Checking the linear independence of elements of 2 X 2 matrices

In summary: Thank you for catching that.In summary, the conversation discussed a problem involving linear independence and finding coefficients for a linear combination. One way to find the coefficients is by solving a system of equations, while another way is to use the definition of linear independence. The problem was ultimately solved by solving a reduced problem and checking the resulting values.
  • #1
Pushoam
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Homework Statement


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Homework Equations


3. The Attempt at a Solution [/B]
## |3 \rangle = |1 \rangle - 2 ~ |2 \rangle ##
So, they are not linearly independent.

One way to find the coefficients is :
## |3 \rangle = a~ |1 \rangle +b~ |2 \rangle ## ...(1)
And solve (1) to get the values of a and b.

Is there any other easier way?
 

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  • #2
Pushoam said:
One way to find the coefficients is :
## |3 \rangle = a~ |1 \rangle +b~ |2 \rangle ## ...(1)
And solve (1) to get the values of a and b.

Is there any other easier way?
It doesn't get much easier than that. Since ##a## and ##b## are overdetermined, you can choose two elements from each matrix (the right column from each, for example) and solve the reduced problem

##\begin{bmatrix} 1 & 1\\0 & 1 \end{bmatrix} \begin{bmatrix} a\\b \end{bmatrix} = \begin{bmatrix} -1\\-2 \end{bmatrix}##

and then check the resulting ##a## and ##b## on the left columns.
 
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  • #3
Pushoam said:

Homework Statement


View attachment 229238

Homework Equations


3. The Attempt at a Solution [/B]
## |3 \rangle = |1 \rangle - 2 ~ |2 \rangle ##
So, they are not linearly independent.

One way to find the coefficients is :
## |3 \rangle = a~ |1 \rangle +b~ |2 \rangle ## ...(1)
And solve (1) to get the values of a and b.

Is there any other easier way?
I think you have done things the easiest way -- by inspection.

Another way is to use the definition of linear independence. The matrices A, B, and C (which you are calling |1>, |2>, and |3>) are linearly independent if there is only the nontrivial solution for the constants in the equation ##c_1A + c_2B + c_3C = 0##. By nontrivial, I mean solutions other than ##c_1 = c_2 = c_3 = 0##.
 
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  • #4
tnich said:
It doesn't get much easier than that. Since ##a## and ##b## are overdetermined, you can choose two elements from each matrix (the right column from each, for example) and solve the reduced problem

##\begin{bmatrix} 1 & 1\\0 & 1 \end{bmatrix} \begin{bmatrix} a\\b \end{bmatrix} = \begin{bmatrix} -1\\-2 \end{bmatrix}##and then check the resulting ##a## and ##b## on the left columns.
I did not understand what you meant by "##a## and ##b## are overdetermined". When to use this concept in general?
 
  • #5
Pushoam said:
I did not understand what you meant by "##a## and ##b## are overdetermined". When to use this concept in general?
An overdetermined problem is one in which you have more equations than variables. In this particular case you have four linear equations to solve for two variables.
##0a+b=-2\\a+b=-1\\0a+0b=0\\0a+b=-2##
or
##\begin{bmatrix}0 &1\\1&1\\0&0\\0&1\end{bmatrix} \begin{bmatrix}a\\b\end {bmatrix}= \begin{bmatrix}-2\\-1\\0\\-2\end{bmatrix}##

In general such a system of equations can have no solutions, one solution, or an infinite number of solutions. There are no solutions if and only if the vectors are independent. You can use Gauss-Seidel to determine this. Or you can try to find a set of linearly independent rows (easy in this case) in the leftmost matrix, remove the other rows (on both sides), and solve the reduced problem.
 
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  • #6
tnich said:
An overdetermined problem is one in which you have more equations than variables. In this particular case you have four linear equations to solve for two variables.
##0a+b=-2\\a+b=-1\\0a+0b=0\\0a+b=-2##
or
##\begin{bmatrix}0 &1\\1&1\\0&0\\0&1\end{bmatrix} \begin{bmatrix}a\\b\end {bmatrix}= \begin{bmatrix}-2\\-1\\0\\-2\end{bmatrix}##

In general such a system of equations can have no solutions, one solution, or an infinite number of solutions. There are no solutions if and only if the vectors are independent. You can use Gauss-Seidel to determine this. Or you can try to find a set of linearly independent rows (easy in this case) in the leftmost matrix, remove the other rows (on both sides), and solve the reduced problem.
It is pretty easy in this case. The first equation says that ##0 a + b = -2##, so ##b = -2.## The second equation says that ##a+b = - 1\: \Rightarrow a = -1 - b = -1 + 2 = 1.## Now check if these values of ##a## and ##b## satisfy the third and fourth equations.
 
  • #7
Mark44 said:
I think you have done things the easiest way -- by inspection.

Another way is to use the definition of linear independence. The matrices A, B, and C (which you are calling |1>, |2>, and |3>) are linearly independent if there are nontrivial solutions for the constants in the equation ##c_1A + c_2B + c_3C = 0##. By nontrivial, I mean solutions other than ##c_1 = c_2 = c_3 = 0##.
I think you probably wanted to write "linearly dependent " instead of "linearly independent".
 
  • #8
Pushoam said:
I think you probably wanted to write "linearly dependent " instead of "linearly independent".
Yes, I did. I'll fix my original post.
 

1. What is linear independence in 2 X 2 matrices?

Linear independence refers to the relationship between two or more elements of a matrix. In a 2 X 2 matrix, the elements are considered linearly independent if they cannot be expressed as a linear combination of each other. This means that no element can be created by multiplying or adding the other elements.

2. How can I check the linear independence of elements in a 2 X 2 matrix?

To check the linear independence of elements in a 2 X 2 matrix, you can use the determinant method. Calculate the determinant of the matrix and if it is equal to 0, then the elements are linearly dependent. If the determinant is not equal to 0, then the elements are linearly independent.

3. Can the linear independence of elements in a 2 X 2 matrix be visually determined?

Yes, the linear independence of elements in a 2 X 2 matrix can be visually determined by plotting the elements on a graph. If the elements lie on the same line or if one element is a multiple of the other, then they are linearly dependent. If the elements do not lie on the same line, then they are linearly independent.

4. What is the importance of checking the linear independence of elements in a 2 X 2 matrix?

Checking the linear independence of elements in a 2 X 2 matrix is important because it helps determine the dimension of the matrix and whether it is invertible. Linearly independent elements are necessary for the matrix to be invertible, which is important in many mathematical and scientific applications.

5. Can the linear independence of elements in a 2 X 2 matrix change?

No, the linear independence of elements in a 2 X 2 matrix cannot change. Once a set of elements is linearly independent, they will always be linearly independent. However, if one or more elements are added or removed from the matrix, the linear independence may change.

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