Math 260 Exam 1 Solutions by Jerry L. Kazdan, Exams of Calculus

Solutions to exam 1 of math 260 by jerry l. Kazdan. It includes answers to ten questions covering topics such as linear spaces, linear maps, and systems of linear equations. The document also provides explanations for each solution.

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Math 260 Exam 1 Jerry L. Kazdan
Feb. 9, 2012 12:00 1:20
Directions This exam has 10 questions (10 points each). Closed book, no calculators or
computers– but you may use one 300 ×500 card with notes on both sides. Neatness counts.
1. Which of the following sets are linear spaces?
a) The points X= (x1, x2, x3) in R3with the property x12x3= 0 .
Solution: Yes obviously.
b) The set of solutions xof Ax = 0, where Ais an m×nmatrix.
Solution: Yes obviously.
c) The set of polynomials p(x) with R1
1p(x) cos 2x dx = 0.
Solution: Yes obviously.
d) The set of solutions y=y(t) of y00 + 4y0+y=x23. [Note: You are not being asked
to solve this differential equation. You are only being asked a more primitive question.]
Solution: No. The function y(x)0 does not satisfy this equation.
2. Let Sand Tbe linear spaces and L:STbe a linear map. Say V1and V2are (distinct!)
solutions of the equations LX =Y1while Wis a solution of LX =Y2. Answer the following
in terms of V1,V2, and W.
a) Find some solution of LX = 2Y13Y2.
Solution: For instance X:= 2V13W
b) Find another solution (other than W) of LX =Y2.
Solution: For instance X:= V2V1+W.
3. Say you have klinear algebraic equations in nvariables; in matrix form we write AX =Y.
Give a proof or counterexample for each of the following.
a) If n=kthere is always at most one solution.
Solution: Counterexample: A= 0 matrix.
b) If n>k, given any Yyou can always solve AX =Y.
Solution: Counterexample: Ais the zero matrix.
c) If n>k the nullspace of Ahas dimension greater than zero.
Solution: Yes, by the Rank Theorem: dim N(A) = ndim I(A)nk1
d) If n<k then for some Ythere is no solution of AX =Y.
Solution: Yes, by the Rank Theorem: k > n = dim I(A) + dim N(A)dim I(A) . Thus
the dimension of the image of Ais less than k.
e) If n<k the only solution of AX = 0 is X= 0.
Solution: Counterexample: let Abe the zero matrix.
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Math 260 Exam 1 Jerry L. Kazdan

Feb. 9, 2012 12:00 – 1:

Directions This exam has 10 questions (10 points each). Closed book, no calculators or computers– but you may use one 3′′^ × 5 ′′^ card with notes on both sides. Neatness counts.

  1. Which of the following sets are linear spaces? a) The points X = (x 1 , x 2 , x 3 ) in R^3 with the property x 1 − 2 x 3 = 0. Solution: Yes – obviously. b) The set of solutions x of Ax = 0, where A is an m × n matrix. Solution: Yes – obviously. c) The set of polynomials p(x) with

− 1 p(x) cos 2x dx^ = 0. Solution: Yes – obviously. d) The set of solutions y = y(t) of y′′^ + 4y′^ + y = x^2 − 3. [Note: You are not being asked to solve this differential equation. You are only being asked a more primitive question.] Solution: No. The function y(x) ≡ 0 does not satisfy this equation.

  1. Let S and T be linear spaces and L : S → T be a linear map. Say V 1 and V 2 are (distinct!) solutions of the equations LX = Y 1 while W is a solution of LX = Y 2. Answer the following in terms of V 1 , V 2 , and W. a) Find some solution of LX = 2Y 1 − 3 Y 2. Solution: For instance X := 2V 1 − 3 W b) Find another solution (other than W ) of LX = Y 2. Solution: For instance X := V 2 − V 1 + W.
  2. Say you have k linear algebraic equations in n variables; in matrix form we write AX = Y. Give a proof or counterexample for each of the following. a) If n = k there is always at most one solution. Solution: Counterexample: A = 0 matrix. b) If n > k , given any Y you can always solve AX = Y. Solution: Counterexample: A is the zero matrix. c) If n > k the nullspace of A has dimension greater than zero. Solution: Yes, by the Rank Theorem: dim N (A) = n − dim I(A) ≥ n − k ≥ 1 d) If n < k then for some Y there is no solution of AX = Y. Solution: Yes, by the Rank Theorem: k > n = dim I(A) + dim N (A) ≥ dim I(A). Thus the dimension of the image of A is less than k. e) If n < k the only solution of AX = 0 is X = 0. Solution: Counterexample: let A be the zero matrix.
  1. Find a real 2 × 2 matrix A such that A^4 = I but A^2 6 = I.

Solution: For instance, A is a rotation by π/2 (90 degrees): A :=

1 0

  1. Find a quadratic polynomial p(x) that passes through the three points (− 1 , 0), (0, −1), and (2, 3). [Don’t bother to “simplify” your answer.]

Solution: This is simple enough that the computation is fairly easy using many different bases for the space of quadratic polynomials. I’ll use a Lagrange basis:

p 1 (x) :=

x(x − 2) −1(− 1 − 2)

; p 2 (x) :=

(x + 1)(x − 2) 1(0 − 2)

; p 3 (x) :=

(x + 1)x (2 + 1)

Then

p(x) = 0p 1 (x) + (−1)p 2 (x) + 3p 3 (x) =

(x + 1)(x − 2) 2

(x + 1)x 6

= x^2 − 1.

  1. Let A : R^3 → R^2 and B : R^2 → R^3 be given matrices, and let C := BA : R^3 → R^3. Show that C cannot be invertible.

Solution: Any proof that begins with C−^1 = A−^1 B−^1 is almost certainly nonsense since this presumes A and B are invertible. But if a matrix is invertible, it must be square (why?), and neither A nor B are square. Note that D := AB : R^2 → R^2 can be invertible (Simple Example?).

Here is a solution. If C is invertible, it must be one-to-one. But A can’t be one-to-one (why?) and anything in the nullspce of A is also in then nullspace of C.

Another solution. If C is invertible, it must be onto. But B can’t be onto (why?) and anything in the image of C must also be in then image of B.

  1. In R^3 , find the distance from the point P := (1, 1 , 0) to the plane x + 2y − z = 0.

Solution: There are several approaches. One begins with the observation that the vector N := (1, 2 , −1) is orthogonal to this plane because if V := (x, y, z) is in this plane then 〈V, N 〉 = 0. Think of P as a vector from the origin (which is in the plane) to the point P. From a sketch, it is clear that the distance from P to this plane is ‖P ‖ cos θ , where θ is the angle between the vectors P and N. But 〈P, N 〉 = ‖P ‖‖N ‖ cos θ. Thus

Distance =

〈P, N 〉

‖N ‖

Since we might have used −N for the normal to the plane, to find the distance, if needed we should insert the absolute value in the final step.