Linear Algebra : Operations and Properties

Study concepts, example questions & explanations for Linear Algebra

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Example Questions

Example Question #11 : Eigenvalues And Eigenvectors Of Symmetric Matrices

Possible Answers:

Correct answer:

Explanation:

Example Question #12 : Eigenvalues And Eigenvectors Of Symmetric Matrices

,

where  is a real number.

For  to have two real eigenvalues, what must be true for  ?

Possible Answers:

 or 

 can be any real number.

 or 

Correct answer:

 can be any real number.

Explanation:

Any real value of  makes  a symmetric matrix with real entries. It holds that any eigenvalues of  must be real regardless of the value of .

Example Question #13 : Eigenvalues And Eigenvectors Of Symmetric Matrices

Give the set of eigenvalues of  in terms of , if applicable.

Possible Answers:

The only eigenvalue is 0.

The eigenvalues are  and .

The eigenvalues are 0 and .

The eigenvalues are 0 and .

The only eigenvalue is .

Correct answer:

The eigenvalues are 0 and .

Explanation:

An eigenvalue of  is a zero of the characteristic equation formed from the determinant of , so find this determinant as follows:

Subtracting elementwise:

Set the determinant to 0 and solve for :

The determinant can be found by taking the upper-left-to-lower-right product and subtracting the upper-right-to-lower-left product:

,

so the eigenvalues of this matrix are 0 and .

 

 

Example Question #861 : Linear Algebra

That last question dealt with isomorphism. This question is meant to point out the difference between isomorphism and homomorphisms. 

A homomorphism is a mapping between vector spaces that 

Possible Answers:

Preserves vector addition and is injective

onto and 1-to-1

Preserves scalar multiplication and is onto

Preserves vector addition and scalar multiplication

Correct answer:

Preserves vector addition and scalar multiplication

Explanation:

By definition a homomorphism is a mapping that preserves vector addition and scalar multiplication.

 

Compare this to the previous problem. An isomorphism is a homomorphism that is also 1-to-1 and onto. Therefore isomorphism is just a special homomorphism. In other words, every isomorphism is a homomorphism, but not all homomorphisms are an isomorphisms. 

Example Question #862 : Linear Algebra

Consider the mapping . Can f be an isomorphism?

(Hint: Think about dimension's role in isomorphism) 

Possible Answers:

No

Yes

not enough information

Correct answer:

No

Explanation:

No, f, cannot be an isomorphism. This is because  and  have different dimension. Isomorphisms cannot exist between vector spaces of different dimension.

Example Question #863 : Linear Algebra

Isomorphism is an important concept in linear algebra. To be able to tell if a mapping is isomorphic, it is important to be able to know what an isomorphism is.

Let f be a mapping between vector spaces V and W. Then a mapping f is an isomorphism if it is 

Possible Answers:

Onto (surjective)

Preserves vector addition

1-to-1 (injective)

Preserves scalar multiplcation

All answers.

Correct answer:

All answers.

Explanation:

An isomorphism is homomorphism (preserves vector addition and scalar multiplcation) that is bijective (both onto and 1-to-1). Therefore an isomorphism is a mapping that is

1) onto

2) 1-to-1

3) Preserves vector addition

4) Preserves scalar multiplcation

Example Question #4 : Linear Mapping

In the previous question, we said an isomorphism cannot be between vector spaces of different dimension. But are all homomorphisms between vector spaces of the same dimension an isomorphism?

Consider the homomorphism . Is f an isomorphism?

Possible Answers:

Not enough information

Yes

No

Correct answer:

Not enough information

Explanation:

The answer is not enough information. The reason is that it could be an isomorphism because it is between vector spaces of the same dimension, but that doesn't mean it is.

 

For example:

Consider the zero mapping f(x,y)= (0,0).

This mapping is not onto or 1-to-1 because all elements go to the zero vector. Therefore it is not an isomorphism even though it is a mapping between spaces with the same dimension. 

 

Another example:

Consider the identity mapping f(x,y) = (x,y)

This is an isomorphism. It clearly preserves structure and is both onto and 1-to-1. 

 

Thus f could be an isomorphism (example identity map) or it could NOT be an isomorphism ( Example the zero mapping)

Example Question #5 : Linear Mapping

Let f be a mapping such that 

 

Let f be defined such that 

Is f 1-to-1 and onto?

Possible Answers:

No, it is not 1-to-1 but it is onto

No, it is 1-to-1 and not onto

No, it is not 1-to-1 and not onto

Yes

Correct answer:

No, it is not 1-to-1 and not onto

Explanation:

f is not 1-to-1 and it is not onto.

f is not onto because all of is not in the image of f. For example, the vector (1,1) is not in the image of f.

 

f is not 1-to-1. For example, the vector (1,1) and (1,0) both go to the same vector.

Ie f(1,1) = f(1,0). Therefore f is not 1-to-1.

Example Question #864 : Linear Algebra

Let f be a mapping such that 

 

Let f be defined such that 

Is f an isomorphism?

(Hint: Consider the zero vector)

Possible Answers:

Yes

No, it is not a homomorphism

No, it is not 1-to-1

No, it is not onto

Correct answer:

No, it is not a homomorphism

Explanation:

f is 1-to-1 and onto but it is not a homomorphism. Therefore it is not an isomorphism. To see this consider f(0,0) = (0,5)

 

A homomorphism always takes the zero vector to the zero vector. This particular mapping does not. Thus it does not preserve structure ie not a homomorphism.

 

 

Example Question #7 : Linear Mapping

The last question showed us isomorphisms must be between vector spaces of the same dimension. This question now asks about homomorphisms. 

Consider the mapping . Can f be a homomorphism?

Possible Answers:

No

not enough information

Yes

Correct answer:

Yes

Explanation:

The answer is yes. There is no restriction on dimension for homomorphism like there is for isomorphism. Therefore f could be a homomorphism, but it is not guaranteed. 

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