorphisms carry over to ring homomorphisms. Group theory The quotient group G=N exists iff N is a normal subgroup. A homomorphism is a structure-preserving map: f (x ∗ y) = f (x) ∗ f (y). The kernel of a homomorphism is a normal subgroup: Ker φ E G. For every normal subgroup N E G, there is a natural quotient homomorphism φ: G ! G=N, φ(g) = gN. There are four standard isomorphism theorems for groups. Ring theory The quotient ring R=I exists iff I is a two-sided ideal. A homomorphism is a structure-preserving map: f (x + y) = f (x) + f (y) and f (xy) = f (x)f (y). The kernel of a homomorphism is a two-sided ideal: Ker φ E R. For every two-sided ideal I E R, there is a natural quotient homomorphism φ: R ! R=I , φ(r) = r + I . There are four standard isomorphism theorems for rings. M. Macauley (Clemson) Lecture 7.3: Ring homomorphisms Math 4120, Modern algebra 2 / 10 Ring homomorphisms Definition A ring homomorphism is a function f : R ! S satisfying f (x + y) = f (x) + f (y) and f (xy) = f (x)f (y) for all x; y 2 R: A ring isomorphism is a homomorphism that is bijective. The kernel f : R ! S is the set Ker f := fx 2 R : f (x) = 0g. -
NOTES in COMMUTATIVE ALGEBRA: PART 1 1. Results/Definitions Of
NOTES IN COMMUTATIVE ALGEBRA: PART 1 KELLER VANDEBOGERT 1. Results/Definitions of Ring Theory It is in this section that a collection of standard results and definitions in commutative ring theory will be presented. For the rest of this paper, any ring R will be assumed commutative with identity. We shall also use "=" and "∼=" (isomorphism) interchangeably, where the context should make the meaning clear. 1.1. The Basics. Definition 1.1. A maximal ideal is any proper ideal that is not con- tained in any strictly larger proper ideal. The set of maximal ideals of a ring R is denoted m-Spec(R). Definition 1.2. A prime ideal p is such that for any a, b 2 R, ab 2 p implies that a or b 2 p. The set of prime ideals of R is denoted Spec(R). p Definition 1.3. The radical of an ideal I, denoted I, is the set of a 2 R such that an 2 I for some positive integer n. Definition 1.4. A primary ideal p is an ideal such that if ab 2 p and a2 = p, then bn 2 p for some positive integer n. In particular, any maximal ideal is prime, and the radical of a pri- mary ideal is prime. Date: September 3, 2017. 1 2 KELLER VANDEBOGERT Definition 1.5. The notation (R; m; k) shall denote the local ring R which has unique maximal ideal m and residue field k := R=m. Example 1.6. Consider the set of smooth functions on a manifold M.