Are Linear Transformations of Linearly Dependent Sets Also Linearly Dependent?

In summary, if A is a 3x3 Matrix and {v1, v2, v3} is a linearly dependent set of vectors in R^3, then {Av1, Av2, Av3} is also a linearly dependent set. This is because a linear transformation preserves the operations of vector addition and scalar multiplication. If the matrix A is invertible, then the converse is also true - if v1, v2, v3 are linearly independent, then Av1, Av2, Av3 are also linearly independent.
  • #1
Mola
23
0
If A is a 3x3 Matrix and {v1, v2, v3} is a linearly dependent set of vectors in R^3, then {Av1, Av2, Av3} is also a linearly dependent set?

Is this true? Can someone please explain why or why not??

What I think: I think it is true because I read that a linear transformation preserves the operations of vector addition and scalar multiplication.
 
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  • #2
If v1,v2,v3 are linearly dependent you can find constants a1, a2, a3 not all 0 such that
[tex]a_1v_1 + a_2v_2 + a_3v_3 = 0[/tex]
Now left-multiplying this by A you get:
[tex]A(a_1v_1+a_2v_2+a_3v_3) = A0=0[/tex]
Now use your rules for matrix arithmetic to derive:
[tex]a_1(Av_1)+a_2(Av_2)+a_3(Av_3)=0[/tex]
(HINT: Ak = kA for constants k, and A(v+w) = Av+Aw for vectors v, w where the expression makes sense).
 
  • #3
That makes sense. So if we have a1(Av1) + a2(Av2) + a3(Av3) = 0, then at least one of the constants could be zero and that will definitely result to a linearly dependent set.
Thanks.

That leads me to a related theory: Let's assume we are talking about {v1, v2, v3} being a linearly INDEPENDENT set now. If we multiply the vectors by the matrix A, how does it affect the independece? Would it make a differerence if the matrix A is invertible?
 
  • #4
Mola said:
That leads me to a related theory: Let's assume we are talking about {v1, v2, v3} being a linearly INDEPENDENT set now. If we multiply the vectors by the matrix A, how does it affect the independece? Would it make a differerence if the matrix A is invertible?

This is actually a quite interesting little question (well in my opinion anyway). First for fixed A, v1,v2,v3 note that if we take the contrapositive of your initial result we get:
If Av1, Av2, Av3 are linearly independent, then v1,v2,v3 are linearly independent.
so for linear independence it goes backwards. For an arbitrary matrix A we can not prove your new statement since we can just let A be the 0 matrix. However if A is invertible, then we can just go backwards by noting that if,
[tex]a_1Av_1+a_2Av_2+a_3Av_3 = 0[/tex]
Then we can left-multiply by [itex]A^{-1}[/itex] to get,
[tex]a_1v_1+a_2v_2+a_3v_3 = 0[/tex]
so if v1,v2,v3 are linearly independent and A is invertible, then Av1, Av2, Av3 are linearly independent.
 
  • #5
Thanks rasmhop... I did think "A" being an invertible matrix could make a difference but I didn't know how to prove it.
That was a very good help from you.
 

1. What does it mean for a set to be linearly dependent?

Linear dependence refers to the relationship between elements in a set. A set is considered linearly dependent if one or more of its elements can be expressed as a linear combination of the other elements in the set. In other words, at least one element in the set is not independent and can be written as a combination of the other elements.

2. How can I determine if a set is linearly dependent?

To determine if a set is linearly dependent, you can use the linear dependence test. This involves setting up a system of equations with the elements of the set as variables, and solving for the coefficients. If there exists a non-zero solution, then the set is linearly dependent. If the only solution is the trivial solution (all coefficients are zero), then the set is linearly independent.

3. Can a linearly dependent set contain a zero vector?

Yes, a linearly dependent set can contain a zero vector. In fact, a set containing only the zero vector is always linearly dependent. This is because any scalar multiple of the zero vector is still the zero vector, making it possible to express the zero vector as a linear combination of the other elements in the set.

4. What is the importance of understanding linearly dependent sets in linear algebra?

Linearly dependent sets are important in linear algebra because they can help us understand the structure of vector spaces. They also play a crucial role in solving systems of linear equations, as they can indicate whether a system has a unique solution, infinitely many solutions, or no solution at all. Additionally, knowing if a set is linearly dependent can help us determine a basis for a vector space.

5. Can a set with more elements than dimensions be linearly dependent?

Yes, it is possible for a set with more elements than dimensions to be linearly dependent. This is because linear dependence is determined by the relationships between the elements in the set, not the number of elements or dimensions. As long as there exists at least one element that can be expressed as a linear combination of the others, the set is considered linearly dependent.

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