Prove Linear Independence of Vector Sums

In summary, if vectors v1 and v2 are linearly independent, then their sum (v1 + v2) is also linearly independent.
  • #1
canephalanx
3
0
How can I prove given an arbitrary set of vectors v1 and v2, given they are linearly independent, that their sum (v1 + v2) is also linearly independent?
 
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  • #2
Linearly independent from what?
 
  • #3
let me rephrase that, how can i show that v1,v2, and v1+v2 is linearly independent given v1 and v2 is linearly independent. I seemed to have left out a key statement.
 
  • #4
You can't. Try to find the linear dependency
 
  • #5
I see. How can I prove otherwise?
 
  • #6
Well, how do you prove that a set of vectors is linearly dependent?
 
  • #7
[tex]\vec{v_{1}}, \vec{v_{1}}, \mbox{ and }\vec{v_1}+\vec{v_2}[/tex] are linearly independent if the only solution to

[tex]a\vec{v_{1}}+b\vec{v_{2}}+c(\vec{v_{1}}+\vec{v_{2}})=0[/tex]

is [tex]a=0, b=0, c=0[/tex].

Is this the case, or can you find other values that satisfy this equation?
 
  • #8
canephalanx said:
let me rephrase that, how can i show that v1,v2, and v1+v2 is linearly independent given v1 and v2 is linearly independent. I seemed to have left out a key statement.

The set {v1, v1, v1 + v2 } is always linearly dependent, since the third one listed is a linear combination of the first two.
 
  • #9
JThompson said:
[tex]\vec{v_{1}}, \vec{v_{1}}, \mbox{ and }\vec{v_1}+\vec{v_2}[/tex] are linearly independent if the only solution to

[tex]a\vec{v_{1}}+b\vec{v_{2}}+c(\vec{v_{1}}+\vec{v_{2}})=0[/tex]

is [tex]a=0, b=0, c=0[/tex].

Is this the case, or can you find other values that satisfy this equation?
Well, that reduces to (a+ c)v1+ (b+ c)v1= 0. Since v1 and v2 are independent, you must have a+ c= 0 and b+ c= 0. Obviously a= b= c is one solution to that but those are only two equations in three unknows. We can typically solve two equations in two unknowns. Okay, solve for a and b, say, treating c as a number. Then let c be whatever you want.

Solving for a and b "in terms of c" gives a= -c and b= -c. Take c to be anything you like and find a and b. If you happen to select c= 0, then, of course, you get a= b= c= 0. But what if you select c= 1?
 

FAQ: Prove Linear Independence of Vector Sums

What is "Prove Linear Independence of Vector Sums"?

"Prove Linear Independence of Vector Sums" is a mathematical concept that involves determining whether a set of vectors can be combined in a linear combination to equal the zero vector. If it is not possible, then the vectors are considered linearly independent.

Why is it important to prove linear independence of vector sums?

Proving linear independence of vector sums is important in many areas of mathematics and science, particularly in linear algebra and physics. It allows us to determine whether a set of vectors can be used as a basis for a vector space, and it also helps us to understand the relationships and dependencies between different variables in a system.

What is the process for proving linear independence of vector sums?

The process for proving linear independence of vector sums involves setting up and solving a system of equations based on the given vectors. If the only solution to the system is the trivial solution (all coefficients equal to zero), then the vectors are linearly independent. If there are other non-trivial solutions, then the vectors are linearly dependent.

What are some applications of proving linear independence of vector sums?

Proving linear independence of vector sums is used in many areas of mathematics, such as in finding eigenvalues and eigenvectors, solving systems of linear equations, and determining the rank and nullity of a matrix. It is also important in physics, where it is used to analyze the forces and motion of objects in space.

Can a set of vectors be both linearly independent and linearly dependent?

No, a set of vectors cannot be both linearly independent and linearly dependent. This is because if a set of vectors is linearly dependent, then it means that at least one of the vectors can be expressed as a linear combination of the others. In other words, there is a relationship or dependence between the vectors. On the other hand, if a set of vectors is linearly independent, then there is no such relationship or dependence between the vectors.

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