Solutions to the August 2008 Qualifying Examination

Similar documents
Group Theory. 1. Show that Φ maps a conjugacy class of G into a conjugacy class of G.

GRE Subject test preparation Spring 2016 Topic: Abstract Algebra, Linear Algebra, Number Theory.

ALGEBRA QUALIFYING EXAM PROBLEMS LINEAR ALGEBRA

QUALIFYING EXAM IN ALGEBRA August 2011

Math Introduction to Modern Algebra

August 2015 Qualifying Examination Solutions

ALGEBRA QUALIFYING EXAM PROBLEMS

Dimension. Eigenvalue and eigenvector

Algebra Exam Topics. Updated August 2017

Topics in linear algebra

Bare-bones outline of eigenvalue theory and the Jordan canonical form

φ(xy) = (xy) n = x n y n = φ(x)φ(y)

Solution. That ϕ W is a linear map W W follows from the definition of subspace. The map ϕ is ϕ(v + W ) = ϕ(v) + W, which is well-defined since

(a) II and III (b) I (c) I and III (d) I and II and III (e) None are true.

ALGEBRA PH.D. QUALIFYING EXAM September 27, 2008

MATH 3030, Abstract Algebra Winter 2012 Toby Kenney Sample Midterm Examination Model Solutions

MATH 320: PRACTICE PROBLEMS FOR THE FINAL AND SOLUTIONS

Chapter 7: Symmetric Matrices and Quadratic Forms

Therefore, A and B have the same characteristic polynomial and hence, the same eigenvalues.

Math 594. Solutions 5

SUMMARY ALGEBRA I LOUIS-PHILIPPE THIBAULT

Math 120 HW 9 Solutions

University of Colorado at Denver Mathematics Department Applied Linear Algebra Preliminary Exam With Solutions 16 January 2009, 10:00 am 2:00 pm

CHAPTER I. Rings. Definition A ring R is a set with two binary operations, addition + and

MATRIX LIE GROUPS AND LIE GROUPS

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det

Algebra Exam Syllabus

EXERCISES AND SOLUTIONS IN LINEAR ALGEBRA

Lecture 7.3: Ring homomorphisms

Algebraic structures I

Solutions of exercise sheet 8

A Little Beyond: Linear Algebra

Algebra qual study guide James C. Hateley

Algebra Exam Fall Alexander J. Wertheim Last Updated: October 26, Groups Problem Problem Problem 3...

22M: 121 Final Exam. Answer any three in this section. Each question is worth 10 points.

Math 217: Eigenspaces and Characteristic Polynomials Professor Karen Smith

Diagonalization of Matrix

Final A. Problem Points Score Total 100. Math115A Nadja Hempel 03/23/2017

January 2016 Qualifying Examination

Honors Algebra 4, MATH 371 Winter 2010 Assignment 3 Due Friday, February 5 at 08:35

Computations/Applications

MATH SOLUTIONS TO PRACTICE MIDTERM LECTURE 1, SUMMER Given vector spaces V and W, V W is the vector space given by

Practice Final Exam Solutions

(Rgs) Rings Math 683L (Summer 2003)

HOMEWORK 3 LOUIS-PHILIPPE THIBAULT

Definition (T -invariant subspace) Example. Example

OHSx XM511 Linear Algebra: Solutions to Online True/False Exercises

Diagonalization. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Linear Algebra. Workbook

Algebra Homework, Edition 2 9 September 2010

Exercises on chapter 0

Math 554 Qualifying Exam. You may use any theorems from the textbook. Any other claims must be proved in details.

Math 110, Spring 2015: Midterm Solutions

Review 1 Math 321: Linear Algebra Spring 2010

1 Linear transformations; the basics

Math 121 Practice Final Solutions

The Jordan Canonical Form

Representations. 1 Basic definitions

Group Theory. Ring and Module Theory

Mathematics Department Qualifying Exam: Algebra Fall 2012

Remark By definition, an eigenvector must be a nonzero vector, but eigenvalue could be zero.

Lecture 12: Diagonalization

Lecture Summaries for Linear Algebra M51A

Honors Algebra 4, MATH 371 Winter 2010 Assignment 4 Due Wednesday, February 17 at 08:35

LINEAR ALGEBRA 1, 2012-I PARTIAL EXAM 3 SOLUTIONS TO PRACTICE PROBLEMS

ABSTRACT ALGEBRA 2 SOLUTIONS TO THE PRACTICE EXAM AND HOMEWORK

LINEAR ALGEBRA BOOT CAMP WEEK 2: LINEAR OPERATORS

MATH 1553-C MIDTERM EXAMINATION 3

THE MINIMAL POLYNOMIAL AND SOME APPLICATIONS

LINEAR ALGEBRA REVIEW

Fields and Galois Theory. Below are some results dealing with fields, up to and including the fundamental theorem of Galois theory.

and let s calculate the image of some vectors under the transformation T.

Problem 1.1. Classify all groups of order 385 up to isomorphism.

Online Exercises for Linear Algebra XM511

A = 3 1. We conclude that the algebraic multiplicity of the eigenvalues are both one, that is,

x y B =. v u Note that the determinant of B is xu + yv = 1. Thus B is invertible, with inverse u y v x On the other hand, d BA = va + ub 2

CONSEQUENCES OF THE SYLOW THEOREMS

First we introduce the sets that are going to serve as the generalizations of the scalars.

Final Exam Practice Problems Answers Math 24 Winter 2012

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #2 Solutions

A connection between number theory and linear algebra

Algebra SEP Solutions

Prime Rational Functions and Integral Polynomials. Jesse Larone, Bachelor of Science. Mathematics and Statistics

Linear Algebra Practice Problems

Math 121 Homework 5: Notes on Selected Problems

Chapter 2: Linear Independence and Bases

Problem 1A. Find the volume of the solid given by x 2 + z 2 1, y 2 + z 2 1. (Hint: 1. Solution: The volume is 1. Problem 2A.

Math 547, Exam 1 Information.

Diagonalization. Hung-yi Lee

Lecture 4.1: Homomorphisms and isomorphisms

Study Guide for Linear Algebra Exam 2

Honors Algebra II MATH251 Course Notes by Dr. Eyal Goren McGill University Winter 2007

Math 113 Midterm Exam Solutions

University of Colorado Denver Department of Mathematical and Statistical Sciences Applied Linear Algebra Ph.D. Preliminary Exam May 25th, 2018

NOTES ON FINITE FIELDS

PROBLEM SET. Problems on Eigenvalues and Diagonalization. Math 3351, Fall Oct. 20, 2010 ANSWERS

DIAGONALIZATION. In order to see the implications of this definition, let us consider the following example Example 1. Consider the matrix

Selected exercises from Abstract Algebra by Dummit and Foote (3rd edition).

Chapter 2 Notes, Linear Algebra 5e Lay

HW2 - Due 01/30. Each answer must be mathematically justified. Don t forget your name.

Transcription:

Solutions to the August 2008 Qualifying Examination Any student with questions regarding the solutions is encouraged to contact the Chair of the Qualifying Examination Committee. Arrangements will then be made for the student to meet with a faculty member who can answer their questions. 1

Abstract Algebra 1. (a) A subgroup H of G is normal if for all g G, g 1 Hg H. (b) Note that (ghg 1 h 1 ) 1 = hgh 1 g 1, which is of the same form, so an element in N can be written as n = (g 1 h 1 g1 1 h 1 1 ) (g m h m gm 1 h 1 m ) for some g i, h i G. Let a G. Since a 1 na = a 1 (g 1 h 1 g1 1 h 1 1 ) (g m h m gm 1 h 1 m )a = (a 1 (g 1 h 1 g1 1 h 1 1 )a)(a 1 (g 2 h 2 g2 1 h 1 2 )a) (a 1 (g m h m gm 1 h 1 m )a), it suffices to look at one term. We drop the suffix. a 1 ghg 1 h 1 a = a 1 gaa 1 haa 1 g 1 aa 1 h 1 a = (a 1 ga)(a 1 ha)(a 1 ga) 1 (a 1 ha) 1 N. (c) Since φ(g) H is a subgroup of H, it is also abelian. Using the composition, it suffices to assume that φ is onto. Since φ(aba 1 b 1 ) = φ(a)φ(b)φ(a) 1 φ(b) 1 = e H (H is abelian), we have N ker(φ). We then have the natural maps provided by the first homomorphism theorem G G/N G/ ker(φ) = H. 2. (a) A unit in R is an element with a two sided multiplicative inverse, i.e., a R is a unit if there exists b R such that ab = 1(= ba). (b) Consider the ideal ur. If this is not R, then ur is contained in a maximal ideal M. But then u ur M S, a contradiction. Thus R = ur, so 1 ur, i.e., there is an element b R such that 1 = ub(= bu). Hence u is a unit. (c) One can do this problem using what is called the determinant trick, but we ll give an inductive proof, using induction on the number of generators of M. Note that any quotient of R by ar, where a M, preserves the hypotheses. If M = ar then we are given that ar = a 2 R, so we have an equation a = ra 2 for some r R. Thus a(1 ra) = 0. Using the notation of part (b), 1 ra R S (since if 1 ra M then 1 M), so is a unit. Hence a = 0, so M = 0. Now assume that M = (a 1,..., a n ) with n > 1, and the result is true for 1 k < n. In R/a 1 R we still have M/a 1 R = (M/a 1 R) 2, and the maximal ideal is at most n 1 generated, so M + a 1 R = 0 in R/a 1 R. Thus M = a 1 R, and we are done by the case k = 1. 3. (a) Since Z 2 only has 2 elements we can assume that the coefficient of x 3 is 1. Also, the constant term is 1, or else x divides the polynomial. This leaves 2 possible coefficients for x 2 and x, so there are only 4 possibilities. Since we have a degree 3 polynomial over a field, if it factors it must have a degree one factor. Since we have ruled out a factor of x, the only other possible linear factor is x 1. Thus we have an irreducible polynomial if and only if 1 is not a root (given our other preconditions). The only polynomials of degree 3 that are irreducible are then x 3 + x 2 + 1 and x 3 + x + 1. (b) Let n be the largest exponent of y occuring in p(x, y). Then we can write 0 = p(x, e x ) = e nx p n (x) + e (n 1)x p n 1 (x) + + p 0 (x), where each p i (x) Q[x]. If n = 0, then y does not occur in p(x, y), so the hypothesis already gives p(x, y) = p(x) = 0. Assume n 1. Then p n (x) = (e x p n 1 (x) + e nx p 0 (x)). Since e x always dominates a polynomial in x, if we take the limit on the right as x,

we get 0. Thus p n (x) = 0. But this says that y n does not appear in p(x, y), a contradiction (this proof works in R[x, y] too.) 4. (a) It is clear that Q[ 2 + 3] Q[ 2, 3]. If we show that 2, 3 L = Q[ 2+ 3] then we will be done. We have ( 2+ 3) 2 = 13+2 6 L, so 6 L. Then 6( 2+ 3) = 3 2+2 3 L. Then 3( 2+ 3)+(3 2+2 3) = 3 L (which then gives 2 L also). (b) By part (a) we must find the dimension of Q[ 2, 3] as a Q-vector space. By Eisenstein, x 2 2 is the minimal polynomial of 2 over Q, so Q[ 2] is 2 dimensional over Q. Since the minimal polynomial of 3 over Q is x 2 3 (by Eisenstein), the minimal polynomial of 3 over Q[ 2] must divide this. The only non-trivial divisors are linear, so we are really asking if 3 Q[ 2]. Since 1, 2 is a basis for Q[ 2] over Q, we would have 3 = a + b 2 with a, b Q, or 3 = a 2 + 2b 2 + 2ab 2. Hence ab = 0 and 3 = a 2 + 2b 2. Thus a = 0 and 3 = 2b 2, or b = 0 and 3 = a 2. Neither 3, nor 3/2 are rational, so this is not the case. Thus Q[ 2, 3] is a 2-dimensional Q[ 2] vector space, and hence Q[ 2, 3] is a 2 2 = 4 dimensional Q vector space. You could also show directly that 1, 2, 3, 6 is a basis over Q.

Linear Algebra A. (a) Straightforward. (b) For λ = 0, a basis for its eigenspace is {(1, 1, 1)}. For λ = 1, a basis for its eigenspace is {(1, 1, 0), (1, 0, 1)}. (c) A is diagonalizable since A has 3 linearly independent eigenvectors. In fact, P 1 AP = diag{0, 1, 1} where P = 1 1 1 1 1 0 1 0 1 B. (a) A map T : V W is a linear transformation if T (r 1 v 1 + r 2 v 2 ) = r 1 T (v 1 ) + r 2 T (v 2 ) for all vectors v 1, v 2 V and all scalars r 1, r 2 Q. (b) Let dim(v ) = m and dim(w ) = n. Fix two bases of V and W. Let A be the m n matrix representing the linear transformation T. Since T is surjective, m n and the rank of A is n. W.l.o.g., we may assume that the first n row vectors of A are linear independent. Denote the corresponding n n matrix by B. Then B is invertible. Let S : W V be the linear transformation corresponding to the n m matrix (B 1 0). Then T S is the identity map on W since it corresponds to the matrix (B 1 0) A which is the n n identity matrix. C. (a) Let v X. Then, (w, v) = 0 for all w X. Since Y X, (w, v) = 0 for all w Y. So v Y. Thus X Y. (b) For v Y, define a linear transformation α(v) Hom(X/Y, Q) by α(v)(w) = (w, v) for all w X. Note that α(v) is well-defined since α(v)(w) = (w, v) = 0 whenever w Y. Thus, we obtain a linear map α : Y Hom(X/Y, Q) sending v Y to α(v) Hom(X/Y, Q). Note that α(v) = 0 if and only if α(v)(w) = (w, v) = 0 for all w X, i.e., if and only if v X. So Ker(α) = X, and α induces an injection β : Y /X Hom(X/Y, Q). Finally, note that the vector spaces Y /X and Hom(X/Y, Q) have the same dimension (dim X dim Y ). Therefore, the injection β must be an isomorphism. D. Since A 2 i = A i, the minimal polynomial of A i divides λ(λ 1). So each A i is diagonalizable. Since the matrices A 1,..., A k commute, they can be simultaneously diagonalized. So there exists an invertible matrix P such that P 1 A i P is diagonal for all i = 1,..., k. Note that the entries of P 1 A i P are either 0 or 1. Since k P 1 A i P = I n, we may assume (w.l.o.g.) that the entries on the diagonal of

P 1 A i P are (r 1 +... + r i 1 ) many 0 s, followed by r i many 1 1, and followed by all the zeroes again (in particular, the rank of A i is r i ). So k a i (P 1 A i P ) = diag{a 1,..., a 1,..., a k,..., a k } (there are precisely r i many a i s on the diagonal). It follows that ( k ) ( k ) k det a i A i = det a i (P 1 A i P ) = where r i is the rank of A i. E. (a) Let {v, T (v),..., T n 1 (v)} be a basis of V. Since ST = T S, we have S ( T i (v) ) = T i( S(v) ). So the linear map S is uniquely determined by S(v). Note that S(v) = n 1 ( i=0 a it i (v) for some scalars a 0, a 1,..., a n 1. Then, S(v) = n 1 i=0 a it i) (v). Hence S = n 1 i=0 a it i. (b) We will work with matrices instead of linear operators. Let A be the matrix representing T. Let diag{n 1,..., N r } be the rational canonical form of A, and let p 1,..., p r be the corresponding invariant polynomials. Then, p 1... p r. Note that A (hence T ) has a cyclic vector if and only if r = 1. Assume r > 1. We will draw a contradiction. Let B = diag{n 1, 0,..., 0}. Then AB = BA. By the assumption, B = p(a) for some polynomial p. In particular, N 1 = p(n 1 ) and 0 = p(n r ). Since p r is the minimal polynomial of N r, we have p r p. So p 1 p, and 0 = p(n 1 ) = N 1 which is absurd. a r k k