MATH 101A: ALGEBRA I PART C: TENSOR PRODUCT AND MULTILINEAR ALGEBRA. This is the title page for the notes on tensor products and multilinear algebra.

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1 MATH 101A: ALGEBRA I PART C: TENSOR PRODUCT AND MULTILINEAR ALGEBRA This is the title page for the notes on tensor products and multilinear algebra. Contents 1. Bilinear forms and quadratic forms definition of bilinear form quadratic form nondegenerate bilinear forms nonsingular bilinear forms 3 2. Matrix of a bilinear form matrix as homomorphism dual bases basis for homomorphisms 7 3. Naturality and contravariant functors natural transformations contravariant functors unnaturality of the dual Tensor product definition exact functors and flat modules list of properties right exactness of tensor product localization is exact extension of scalars Modules over a PID rank p-rank p-primary modules 24 0

2 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 1 1. Bilinear forms and quadratic forms To save time, I am talking about bilinear forms and quadratic forms at the same time. We assume throughout that R is a commutative ring. (This will make E R F into an R-module for R-modules E, F.) 1.1. definition of bilinear form. Definition 1.1. If E, F are R-modules, a bilinear form on E F is an R-bilinear map f : E F R. I.e., (1) f(x, ) : F R is linear for each x E and (2) f(, y) : E R is linear for each y F. In the case E = F, f is called a bilinear form on E. Example 1.2. E = F = R n and f : E F R is given by n f(x, y) = x i y i. In this example you can see why R needs to be commutative: i=1 f(x, ry) = x i ry i = r x i y i = rf(x, y) holds because x i r = rx i. This is an example of a symmetric bilinear form on E where symmetric means f(x, y) = f(y, x). Example 1.3. E = R n = F and f is given by f(x, y) = i<j x i y j x j y i. This is an example of an alternating form which means f(x, y) = f(y, x). Note that symmetric and alternating only apply to the case E = F. Example 1.4. Take R = R and E = F = C 0 (I), the ring of continuous functions I = [0, 1] R considered as an R-module. Then f is given by f(φ, ψ) = 1 This is a symmetric bilinear form. 0 φ(x)ψ(x) dx.

3 2 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA The notation f(x, y) = x, y is sometimes used, especially in this last example. Here is a general example where E F. Example 1.5. Let E be any R-module and let F = Hom R (E, R). Let be given by f : E Hom R (E, R) R f(x, g) = g(x). This is R-linear in x by definition and it is R-linear in g because of the way the R-module structure of Hom R (E, R) is defined, namely by pointwise addition and scalar multiplication given by rg(x) = g(rx) This definition only works if R is commutative: s(rg)(x) = rg(sx) = g(rsx) = (rs)g(x) quadratic form. I gave two definitions of a quadratic form and showed that one implies the other. Definition 1.6. (This definition requires 1 2 on E is a function f : E R so that R.) A quadratic form f(x) = 1 g(x, x) 2 for some symmetric bilinear form g on E. The second definition works for any ring R. Definition 1.7. A quadratic form on E is a function f : E R so that (1) f(rx) = r 2 f(x) for every r R, x E. (2) The function g(x, y) := f(x + y) f(x) f(y) is a symmetric bilinear form on E. To see that the second definition implies the first, suppose that x = y. Then g(x, x) = f(2x) 2f(x) = 4f(x) 2f(x) = 2f(x). This implies that f(x) = 1g(x, x) if 1 R. Conversely, f(x) := 2 2 g(x, x) is easily seen to satisfy the second definition. 1 2

4 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA nondegenerate bilinear forms. Definition 1.8. Given a bilinear form f : E F R and S E, I defined S := {y F f(x, y) = 0 x S} Similarly, if T F then T := {x E f(x, y) = 0 y T } Proposition 1.9. Suppose E = F and f : E E R is symmetric or alternating. Then S = S for any S E. It is easy to see that S is always a submodule of F and T is always a submodule of E. However, in class I only pointed this out in the case of F E and E F. These are important because they are the kernels of the maps and φ f : E Hom R (F, R) ψ f : F Hom R (E, R). Definition We say that f : E F is nondegenerate on the left if F = 0, i.e., φ f is a monomorphism. We can that f is nondegenerate on the right if E = 0, i.e., ψ f is a monomorphism. Lang uses the notation E 0 = F and F 0 = E. Proposition Every bilinear form f : E F R induces a nondegenerate (on both sides) bilinear form by the equation f : E/E 0 F/F 0 R f(x + E 0, y + F 0 ) = f(x, y) nonsingular bilinear forms. Definition A bilinear form f : E F R is nonsingular on the left if φ f : E Hom R (F, R) is an isomorphism. It is nonsingular on the right if ψ f : F Hom R (E, R) is an isomorphism. f is called nonsingular if it is nonsingular on both sides.

5 4 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA We discussed why nonsingularity on the left and right were different. It is because a module is not always equal to its double dual. Definition The dual E of any R module E is defined by E = Hom R (E, R). If f : E F R is nonsingular on the left then φ f : E = F. Nonsingularity on the right would mean that ψ f : F = Hom R (F, R) = F But there are well-known examples where this is not true. There are also easy examples: If F is a torsion module over a PID R then F = 0. The well-known example is V a countably infinite dimensional vector space over Q. Then V is uncountable dimensional and V is even bigger dimensional. There is a related isomorphism: Proposition The mapping which sends a bilinear form f to φ f : E F and to ψ f : F E gives isomorphisms of R-modules: L 2 (E F, R) = Hom R (E, Hom R (F, R)) = HomR (F, Hom R (E, R)) Proof. The inverse of the first mapping is given by sending φ : E F to f(x, y) = φ(x)(y). This proposition is about all possible f. For a fixed nonsingular f, we get a different formula: Theorem If f : E F R is nonsingular then we get an induced isomorphism of R-modules End R (E) = L 2 (E F, R) where A End R (E) is mapped to the function fa given by fa(x, y) = f(ax, y).

6 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 5 Remark On the second day, I pointed out that this theorem requires only that f : E F R be nonsingular on the left. Proof. We know that L 2 (E F, R) = Hom R (E, F ) and that a bilinear form g maps to the homomorphism φ g : E F given by φ g (x) = g(x, ). The definition of nonsingular on the left means that φ f : E F is an isomorphism. But, F = E implies that We conclude that Hom R (E, F ) = Hom R (E, E) = End R (E). L 2 (E F, R) = Hom R (E, F ) = Hom R (E, E) = End R (E). The only question is: What is the formula for this isomorphism? The isomorphism is given by composition with the inverse φ 1 f : F E. So, g corresponds to A = φ 1 f φ g which, when applied to x E gives Ax = φ 1 f (φ g(x)). Applying φ f to both sides we got: f(ax, ) = φ g (x) = g(x, ) which is the formula in the theorem. The significance of this theorem is that it shows the need for a second bilinear form, namely f, in order to express g in matrix form.

7 6 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 2. Matrix of a bilinear form Suppose that E = R n and F = R m are free R-modules with bases {a 1,, a n } and {b 1,, b m }. If f : E F R is any bilinear form, we get a bunch of scalars: f(a i, b j ) = g ij R. These scalars determine the bilinear form f uniquely since arbitrary elements x E, y F are given by x = x i a i, y = y j b j. Then ( f(x, y) = f xi a i, ) y j b j = i This can be written in matrix form as f(x, Y ) = t XGY x i y j f(a i, b j ) = j i x i y j g ij where X, Y are column vectors with coordinates x i, y j, t X is the transpose and G = (g ij ) is the n m matrix with ij-entry equal to g ij matrix as homomorphism. At this point I tried to explain that there are hidden nonsingular forms in the matrix equation. This is because the product of a row matrix and a column matrix is the their dot product: f(x, Y ) = X, GY E where X, Z E = x i z i is the dot product in E. This is a nonsingular symmetric bilinear form. The bilinear form can also be written in terms of the dot product in F : f(x, Y ) = t GX, Y F The point is that, given a fixed nonsingular form on E or F we can express bilinear forms as homomorphisms: Proposition 2.1. If E, F are free and finitely generated over R then a bilinear form f on E F is given by f(x, Y ) = X, GY E where G = (g ij ) Hom R (F, E) is uniquely determined by f. This is just a rewording of what I explained earlier (that the matrix determines f). I just needed to explain how matrices give homomorphisms. This is just standard linear algebra but over arbitrary commutative rings. j

8 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA dual bases. First, we need the dual basis on F. If b 1,, b m is the basis for F then we have the dual basis b 1,, b m F given by ( ) b j (x) = b j xi b i = x j I.e., b j picks out the jth coordinate of x. Theorem 2.2. The b i form a basis for F = R m. Proof. First, the b i generate F. To show this let f : F R be any homomorphism. Then f is determined by the numbers f(b i ) = c i R and f = c i b i by the following: ( ) f(x) = f xi b i = x i f(b i ) = x i c i = c i b i (x). This shows that f = c i b i. Therefore, these dual elements b i generate F and give an epimorphism φ : R m F. Next we have to show that φ is 1-1, i.e., its kernel is zero. So, suppose that φ(x 1,, x m ) = x i b i = 0 F. If we apply this element of F to the basis element b j we get xi b i (b j ) = x i δ ij = x j = 0. Since this is true for all j, x = (x 1,, x m ) = (0,, 0). So, φ is an isomorphism and the b i form a basis for F basis for homomorphisms. Corollary 2.3. If E = R n and F = R m are free with bases {a i }, {b j } then Hom R (F, E) = R nm is free with basis the functions a i b j given by if y = y j b j. a i b j(y) = y j a i This corollary says that a homomorphism is given by a linear combination g = g ij a i b j i,j and the action of g is given by ( ) g(x) = g xj b j = i,j x j g ij a i = (a 1,, a n )GX (matrix multiplication) where G = (g ij ) and X = (x j ).

9 8 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA I gave a (much longer than necessary) categorical proof of this corollary using the following lemma. Lemma 2.4. Hom R (M, A B) = Hom R (M, A) Hom R (M, B) Proof. This follows from the universal property of the product A B = A B namely, a homomorphism into the product f : M A B is given uniquely by the projections p 1 f : M A and p 2 f : M B. So, the isomorphism in the lemma is given by and the inverse is given by f (p 1 f, p 2 f) (f, g) s 1 f + s 2 g where s 1 : A A B and s 2 : B A B are the inclusion maps. Proof of Corollary. Since E = R n we have by the lemma that Hom R (F, E) = Hom R (F, n R) = Hom R (F, R) = (F ) n. n Since the ith inclusion map s i : R E = R n is given by s i (r) = ra i the basis elements of Hom R (F, E) are s i b j = a i b j.

10 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 9 3. Naturality and contravariant functors Somehow, I got into a long explanation about contravariant functors and naturality natural transformations. The concept of naturality is made precise with the definition of a natural transformation. One example I used was the commutator subgroup G = [G, G] of a group G vs. its center Z(G). I claimed that G was natural but Z(G) was not natural. This comes from the fact that any homomorphism G H sends G into H but does not necessarily send Z(G) to Z(H). Definition 3.1. Suppose that F, G : A B are functors between categories A, B. Then a natural transformation η : F G is defined to be an operation which assigns to each object A A a morphism in B of the form η A : F A GA so that, for all morphisms f : A B in A, we have the following commuting square of morphisms in B. F A F f F B η A η B GA Gf GB For example, if A = B = Gps, the inclusion map is a natural transformation from G to G. This is a natural transformation from the commutator subgroup functor to the identity functor. Another example is the torsion submodule tm of a module M over a PID R. The following commuting diagram shows that tm is a natural submodule of M and M/tM is a natural quotient module. tn N N/tN tm M M/tM The two squares in this diagram mean we have two natural transformations t id id/t Natural is not the same as functorial. It means more. In order to have naturality, we need two functors and a natural transformation. The dual E of E is thus functorial but not natural. But it is contravariantly functorial.

11 10 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 3.2. contravariant functors. Definition 3.2. If A and B are categories, a contravariant functor F : A B is a pair of mappings (1) a mapping F : Ob(A) Ob(B), i.e., for each A A we have F A B. (2) for every morphism f : A B in A we get a morphism satisfying the two conditions: (a) F id A = (id A ) = id F A (b) (f g) = g f. F f = f : F B F A Example 3.3. Suppose that X is any fixed R-module. Then we have a contravariant functor sending M to Hom R (M, X). Hom R (, X) : R-Mod Z-Mod Example 3.4. If X is a topological space, let C 0 (X) be the ring of all continuous functions X R. This is a contravariant functor C 0 : T op Rings from the category of topological spaces and continuous maps to the category of rings and ring homomorphisms. Duality E E = Hom R (E, R) is a contravariant functor. So, E is functorial and its elements behave in a functorial way. However, the dual basis is not natural unnaturality of the dual. Theorem 3.5. There is no natural isomorphism E = E in the category of finitely generated free R-modules and isomorphism. First, what does this theorem say? We take the category C whose objects are f.g. free R-modules and whose morphisms are isomorphisms. By a natural isomorphism φ E : E E we mean an isomorphism which makes the following diagram commute for any isomorphism f : E = F of f.g. free R modules: E f F φ E E f F φ F

12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 11 Proof. I proved this by contradiction. But the proof assumes the 1+1 0, i.e., the characteristic of the ring is not 2. Suppose there is such a natural isomorphism. Let E = F = R 2 be free on two generators v, w. Then E is free on the dual basis elements v, w. Let f : E E be the isomorphism given by f(v) = v and f(w) = v ± w (doing two cases at once). Then f (w ) = ±w since f w (xv + yw) = w f(xv + yw) = w (xv + yv ± yw) = ±y and f (v ) = v + w since f v (xv + yw) = v f(xv + yw) = v (xv + yv ± yw) = x + y. Now suppose that there is some isomorphism φ : E E which makes the diagram commute. Then φ = f φf. Suppose that φ(v) = xv + yw. Then φ(v) = f φf(v) = f φ(v) = f (xv + yw ) = xv + xw ± yw. In order for this to be equal to f(v) = xv + yw we must have y = x + y = x y since the same isomorphism φ must work for both functions f. This implies that x = 0 and 2y = 0. But, for φ to be an isomorphism, we must have y invertible in the ring. So, 2 = 0. When you looked at this counterexample, you can see one of the reasons that the dual basis is not natural: When we changed the second basis element from w to v + w, it was the dual basis element v which changed. This dual element v depends not on v but on your choice of the other basis element w (or, in higher dimensions, vi depends on all v j where j i). The reason is that the other basis elements must span the kernel of vi by definition. So, they are the ones that determine what vi are up to a scalar multiple.

13 12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA Here is an outline of what I did: (1) categorical definition (2) construction (3) list of basic properties (4) distributive property (5) right exactness (6) localization is flat (7) extension of scalars (8) applications 4. Tensor product 4.1. definition. First I gave the categorical definition and then I gave an explicit construction universal condition. Tensor product is usually defined by the following universal condition. Definition 4.1. If E, F are two modules over a commutative ring R, their tensor product E F is defined to be the R-module having the following universal property. First, there exists an R-bilinear mapping f : E F E F. Second, this mapping is universal in the sense that, for any other R- module M and bilinear mapping g : E F M, there exists a unique R-module homomorphism h : E F M making the following diagram commute. E F g f E F!h M As with all universal conditions, this definition only gives the uniqueness of E F up to isomorphism. For the existence we need a construction construction of E F. The mapping f : E F E F is not onto. However, the image must generate E F otherwise we get a contradiction. The elements in the image of f are denoted f(x, y) = x y. Definition 4.2. The tensor product E F is defined to be the R module which is generated by the symbols x y for all x E, y F modulo the following conditions

14 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 13 (1) x is R-bilinear. I.e. (a) x ry = r(x y) for all r R (b) x (y + z) = (x y) + (x z) (2) y is R-bilinear. I.e., (a) rx y = r(x y) for all r R (b) (x + y) z = (x z) + (y z) I pointed out that these conditions require R to be commutative since rs(x y) = r(sx y) = sx ry = s(x ry) = sr(x y). Proposition 4.3. E F as given in the second definition satisfies the universal condition of the first definitions and therefore, the tensor product exists and is unique up to isomorphism. Proof. I said in class that this is obvious. If there is a bilinear mapping g : E F M, the induced mapping h : E F M must take the generators x y to g(x, y). Otherwise the diagram will not commute. Therefore, h is given on the generators and is thus unique. The only thing we need is to show that h is a homomorphism. But this is equivalent to showing that the elements of the form rx y r(x y) and elements corresponding to the other three conditions in the second definition go to zero in M. But this element goes to g(rx, y) rg(x, y) = 0 since g is R-bilinear and similarly for the other three elements. So, h is an R-module homomorphism and we are done functorial properties of tensor product. The first properties I mentioned were the categorical properties which follow directly from the definition. Proposition 4.4. For a fixed R-module M, tensor product with M is a functor M : R-Mod R-Mod. What this means is that, given an homomorphism f : A B there is an R-module homomorphism which satisfies two conditions: (1) 1 id A = id M A 1 f : M A M B

15 14 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA (2) 1 fg = (1 f)(1 g). The definition is (1 f)(x y) = x f(y). This gives a homomorphism since the mapping M A M B given by (x, y) x f(y) is bilinear and therefore induces the desired mapping 1 f. More generally, given two homomorphisms f : M N, g : A B we get a homomorphism by the formula f g : M A N B (f g)(x y) = f(x) g(y) exact functors and flat modules. Flat modules are those for which the functor M is exact. An exact functor is one that takes short exact sequences to short exact sequences. So, first I explained the definitions. Definition 4.5. An exact sequence is a sequence of modules and homomorphisms so that the image of each map is equal to the kernel of the next map. A short exact sequence is an exact sequence of the following form: 0 A α B β C 0. In other words, α : A B is a monomorphism, β : B C is an epimorphism and im α = ker β or: C = B/αA. Sometimes short exact sequences are written: A B C. Definition 4.6. A functor F : R-Mod R-Mod is called exact if it takes short exact sequences to short exact sequences. Thus the short exact sequence above should give the short exact sequence 0 F A F α F B F β F C 0. Definition 4.7. An R-module M is called flat if M is an exact functor. I.e., 0 M A 1 α M B 1 β M C 0 is exact for all short exact sequences A B C. One of the main results (which we will see is actually trivial) is that S 1 R is flat for any multiplicative set S. I.e., localization is exact.

16 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA list of properties. I explained that the exactness of localization was one of the key ideas. However, the explanation required an understanding of the basic properties of tensor product. So, I went back to the beginning with this list. (0) (unity) R M = M. (1) (commutative) M N = N M (2) (distributive) N M i = (N Mi ) (3) (associative) (A B) C = A (B C) (4) (right exactness) M is right exact, i.e., a short exact sequence A B C gives an exact sequence M A 1 α M B 1 β M C 0 (5) (localization is exact) I.e., we get an exact sequence: 0 S 1 A S 1 B S 1 C 0. (6) (extension of scalars) Given a ring homomorphism R S, every R-module M gives an S module S R M Grothedieck ring. I did not prove properties (1) and (3). I said they were obvious. However, I put the first three conditions into a conceptual framework by pointing out that these are the axioms of a ring. The only thing that we don t have is an additive inverse. The algebraic construction is as follows. First, you take the set of all isomorphism classes of finnitely generated R-modules [M]. This set has addition and multiplication given by [M] + [N] = [M N] [M][N] = [M N] Addition and multiplication are associative and commutative and have units: [0] is the additive unit and [R] is the multiplicative unit. It just doesn t have additive inverses. So, Grothendieck said to just put in formal inverses: [M] [N] which are defined like fractions: [M] [N] = [A] [B] if there exists another module C so that M B C = N A C. This gives a ring whose name is G(R). The notation K 0 (R) is for the ring of formal differences of f.g. projective R-modules.

17 16 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA R M = M. After using this formula many times in the lecture, I decided I should prove it. I put the proof at the beginning in the notes where it belongs. Theorem 4.8. R M = M for any R-module M. Proof. Since the mapping R M M given by (r, x) rx is bilinear it induces a mapping µ : R M M so that µ(r x) = rx. The inverse mapping φ : M R M is given by φ(x) = 1 x. We carefully checked that these are inverse to each other: φµ(r x) = φ(rx) = 1 rx = r(1 x) = r x µφ(x) = µ(1 x) = 1x = x. So, these maps are both isomorphisms of R-modules distributive property. I gave a category theory proof of the distributivity of tensor product over direct sum. First I pointed out that the following formal characterization of direct sum. Lemma 4.9. M is the direct sum of modules M 1,, M n if and only if there are inclusion maps s i : M i M and projection maps p i : M M i so that (1) p j s i = δ ij, i.e., equal to the identity mapping on M i if i = j and equal to 0 if i j. (2) s i p i = id M. I drew the following diagrams to illustrate these equations. δ ij M i M j s i p j M p j s i = δ ij n M M i=1 s i p i = id M p i s i M This lemma was proved in any preadditive category in Part B, Theorem 7.4.

18 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 17 Theorem If M = n i=1 M i then n N M = N M i = i=1 n (N M i ). i=1 Proof. Consider the homomorphisms: N M i 1 s i 1 p j N M N M j a) (1 p j )(1 s i ) = 1 p j s i = 1 δ ij = δ ij (1 1). b) (1 s i )(1 p i ) = 1 s i p i = 1 1 = id N M. These conditions imply that N M = N M i by the above lemma. Remark This proof works in any preadditive category to show that any linear functor distributes over direct sum right exactness of tensor product. I didn t prove the right exactness of tensor product this first time because the elementary proof is messy and not very instructive. I just explained that this is a special case of a much more general principle that: All linear left adjoint functors are right exact. I will explain this later. The statement of the theorem is the following. Theorem Tensor product with any R-module M sends any exact sequence of R-modules of the form: A α B β C 0 to another exact sequence of the same form: M A M B M C 0. This statement appears stronger than the original statement since the hypothesis is weaker. But I explained that the first statement implies this second version. Suppose that we know that M sends short exact sequences to right exact sequences as above. Then how can we conclude that it sends the more general right exact sequences A B C 0 to right exact sequences? The first statement implies that M takes epimorphisms to epimorphisms. (In fact this is obvious since the generators x y M C come from generators x ỹ M B.) Therefore M A maps onto M α(a). If we assume the weaker condition that the functor M

19 18 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA takes short exact sequences to right exact sequences, then it will take the short exact sequence to an exact sequence 0 α(a) B β C 0 M α(a) M B 1 β M C 0 This says that M α(a) maps onto the kernel of 1 β. But M A maps onto M α(a). So, M A also maps onto ker(1 β). So, we get an exact sequence M A 1 α M B 1 β M C 0. Here is an example of how this is used. Corollary Suppose that I R is an ideal. Then R/I M = M/IM where IM is the submodule of M generated by all products of the form ax where a I and x M. In particular, when I = (p) is principal, we have R/(p) M = M/pM where pm = {px x M}. Proof. Suppose that I is generated by elements a i. Then we have an epimorphism of R modules R I i sending (r i ) R to r i a i I. This gives an exact sequence R α R R/I 0. i Tensor with M to give R M α 1 R M R/I M 0. i Using the isomorphisms µ : R M = M and φ : M = R M we get an exact sequence M µ(α 1)φ M R/I M 0 i where µ(α 1)φ sends (x i ) M to a i x i M. The image is equal to IM by definition. So, R/I M = M/IM as claimed.

20 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 19 For finitely generated modules over a PID we can now compute the tensor product: ( M R n ) R/(p n i i ) = M n M/p n i i M localization is exact. Recall that a multiplicative set is a subset S R which is closed under multiplication, contains 1 and does not contain 0. The localization S 1 R was defined to be the ring of all fractions r/s where r R and s S modulo the equivalence relation r s r s if there is an element t S so that rs t = r st. This ring is also an R-module since we have an action of R given by r x s = rx s. Proposition For any R-module M let S 1 M be the set of equivalence classes of fractions x/s where x M, s S modulo the equivalence relation x/s y/s if there is a t S so that ts x = tsy. Then S 1 M is an R-module with action of R given by r(x/s) = rx/s and S 1 M = S 1 R M. Proof. There is an obvious map S 1 R M S 1 M sending r/s x to rx/s. The inverse map sends x/s to 1/s x. To show that this is well-defined, take an equivalent element tx/ts. This goes to 1 ts tx = t ( 1 ts x The rest of the proof is straightforward. ) = t ts x = 1 s x. Theorem S 1 R is a flat R-module. Equivalently, every short exact sequence of R-modules A B C induces an exact sequence 0 S 1 A S 1 B S 1 C 0. Proof. Since tensor product is right exact, it suffices to show that S 1 A S 1 B is a monomorphism. This is easy. We can assume that A B and suppose that a A and s S so that the element a/s S 1 A goes to zero in S 1 B. This means a s 0 s

21 20 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA in S 1 B. By definition this is equivalent to saying that there exists t S so that tsa = 0. But this same equation implies that a/s = 0/1 in S 1 A. So, we are done. The ring S 1 R acts on the module S 1 M in the obvious way: r x s t = rx st. This makes S 1 M into a module over S 1 R. This is an example of extension of scalars extension of scalars. We had a concept before called restriction of scalars. That was when we had a subring S of R or, more generally, a ring homomorphism φ : S R and we got an induced map φ : R- Mod S- Mod which sent an R-module M to the same thing with the action of S given by s x = φ(s)x. I.e., we restricted the action of the ring to S. Extension of scalars goes the other way. Proposition Given a ring homomorphism φ : R S and an R-module M, S R M is an S-module with action of S given by s(t x) = st x. The module is sometimes written as S φ M because the R-module structure is given by r(s x) = (φ(r)s) x = s rx. This is the R-module structure induced from the S-module structure by restriction of scalars. Proof. Multiplication by elements of S gives an R-linear map S S and therefore gives an R-linear map S M S M by naturality of tensor product. This gives a sequence of ring homomorphisms S End R (S) End R (S M) which defines the S-module structure on S M. One special case of this is when R is a domain and F = Q(R) is the field of fractions. Definition Suppose that M is a module over a domain R. Then the rank of M is defined to be the dimension of Q(R) M as a vector space over the field Q(R). r(m) = dim Q(R) Q(R) M.

22 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 21 Theorem For a f.g. module M over a PID R, if M = R r R/(p n i i ), the number r is equal to the rank of M and is therefore uniquely determined. Proof. This is a calculation using the fact that since aq(r) = Q(R) for a 0: R/(a) Q(R) = Q(R)/aQ(R) = 0 Q(R) M = Q(R) R r Q(R)/p n i i Q(R) = Q(R) r. are uniquely deter- It still remains to show that the numbers p n i i mined.

23 22 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 5. Modules over a PID I spent one more day to finish the uniqueness part of the structure theorem for f.g. modules over a PID. First I reviewed properties of the rank rank. Recall that if R is any domain, Q(R) is a field. So, for any R-module M, we can define the rank of M to be rm = dim Q(R) M Q(R). We know that Q(R) = S 1 R is a flat R-module. short exact sequence of R-modules 0 A B C 0 gives a short exact sequence of vector spaces 0 Q(R) A Q(R) B Q(R) C 0. Therefore, any Lemma 5.1. If 0 A B C 0 is a short exact sequence of vector spaces over a field F then (1) B = A C (2) dim B = dim A + dim C. Proof. This follows from the fact that all modules over fields are free and thus projective. Theorem 5.2. If 0 A B C 0 is a short exact sequence of f.g. R-modules where R is any domain, then r(b) = r(a) + r(c) p-rank. Suppose that p R is a prime ideal. Then R/p is a domain. So, modules over R/p have rank. Definition 5.3. Define the p-rank of an R-module M to be the rank of the R/p-module R/p M = M/pM. This is the dimension of the vector space Q(R/p) M.

24 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 23 Example 5.4. Let R = Z and M = Z/20 Z/8. The prime number p = 5 is irreducible and thus generates a prime ideal p = (5) = 5Z. Here R/p = Z/5 is a field. The 5-rank of M is the dimension of the vector space: Z/5 M = Z/5 (Z/20 Z/8) = (Z/5 Z/20) (Z/5 Z/8) = Z/(5, 20) Z/(5, 8) = Z/5 which is 1. In the first step we used the distributivity of tensor product over direct sum. In the second step we used the rule that So, and M R/(p) = M/pM. Z/5 Z/20 = Z 5Z + 20Z = Z 5Z Z Z/5 Z/8 = 5Z + 8Z = Z Z = 0 Similarly, the 2-rank of M is the dimension over Z/2 of Z/2 M = Z/2 (Z/20 Z/8) = Z/2 Z/2 which is 2. For all other prime numbers p, the p-rank of M is zero. With this example we decided that we could state without proof the general formula. Proposition 5.5. (1) Suppose R = Z and k M = Z/n i. i=1 Then the p-rank of M is the number of indices i so that p n i. (2) More generally, suppose that R is a PID and k M = R/(p n i i ) i=1 where p i R are irreducible. Then the p-rank of M is the number of indices i so that p = p i. We will use the following observation. Corollary 5.6. The p-rank of a cyclic module is either 0 or 1.

25 24 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 5.3. p-primary modules. Now suppose that R is a PID and p is a fixed irreducible element. Suppose that M is f.g. p-primary. Then k M = R/(p n i ). i=1 The p-rank of M is the number of summands k. We want to find a formula for the numbers n i. In order to do this, we asked: What is the p-rank of p m M? We took one summand R/(p n ) and noted that the annihilator of this module is (p n ) and p m (p n ) if and only if m n. Therefore, p m R/(p n ) = 0 if and only if m n. If m < n then p m R/(p n ) is nonzero and cyclic. Being p-primary, this makes its p-rank equal to 1. So: { p-rank (p m R/(p n 1 if m < n )) = 0 if m n So, the p-rank of p m M = k p m R/(p n i ) i=1 is equal to the number of indices i for which n i > m. Now we have enough invariants to show that the formula given in the structure theorem for f.g. modules over a PID is unique. Example 5.7. Suppose that R = Z and M = Z 5 Z/6 Z/27. (1) First, take the rank: Q M = Q 5. So, rm = 5. (2) The 2-rank of M is = 6 since Z/2 M = M/2M = (Z/2) 5 Z/(2, 6) Z/(2, 27) = (Z/2) 6. (3) This implies that M has one cyclic 2-primary summand Z/2 n. To find n we compute the 2-ranks of 2M, 4M, etc. until we reach 5. But 2M = (2Z) 5 2Z/6Z 2Z/27 = Z 5 Z/3 Z/27 which has 2-rank 5. So, we see that the 2-primary summand of M is Z/2. (4) The 3-rank of M is = 7 since Z/3 M = M/3 = (Z/3) 5 Z/(3, 6) Z/(3, 27) = (Z/3) 7. (5) So, M has 2 cyclic 3-primary summands. We need to calculate the 3-ranks of 3M, 9M, etc. 3M = (3Z) 5 3Z/6 3Z/27 = Z 5 Z/2 Z/9. 9M = Z 5 Z/2 Z/3.

26 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA 25 27M = Z 5 Z/2. So, M, 3M, 9M, 27M have 3-rank 7,6,6,5 respectively. We stop when we reach the rank of M which is 5. These numbers show that the 3-primary part of M is Z/3 Z/3 3. (6) For all other primes p, the p-rank of M is 5. So, the decomposition of M is M = Z 5 Z/2 Z/3 Z/3 3. Example 5.8. Suppose that M is a finitely generated abelian group with rm = 2, 2-rank of M, 2M, 4M, 8M, 16M equal to 5, 5, 4, 3, 2 and 3-rank of M, 3M, 9M equal to 4, 4, 2 and p-rank of M equal to 2 for all other primes. Then M = Z 2 (Z/4) 2 Z/8 Z/16 (Z/9) 2 = Z 2 Z/144 Z/72 Z/8 (Z/4) 2. (In this order each denominator divides the previous one.) Theorem 5.9. In the decomposition of a finitely generated module over a PID: M = R r R/(p n i i ) the numbers r and pairs (p i, n i ) are uniquely determined up to reordering and can be determined from the rank of M and the p-rank of M, pm, p 2 M, etc. for each irreducible p.

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