University of British Columbia
Math 307, Section 101 (Froese)
Final Exam, December 2015
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Question
Points
1
15
2
14
3
12
4
15
5
16
6
10
7
18
Total:
100
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in all examination papers, and must not take any examination material from
the examination room without permission of the examiner or invigilator.
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Additional Instructions:
• No notes, books or calculators are allowed. A MATLAB/Octave formula sheet is provided on the last page.
• Read the questions carefully and make sure you provide all the information that is asked for in the question.
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• Answer the questions in the space provided. Continue on the back of the page if necessary.
Page 1 of 14
Score
1. Let


4 0 0
A = 0 a 0 ,
0 0 2
√ 1 −1
.
B= 2
1
1
(a) (3 points) For what real values of a (if any) is kAk = 4?
(b) (3 points) For what real values of a (if any) is cond(A) = 4?
x
0
(c) (3 points) Compute the streching ratio kBxk/kxk, where x = 1 6=
.
x2
0
(d) (3 points) Use the calculation in the previous part to determine kBk and cond(B).
Page 2 of 14
   
1
1



(e) (3 points) Suppose C is a 3 × 3 matrix with cond(C) = 10. If C 1 = 0 and
1
0

  
1
1.1



C 1 + a = 0 , what are the possible values of a?
1
0
2. Let (xi , yi ), i = 1, . . . 4 be four points in the plane with x1 < x2 < x3 < x4 .
(a) (3 points) If the polynomial p(x) = a1 x3 + a2 x2 + a3 x + a4 interpolates the four
points, then the coefficient vector a = [a1 , a2 , a3 , a4 ]T satisfies an equation of the
form Aa = d. Write down A and d.
Page 3 of 14
(b) (3 points) If the polynomial p(x) = b1 x4 +b2 x3 +b3 x2 +b4 x+b5 interpolates the four
points, and also satisfies p0 (x4 ) = 0, then the coefficient vector b = [b1 , b2 , b3 , b4 , b5 ]T
satisfies an equation of the form Bb = d. Write down B and d.
(c) (4 points) If the polynomial p(x) = c1 x2 + c2 x + c3 interpolates the four points,
then the coefficient vector c = [c1 , c2 , c3 ]T satisfies an equation of the form Ca = e.
Write down C and e.
Page 4 of 14
(d) (4 points) For each of the equations in parts (a) (b) and (c) say whether you expect
there to be a solution. For the case(s) where you do not expect a solution, write
down the least squares equation. Do these have a solution? Give a reason. What
quantity is minimized when the least squares equation is satisfied?
Page 5 of 14
−−
3. Consider the chemical system consisting of the species H2 SO4 , HSO−
and H+ . In
4 , SO4
addition to the species H, S and O, we also regard the charge as a species q. Thus the
formula matrix is
H2 SO4
H
2

S
1
A= 

O
4
q
0

HSO−
4
1
1
4
−1
SO−−
4
0
1
4
−2
H+

1
0 
.
0 
1
After defining A in MATLAB/Octave, we compute
>rref(A)
ans =
1
0
0
0
0
1
0
0
>rref(A’)
ans =
-1
2
0
0
1
-1
0
0
1
0
0
0
0
1
0
0
0
4
0
0
1
-2
0
0
(a) (4 points) Write down a basis for N (A) and for N (AT ).
(b) (4 points) Write down the possible reactions for this system.
Page 6 of 14
(c) (4 points) If a sample contains 350 atoms of H, 200 atoms of S and 800 atoms of
O, what is the total charge q? (Hint: what subspace contains [350, 200, 800, q]T ?)
4. (a) (4 points) Write down two conditions that must be satisfied in order for the functions φn (t), for t ∈ [0, 1] and n ∈ Z to form an orthonormal set. Do the functions
e2πint satisfy these conditions?
√
(b) (3 points) Do the functions φn (t) = (1/ 2)e2πint on the larger interval t ∈ [0, 2],
form an orthonormal set?
P∞Can we expand any (sufficiently nice) function defined
for t ∈ [0, 2] in a series n=−∞ cn φn (t)
Page 7 of 14
(c) (4 points) Find the coefficients cn in the Fourier series
eiπt =
∞
X
cn e2πint
n=−∞
where t ∈ [0, 1].
(d) (4 points) What does Parseval’s formula say for the series in part (c)?
Page 8 of 14
5. Let
2 −1
A=
.
1
0
(a) (4 points) Is A diagonalizable? Give a reason.
(b) (4 points) Schur’s lemma states that there is a unitary matrix U and an upper
triangular matrix T such that A = U T U ∗ . Find U and T .
Page 9 of 14
(c) (4 points) What are T 2 and T 3 ? Guess a formula for T n for any positive integer n,
and use it to compute An .
(d) (4 points) Write down a formula for the nth term, xn , in the sequence defined by
the recurrence relation x0 = a, x1 = b and xn+1 = 2xn − xn−1 for n ≥ 1.
Page 10 of 14
6. Suppose A is an 5 × 5 real symmetric matrix defined in MATLAB/Octave. The commands
> x=rand(5,1)
>for k=1:50 y=(A-3*eye(5))\x; x=y/norm(y) end
yield output ending in
x =
0.12692
-0.32566
0.80572
-0.11046
-0.46524
x =
x =
-0.12692
0.32566
-0.80572
0.11045
0.46524
0.12692
-0.32566
0.80572
-0.11046
-0.46524
If the eigenvalues of A are 0, 0.5, 1.5, 2.5, 4 what output would you get for
(a) (4 points) dot(x,A*x)
(b) (3 points) dot(x,x)
(c) (3 points) dot(y,x)
Page 11 of 14
7. (a) (4 points) Let P = [pi,j ] be an n × n matrix. What does it mean to say that P is a
stochastic matrix? If P is stochastic, what can you say about the eigenvalues and
eigenvectors? What additional information do you have about the eigenvalues and
eigenvectors if P k has all positive entries for some k?
(b) (4 points) Draw the 4 site internet represented by the stochastic matrix


0 0 1/2 0
1/3 0 0 0

P =
1/3 1 0 0 .
1/3 0 1/2 1
(c) (3 points) By examining this internet or otherwise, find an eigenvector of P with
eigenvalue 1.
Page 12 of 14
(d) (3 points) Given that the eigenvalues
  of P satisfy λ1 = 1, |λ2 | = 0.65034, |λ3 | =
1

0

|λ4 | = 0.50624, what is limk→∞ P k 
0?
0
(e) (4 points) If we add damping with a damping factor α = 1/2 what is the new
1

0

stochastic matrix S? What can you say about limk→∞ S k 
0?
0
Page 13 of 14
Page 14 of 14
sum(x)
rand(12,4)
zeros(12,4)
ones(12,4)
eye(12)
eye(12,4)
linspace(1.2,4.7,100)
diag(x)
diag(x,n)
[A B; C D]
A(2:12,:)
A([1:4,6],:)
x(2) = 7
A(2,1) = 0
3*x
x+3
x+y
A*x
A*B
x.*y
A^3
cos(A)
sin(A)
x’
A’
A(2:12,4)
A(2:12,4:5)
A = [1 2; 3 4]
12 × 4 matrix with uniform random numbers in [0, 1)
12 × 4 matrix of zeroes
12 × 4 matrix of ones
12 × 12 identity matrix
12 × 4 matrix whose first 4 rows are the 4 × 4 identity
row vector of 100 equally spaced numbers from 1.2 to 4.7
matrix whose diagonal is the entries of x (other elements are zero)
matrix whose diagonal is the entries of x on diagonal n (other elements are
zero)
sum of the elements of x
define variable x to be 3
set x to the 1 × 3 row vector (1, 2, 3)
set x to the 3 × 1 vector (1,
2, 3)
1 2
set A to the 2 × 2 matrix
3 4
change x2 to 7
change A21 to 0
multiply each element of x by 3
add 3 to each element of x
add x and y element by element
product of matrix A and column vector x
product of two matrices A and B
element-wise product of vectors x and y
for a square matrix A, raise to third power
cosine of every element of A
sine of every element of A
transpose of vector x
transpose of vector A
the submatrix of A consisting of the second to twelfth rows of the fourth column
the submatrix of A consisting of the second to twelfth rows of the fourth and
fifth columns
the submatrix of A consisting of the second to twelfth rows of all columns
the submatrix of Aconsisting
of the first to fourth rows and sixth row
A B
creates the matrix
where A, B, C, D are block matrices (blocks must
C D
have compatible sizes)
x = 3
x = [1 2 3]
x = [1; 2; 3]
−1
π
√
pi
i
for k=1:10 ... end
hold on
hold off
plot3(x,y,z,’bo’)
plot(x,y,’bo’)
plot(x,y,’r-’)
semilogy(x,y,’bo’)
axis([-0.1 1.1 -3 5])
polyval(A)
roots(a)
[V D] = eig(A)
[Q R] = qr(A,0)
nextpow2(N)
fft(f,N)
vander(x)
polyval(a,x)
A\b
A^(-1)
rref(A)
det(A)
norm(A)
cond(A)
length(A)
norm(x)
the
the
the
the
the
the
the
the
solution x to Ax = b
inverse of A
reduced row echelon form of A
determinant of A
(operator) norm of A
condition number of A
larger of the number of rows and number of columns of A
norm (length) of a vector x
for loop taking k from 1 to 10 and performing the commands . . . for each
plots the points of y against the points of x using blue dots
plots the points of y against the points of x using red lines
plots y against x using a logarithmic scale for y
changes the axes of the plot to be from −0.1 to 1.1 for the x-axis and −3 to 5
for the y-axis
puts any new plots on top of the existing plot
any new plot commands replace the existing plot (this is the default)
plots the points of z against the points of x and y using blue dots
returns the Vandermonde matrix for the points of x
returns the values of the polynomial a1 xn−1 + a2 xn−2 + . . . an at the points of
x
returns the matrices Q and R in the QR factorization of A
calculates the next power of 2 of N
FFT transform of the vector f using N points (pads f with zeros if it has fewer
than N elements)
returns the coefficients of the characteristic polynomial of A
returns the solutions to a1 xn−1 + a2 xn−2 + . . . an = 0
returns the matrix V whose columns are normalized eigenvectors of A and the
diagonal matrix D of corresponding eigenvalues
returns
returns
returns
returns
returns
returns
returns
returns