Mat240 assignment (a) Find the equation of the plane containing the following points in space. A(2, -5,-1), B(0,4,6), C(-3,7,1)

Similar documents
Vector Spaces 4.1 Vectors in n Spaces

Vector Spaces - Definition

Solution to Set 6, Math W = {x : x 1 + x 2 = 0} Solution: This is not a subspace since it does not contain 0 = (0, 0) since

Solution to Set 7, Math 2568

6. Orthogonality and Least-Squares

MATH 221: SOLUTIONS TO SELECTED HOMEWORK PROBLEMS

Inner Product Spaces 5.2 Inner product spaces

Department of Aerospace Engineering AE602 Mathematics for Aerospace Engineers Assignment No. 4

APPENDIX: MATHEMATICAL INDUCTION AND OTHER FORMS OF PROOF

Vector Spaces and Subspaces

Spring, 2006 CIS 610. Advanced Geometric Methods in Computer Science Jean Gallier Homework 1

Lecture 9: Vector Algebra

MATH SOLUTIONS TO PRACTICE PROBLEMS - MIDTERM I. 1. We carry out row reduction. We begin with the row operations

MAT 445/ INTRODUCTION TO REPRESENTATION THEORY

Analytical Geometry. 2.4 The Hyperbolic Quadric of PG(3,F)

= (c + a,d + b) = (c, d) + (a,b). (0, 0) + (a,b) = (0 + a,0 + b) = (a,b) (a,b) + ( a, b) = (a + a,b + b) = (0,0) = 0.

Math Linear Algebra II. 1. Inner Products and Norms

acclamation. sophomores, their roomer, George P. Burdell, who

Math 24 Winter 2010 Sample Solutions to the Midterm

MATH 304 Linear Algebra Lecture 20: Review for Test 1.

4.1 Distance and Length

On a generalization of the Gaussian plane to three dimensions

EXERCISE SET 5.1. = (kx + kx + k, ky + ky + k ) = (kx + kx + 1, ky + ky + 1) = ((k + )x + 1, (k + )y + 1)

Definition 1. A set V is a vector space over the scalar field F {R, C} iff. there are two operations defined on V, called vector addition

Resolution of Singularities in Algebraic Varieties

Math Linear Algebra

2 so Q[ 2] is closed under both additive and multiplicative inverses. a 2 2b 2 + b

The Gram-Schmidt Process 1

Chapter 3. Vector spaces

Linear Algebra. Hoffman & Kunze. 2nd edition. Answers and Solutions to Problems and Exercises Typos, comments and etc...

A Note on Operators in Hilbert C*-Modules

Vector Spaces. EXAMPLE: Let R n be the set of all n 1 matrices. x 1 x 2. x n

A Simple Turbulence Closure Model

Lecture 20: 6.1 Inner Products

A Simple Turbulence Closure Model. Atmospheric Sciences 6150

Geometry of Vector Spaces

Jim Lambers MAT 610 Summer Session Lecture 1 Notes

6.1. Inner Product, Length and Orthogonality

Review for Exam 2 Solutions

Linear Algebra. 1.1 Introduction to vectors 1.2 Lengths and dot products. January 28th, 2013 Math 301. Monday, January 28, 13

We now begin with vector calculus which concerns two kinds of functions: Vector functions: Functions whose values are vectors depending on the points

Fall, 2003 CIS 610. Advanced geometric methods. Homework 1. September 30, 2003; Due October 21, beginning of class

= (c + a,d + b) = (c, d) + (a,b). (0, 0) + (a,b) = (0 + a,0 + b) = (a,b) (a,b) + ( a, b) = (a + a,b + b) = (0,0) = 0.

MAT2342 : Introduction to Applied Linear Algebra Mike Newman, fall Projections. introduction

Vertex Operator Algebra Structure of Standard Affine Lie Algebra Modules

v = v 1 2 +v 2 2. Two successive applications of this idea give the length of the vector v R 3 :

15B. Isometries and Functionals 1

A Note on the Number of Squares in a Partial Word with One Hole

Solutions for Math 225 Assignment #4 1

APPM 3310 Problem Set 4 Solutions

Vector Spaces. distributive law u,v. Associative Law. 1 v v. Let 1 be the unit element in F, then

ORTHOGONALITY AND LEAST-SQUARES [CHAP. 6]

Math 4377/6308 Advanced Linear Algebra

Infinite-Dimensional Triangularization

MTH5102 Spring 2017 HW Assignment 1: Prob. Set; Sec. 1.2, #7, 8, 12, 13, 20, 21 The due date for this assignment is 1/18/17.

Math 4377/6308 Advanced Linear Algebra

Unit I Vector Spaces. Outline. definition and examples subspaces and more examples three key concepts. sums and direct sums of vector spaces

Solutions to the Final Exam, Math 53, Summer 2012

Worksheet for Lecture 23 (due December 4) Section 6.1 Inner product, length, and orthogonality

THE RING OF POLYNOMIALS. Special Products and Factoring

Realizations of Loops and Groups defined by short identities

Math 313 Midterm I KEY Winter 2011 section 003 Instructor: Scott Glasgow

MATH 260 LINEAR ALGEBRA EXAM II Fall 2013 Instructions: The use of built-in functions of your calculator, such as det( ) or RREF, is prohibited.

Homework 2 Solutions

Lecture 11: Vector space and subspace

6. The scalar multiple of u by c, denoted by c u is (also) in V. (closure under scalar multiplication)

12. Special Transformations 1

Math 24 Spring 2012 Questions (mostly) from the Textbook

b 1 b 2.. b = b m A = [a 1,a 2,...,a n ] where a 1,j a 2,j a j = a m,j Let A R m n and x 1 x 2 x = x n

Transpose & Dot Product

6.4 BASIS AND DIMENSION (Review) DEF 1 Vectors v 1, v 2,, v k in a vector space V are said to form a basis for V if. (a) v 1,, v k span V and

Vector Spaces 4.2 Vector Spaces

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx)

Lecture 23: 6.1 Inner Products

Ring Sums, Bridges and Fundamental Sets

Linear and Bilinear Algebra (2WF04) Jan Draisma

DEF 1 Let V be a vector space and W be a nonempty subset of V. If W is a vector space w.r.t. the operations, in V, then W is called a subspace of V.

Classification of Associative Two-Dimensional Algebras

Transpose & Dot Product

XV - Vector Spaces and Subspaces

Vector Geometry. Chapter 5

Chapter 2. Vectors and Vector Spaces

NAME MATH 304 Examination 2 Page 1

Math 416, Spring 2010 Matrix multiplication; subspaces February 2, 2010 MATRIX MULTIPLICATION; SUBSPACES. 1. Announcements

Linear Algebra Highlights

August 23, 2017 Let us measure everything that is measurable, and make measurable everything that is not yet so. Galileo Galilei. 1.

Math 302 Test 1 Review

What is a Linear Space/Vector Space?

Notes on Linear Algebra

Problem Set 1. Homeworks will graded based on content and clarity. Please show your work clearly for full credit.

(here, we allow β j = 0). Generally, vectors are represented as column vectors, not row vectors. β 1. β n. crd V (x) = R n

Solution to Homework 1

MATH 304 Linear Algebra Lecture 8: Vector spaces. Subspaces.

Vector Space Basics. 1 Abstract Vector Spaces. 1. (commutativity of vector addition) u + v = v + u. 2. (associativity of vector addition)

MATH 260 LINEAR ALGEBRA EXAM III Fall 2014

Linear algebra II Tutorial solutions #1 A = x 1

Linear Algebra (Math-324) Lecture Notes

Matrix Completion Problems for Pairs of Related Classes of Matrices

Two Proofs of Commute Time being Proportional to Effective Resistance

Every 3-connected, essentially 11-connected line graph is hamiltonian

Transcription:

Mat240 assignment 2 1.1--3 (a) Find the equation of the plane containing the following points in space. A(2, -5,-1), B(0,4,6), C(-3,7,1) Vector from point A to point B is u = (0,4,6)-(2, -5,-1) = <-2, 9, 7> vector from point A to point C is v = (-3,7,1)-(2, -5,-1) = <-5, 12, 2> Know one point A(2, -5,-1) and two vectors u= <-2, 9, 7> and v= <-5, 12, 2> in the plane. x= (2, -5,-1)+ su+t v = (2, -5,-1) + s <-2, 9, 7> + t <-5, 12, 2> where s, t R. 1.2--1. True or false. In any vector space, ax=bx implies that a=b. (F) not so when x=0 In any vector space, ax=ay implies that x=y. (F) not so when a=0 18. Let V= {( a 1, a 2 ) : a 1, a 2 R}. For (a 1,a 2 ), ( b 1,b 2 ) V and c R, define (a 1, a 2 ) + (b 1, b 2 ) = (a 1 +2b 1, a 2 +3b 2 ) and c(a 1,a 2 ) = (ca 1,ca 2 ). Is V a vector space over R with these operations? Solution: V is not a vector space, since additive associativity (x+y)+z=x+(y+z) fails. Counter example: ((2,2)+(1,1)) + (½, ¹ ₃)= (2+2, 2+3) + (½, ¹ ₃) = (4,5) + (½, ¹ ₃) = (4+1, 5+1) = (5,6) But (2,2) + ((1,1)+(½, ¹ ₃)) = (2,2) + (1+1, 1+1) = (2,2)+(2+2) = (2+2 2, 2+2 3) = (2+4, 2+6) = (6,8) 1

21. Let V and W be vector spaces over a field F. Let Z= {(v,w): v V and w W}. Prove that Z is a vector space over F with operations (v 1, w 1 ) + (v 2,w 2 ) = (v 1 +v 2, w 1 +w 2 ) and c(v 1, w 1 ) = (cv 1, cw 1 ). Proof: Generally, the first component of a vector in Z inherits vector space properties from V, while the second component of a vector in Z inherits vector space properties from W. 1) since V is a vector space, and W is a vector space, (v₁,u₁), (v₂,u₂) V, (v₁,u₁)+(v₂,u₂)= (v₁+v₂, u₁+u₂) =(v₂,u₂)+(v₁,u₁)=(v₂+v₁, u₂+u₁) for the first component, v₁+v₂ = v₂+v₁ (x₁,w₁), (x₂,w₂) W, (x₁,w₁)+(x₂,w₂)=(x₁+x₂, w₁+w₂)=(x₂,w₂)+(x₁,w₁)=(x₂+x₁, w₂+w₁) for the second component, w₁+w₂ = w₂+w₁ By definition, (v 1, w 1 ) + (v 2,w 2 ) = (v 1 +v 2, w 1 +w 2 )= (v₂+v₁, w₂+w₁) =(v 2,w 2 ) + (v 1, w 1 ) additive commutativity holds for Z. 2) since V and W are vector spaces, (v₁,u₁), (v₂,u₂), (v₃,u₃) V, ((v₁,u₁)+(v₂,u₂)) + (v₃,u₃) = (v₁,u₁)+ ((v₂,u₂) + (v₃,u₃)) for the first component, (v₁+v₂)+ v₃ = v₁+ (v₂+ v₃) (x₁,w₁), (x₂,w₂), (x₃,w₃) W, ((x₁,w₁)+(x₂,w₂)) + (x₃,w₃) = (x₁,w₁)+ ((x₂,w₂) + (x₃,w₃)) for the second component, (w₁+w₂) + w₃ =w₁+ (w₂+ w₃) ((v₁+v₂) + v₃, (w₁+w₂)+ w₃) = (v₁+ (v₂+ v₃), w₁+ (w₂+ w₃)) By definition, ((v₁,w₁ ) + (v₂, w₂)) + (v₃,w₃) = (v₁,w₁ ) + ((v₂, w₂) + (v₃,w₃)) where (v₁,w₁ ), (v₂, w₂), (v₃,w₃) Z additive associativity holds for Z. 3) V,W are vector spaces zero vector 0v for V and zero vector 0w for W. the zero vector 0z for Z can be formed by taking the first component of 0v, and the second component of 0w. check that (0 v,0 w ) is the zero vector in Z. (v,w)+(0 v,0 w ) = (v+0 v, w+0 w )= (v,w) 4) since (v,u) V, (-v,-u) such that (v,u)+(-v,-u)=0v v, -v s.t. v+(-v)=0 (x,w) W, (-x,-w) such that (x,w)+(-x,-w)=0w w, -w s.t. w+(-w)=0 (v,w) Z, (-v,-w) such that (v,w) + (-v,-w) = 0z 5) (v,u) V, 1(v,u)=(v,u) 1 v=v (x,w) W, 1(x,w)=(x,w) 1 w=w by definition, 1(v,w)=(1 v, 1 w) where c=1, but (1 v, 1 w) = (v,w) 1(v,w)= (v,w) 2

6) a,b F, (v,u) V, a(b(v,u))= (ab)(v,u) and (x,w) W, a(b(x,w))= (ab)(x,w) a(bv)= (ab)v and a(bw)= (ab)w (*) (v,w) Z, a(b(v,w)) a(bv,bw) (a(bv), a(bw)) where c=b where c=a = ((ab)v, (ab)w) by (*) (ab)(v,w) where c=ab 7) c F, (v₁,u₁), (v₂,u₂) V, c((v₁,u₁)+(v₂,u₂))= c(v₁,u₁)+c(v₂,u₂) c(v₁+v₂)=cv₁+cv₂ (x₁,w₁), (x₂,w₂) W, c((x₁,w₁)+(x₂,w₂))= c(x₁,w₁)+c(x₂,w₂) c(w₁+w₂)=cw₁+cw₂ (v₁,w₁), (v₂, w₂) Z, c((v₁,w₁)+ (v₂, w₂))= c(v₁+v₂)+ c(w₁+w₂)= (cv₁+cv₂, cw₁+cw₂) = c(v₁,w₁)+c(v₂,w₂) 8) a,b F, (v,u) V, (a+b)(v,u)=a(v,u)+b(v,u)=(av+bv, au+bu) (a+b)v= av+bv (x,w) W, (a+b)(x,w)=a(x,w)+b(x,w)=(ax+bx,aw+bw) (a+b)w= aw+bw (v,w) Z, (a+b)(v,w)=(av+bv, aw+bw)= a(v,w)+b(v,w) 1.3--8. Determine whether the sets are subspaces of R³ under the operations of addition and scalar multiplication defined on R³. A. W 1 = {(a 1, a 2, a 3 ) R³ : a 1 =3a 2 & a 3 = a 2 } Every vector in W 1 is of the form (a 1, a 2, a 3 ) = (3a 2, a 2, a 2 ) = a 2 (3, 1, -1) where a 2 is a parameter. Geometrically, W 1 is a line along the vector (3, 1, -1). The sum of any two vectors in W 1 is also on the line; scalar multiplication will only change the length of the line segment. When a 2 =0, (a 1, a 2, a 3 )=(0,0,0) 0 R³ W 1 or the line is through the origin. W 1 is a subspace of R³ B. W 2 = {(a 1, a 2, a 3 ) R³ : a 1 = a 3 +2 } Every vector in W 2 is of the form (a 1, a 2, a 3 )=(a 3 +2, a 2, a 3 )= (2,0,0) + a 2 (0, 1, 0)+ a 3 (1,0,1) where a 2, a 3 are parameters. This is a plane spanned by vectors (0, 1, 0) and (1,0,1). When a 2 =0= a 3, (a 1, a 2, a 3 )=(2,0,0) 0 R³ W 2 W 2 is not a subspace of R³ 3

C. W 3 = {(a 1, a 2,a 3 ) R³ : 2a 1 7a 2 + a 3 = 0 } Every vector in W 3 is of the form (a 1, a 2, a 3 )=(a 1, a 2, -2a 1 +7a 2 )= a 1 (1,0,-2) + a 2 (0, 1, 7) When a 1 =0=a 2, (a 1, a 2, a 3 )=(0,0,0) 0 R³ W 3 This is a plane through the origin W 3 is a subspace of R³ D. W 4 = {(a 1, a 2,a 3 ) R³ : a 1 4a 2 a 3 = 0 } Every vector in W 4 is of the form (a 1, a 2, a 3 )=(4a 2 + a 3, a 2, a 3 )= a 2 (4,1,0) + a 3 (1, 0, 1). When a 2 =0=a 3, (a 1, a 2, a 3 )=(0,0,0) 0 R³ W 4 This is a plane through the origin. W 4 is a subspace of R³ E. W 5 = {(a 1, a 2, a 3 ) R³: a 1 + 2a 2 3a 3 = 1 } v W 5, v= (a 1, a 2, a 3 ) = (1-2a 2 + 3a 3, a 2, a 3 ) = (1,0,0) + a 2 (-2, 1, 0) + a 3 (3, 0, 1) when a 2 = 0 = a 3, v=(1,0,0) W 5 represents a plane not through the origin W 5 is a not subspace of R³ since 0 R³ W 5 F. W 6 = {(a 1, a 2, a 3 ) R³: 5 a 1 ² + 6 a 3 ² = 0 } 1 Notice that when a 2 = 0, 5 a 1 ² + 6 a 3 ² = 0 (a 1, a 2, a 3 ) = (0,0,0) 0 R³ W 6 W 6 is a cone surface in R³ 2 c F, 5(ca 1 )² 3(ca 2 )² + 6(ca 3 )² = c²(5 a 1 ² + 6 a 3 ² ) = c²(0) = 0 (c(a 1, a 2, a 3 )) W 6 W 6 is closed under scalar multiplication. 3 But for any two vectors (u,v,w) &(x,y,z) W 6 their sum (u,v,w)+(x,y,z) = (u+x, v+y, w+z) But (a 1, a 2, a 3 ) = (u+x, v+y, w+z) does not necessarily satisfy the equation 5 a 1 ² + 6 a 3 ² = 0 5(u+x) ² -3(v+y) ² + 6(w+z) ² = 5(u ² +x ² +2ux) 3(v ² +y ² +2vy) + 6(w ² +z ² +2wz) = (5u ² 3v ² +6w ² ) + (5x ² 3y ² +6z ² )+ 2(5ux 3vy + 6wz) = 0 +0 +2(5ux 3vy + 6wz) where the cross terms are not guaranteed to get cancelled. W 6 is not closed under addition. Hence, W 6 is not a subspace. 4

19. Let W 1 and W 2 be subspaces of a vector space V. Prove that W 1 W2 is a subspace of V W 1 W 2 or W 2 W 1 First prove : Suppose W 1 W 2 or W 2 W 1, if W 1 W 2, then W 1 W2 = W2, which is a subspace of V. if W 2 W 1, then W 1 W2 = W1, which is also a subspace of V. In either case, W1 W2 is a subspace of V. Now prove indirectly by a contradiction: Assume W 1 W2 is a subspace of V, but W 1 W 2 and W 2 W 1, now look for a contradiction. W1 W2 a vector u W2 but u W1 u W 1 W2 W 2 W 1 a vector ( *) v W1 but v W2 v W 1 W2 W 1 W2 is a subspace of V (u+v) W 1 W2 By property of additive closure of a subspace. (u+v) W 1 or (u+v) W2. Assume that (u+v) W 1. But u W1 its inverse (-u) W 1 W 1 is a subspace of V (-u)+(u+v) W 1 But (-u)+(u+v) = ((-u) +u) + v by additive closure of a subspace by additive associativity of a vector space = 0 + v = v W 1 a contradiction with assumption (*) Assumption W2 W1 must be wrong, i.e. W2 W1 holds so does W1 W2 or W2 W1 5