## Linear Vector Spaces: Examples and Problems

### Example 1

Which of the following sets are orthonormal basis sets in the Euclidean vector space ?

• where and
• where and
##### SOLUTION

For the set we have:

Therefore, , , and are unit vectors. In addition, we have:

Therefore, the three vectors , , and are orthogonal to each other. Therefore, is an orthonormal basis set.
For the set we have:

Therefore, and are not orthogonal to each other. Therefore, is not an orthonormal basis set. In fact, we have which means that is linearly dependent, therefore, it is not even a basis set for . Notice that the symbol “.” is used in Mathematica for the dot product as shown below.

View Mathematica Code

e1 = {1, 0, 0};
e2 = {0, 1/Sqrt[2], 1/Sqrt[2]};
e3 = {0, 1/Sqrt[2], -1/Sqrt[2]};
e1.e1
e1.e2
e1.e3
e2.e2
e2.e3
e3.e3
ep1 = {1, 0, 0};
ep2 = {0, 1/Sqrt[2], 1/Sqrt[2]};
ep3 = {0, -1/Sqrt[2], -1/Sqrt[2]};
ep1.ep1
ep1.ep2
ep1.ep3
ep2.ep2
ep2.ep3
ep3.ep3

View Numpy Python Code

import numpy as np
e1 = np.array([1, 0, 0]); # Matrix []
e2 = np.array([0, 1/np.sqrt(2), 1/np.sqrt(2)]);
e3 = np.array([0, 1/np.sqrt(2), -1/np.sqrt(2)]);
ep1 = np.array([1, 0, 0]);
ep2 = np.array([0, 1/np.sqrt(2), 1/np.sqrt(2)]);
ep3 = np.array([0, -1/np.sqrt(2), -1/np.sqrt(2)]);
print("B1 =",e1,e2,e3)
print("B2 =",ep1,ep2,ep3)
print("Check orthogonality")
print("e1.e1 =",np.dot(e1,e1)) # dot operation
print("e2.e2 =",np.dot(e2,e2))
print("e3.e3 =",np.dot(e3,e3))
print("e1.e2 =",np.dot(e1,e2))
print("e1.e3 =",np.dot(e1,e3))
print("e2.e3 =",np.dot(e2,e3))
print("e'1.e'1 =",np.dot(ep1,ep1))
print("e'2.e'2 =",np.dot(ep2,ep2))
print("e'3.e'3 =",np.dot(ep3,ep3))
print("e'1.e'2 =",np.dot(ep1,ep2))
print("e'1.e'3 =",np.dot(ep1,ep3))
print("e'2.e'3 =",np.dot(ep2,ep3))


View Sympy Python Code

from sympy.matrices import Matrix
import sympy as sp
sp.init_printing(use_latex="mathjax")
e1 = Matrix([1, 0, 0]); # Matrix []
e2 = Matrix([0, 1/sp.sqrt(2), 1/sp.sqrt(2)]);
e3 = Matrix([0, 1/sp.sqrt(2), -1/sp.sqrt(2)]);
ep1 = Matrix([1, 0, 0]);
ep2 = Matrix([0, 1/sp.sqrt(2), 1/sp.sqrt(2)]);
ep3 = Matrix([0, -1/sp.sqrt(2), -1/sp.sqrt(2)]);
display("B1=",e1,e2,e3)
display("B2=",ep1,ep2,ep3)
display("Check orthogonality")
display("e1.e1=",e1.dot(e1)) # dot operation
display("e2.e2=",e2.dot(e2))
display("e3.e3=",e3.dot(e3))
display("e1.e2=",e1.dot(e2))
display("e1.e3=",e1.dot(e3))
display("e2.e3=",e2.dot(e3))
display("e'1.e'1=",ep1.dot(ep1))
display("e'2.e'2=",ep2.dot(ep2))
display("e'3.e'3=",ep3.dot(ep3))
display("e'1.e'2=",ep1.dot(ep2))
display("e'1.e'3=",ep1.dot(ep3))
display("e'2.e'3=",ep2.dot(ep3))

### Example 2

Find the angle between the two vectors , and . Also use the cross product operation to find the vector .

##### SOLUTION

To find the geometric angle between the two vectors and , we will use the dot product operation:

We have , . Therefore, and are orthogonal and .
The cross product between and gives the vector as follows:

View Mathematica Code

x = {1, 1, 1};
y = {-1, 2, -1};
z = Cross[x, y]
Norm[x]
Norm[y]
thetaxy = ArcCos[x.y/Norm[x]/Norm[y]]
(*You can also find the angle between the two vectors using the command VectorAngle*)
VectorAngle[x,y]

View Numpy Python Code

import numpy as np
from numpy.linalg import norm
x = np.array([1, 1, 1])
y = np.array([-1, 2, -1])
z = np.cross(x,y) # cross product
print("x =",x)
print("y =",y)
print("x\u00D7y =",z)
print("|x| =",norm(x)) #gives rounded value normalization
print("|y| =",norm(y))
# angle formula (a*b)/(norm a)(norm b)
print("\u03B8 =",np.arccos(np.dot(x,y)/norm(x)/norm(y)))

View Sympy Python Code

from sympy.matrices import Matrix
import sympy as sp
sp.init_printing(use_latex="mathjax")
x = Matrix([1, 1, 1])
y = Matrix([-1, 2, -1])
z = x.cross(y) # cross product
display("x=",x)
display("y=",y)
display("x\u00D7y=",z)
display("|x|=",x.norm()) # normalization
display("|y|=",y.norm())
# angle formula (a*b)/(norm a)(norm b)
display("\u03B8=",sp.acos(x.dot(y)/x.norm()/y.norm()))

#### Problems

1. Show that the following sets are subspaces of . What is the graphical representation of each subspace? Find two different basis sets for each subspace.
2. Show that the following sets are subspaces of . What is the graphical representation of each subspace? Find two different basis sets for each subspace.
3. Find three vectors that are orthogonal to .
4. Find three vectors that are orthogonal to .
5. Choose a value for such that , and are linearly independent
6. Choose two different sets of values for and such that , and are linearly dependent.
7. Verify that , and are linearly independent and then find the unique expansion of in the basis set .
8. Verify that , and are linearly independent and then find the unique expansion of in the basis set .
9. Find two different orthonormal basis sets and two different non-orthonormal basis sets for .
10. Find two different orthonormal basis sets and two different non-orthonormal basis sets for .
11. Find two different orthonormal basis sets and two different non-orthonormal basis sets for . The basis sets should include vector . Hint: An orthonormal basis set is a basis set whose vectors satisfy two conditions. The first condition is that the vectors in the basis set are orthogonal to each other and the second condition is that each vector has a unit norm.
12. Show that the following vectors are linearly dependent , , and .
13. Show that the following vectors are linearly dependent , , and .
14. Verify that the following vectors are linearly independent , , and . Then, find the unique expansion of in the basis set .
15. Verify that the following vectors are linearly independent , , and . Then, find the unique expansion of in the basis set .
16. Use the cross product to find a vector orthogonal to both and . Also, find the area of the parallelogram formed by the two vectors and .
17. Use the cross product to find a vector orthogonal to both and . Also, find the area of the parallelogram formed by the two vectors and .
18. For the shown cuboid, , , , and .
• Use the cross product operation to find two unit vectors orthogonal to the plane . What is the relationship between those two vectors?
• Use the cross product to find the area of the parallelogram .
• Find the angle between the vectors representing and .
Notice that the line geometric object starting at point and ending at point can be represented by a vector .
19. Determine if the following vectors , , , and d are linearly independent where , and while is a set of linearly independent vectors in .
20. Which of the following functions defined below satisfy the properties of a norm function (explain your answer). :
21. Let . Assume that . Show that is the zero vector. (Hint: Show that the components of in an orthonormal basis set are all equal to zero)