Symmetrical Matrices and Invertibility: Is A Always Invertible If Ax ≠ Ay?

In summary, the conversation discusses the invertibility of a symmetrical matrix A based on the condition that for every two different vectors x and y, A*x ≠ A*y. The participants debate whether the proposition is still valid if A is singular, with one claiming that it is not and the other arguing that it is. The conversation also touches on the idea that the invertibility of A guarantees a unique solution to the system Ax=b, and the counterexample of x ≠ 0 and y = 0 is used to show that the proposition is false.
  • #1
peripatein
880
0
Hello,

Would it be correct to say that if for every two different vectors x and y, A*x ≠ A*y (where A is a symmetrical matrix), then A is NOT necessarily invertible? In other words, albeit for any two different vectors x and y symmetrical matrix A times one of the vectors is not equal to A times the other, A is not necessarily invertible?
 
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  • #2
Correction, in case A is a square matrix (of order nXn)
 
  • #3
If A is an n x n - matrix such that Ax ≠ Ay for all pairs of distinct n-vectors x and y, then A is invertible.
 
  • #4
Let us examine the following singular matrix:
2 0 4
1 -1 3
0 -1 1

For any two different vectors I claim that that matrix multiplied by the first vector will never be equal to the multiplication of that same matrix by the second vector.
Hence, the matrix does not necessarily have to be singular for the proposition to be valid and hold.
Wouldn't you agree?
 
  • #5
peripatein said:
Let us examine the following singular matrix:
2 0 4
1 -1 3
0 -1 1

For any two different vectors I claim that that matrix multiplied by the first vector will never be equal to the multiplication of that same matrix by the second vector.
Hence, the matrix does not necessarily have to be singular for the proposition to be valid and hold.
Wouldn't you agree?
Certainly not. As you said, the matrix is singular. This means that there is a nonzero vector x such that Ax=0 (such an x can easily be found if we solve the system Ax=0). On the other hand, A0=0, so Ax=A0, despite that x≠0.
 
  • #6
Okay, so the proposition does not hold in case A is singular, but does that per se guarantee that it holds, for EVERY two different vectors, if A were not singular, i.e. invertible?
 
  • #7
peripatein said:
Okay, so the proposition does not hold in case A is singular, but does that per se guarantee that it holds, for EVERY two different vectors, if A were not singular, i.e. invertible?
Yes, for if A is invertible and Ax=Ay, then x=Ix=(A-1A)x=A-1(Ax)=A-1(Ay)=(A-1A)y=Iy=y, that is, x=y.

The system Ax=b has a unique solution, x=A-1b, if x is invertible. Otherwise, it has either no solution or infinitely many solutions.
 
  • #8
Thank you very much! :-)
 
  • #9
The easy way to see this is false is consider the special case of x ≠ 0 and y = 0.

Ay = 0, so for every x ≠ 0, Ax ≠ 0.

If A is singular, there is a vector x ≠ 0 such that Ax = 0, which is a contradiction. Therefore A is non-singular.
 

1. What is an inverse matrix?

An inverse matrix is a matrix that, when multiplied by the original matrix, results in the identity matrix. The inverse matrix is denoted as A-1 and is used to solve equations involving matrices.

2. How do you find the inverse of a matrix?

The most common method of finding the inverse of a matrix is by using the Gauss-Jordan elimination method. This involves creating an augmented matrix with the original matrix on the left and the identity matrix on the right. Through a series of row operations, the identity matrix will eventually appear on the left, and the inverse matrix will be on the right.

3. Can all matrices have an inverse?

No, not all matrices have an inverse. A square matrix can only have an inverse if its determinant is non-zero. If the determinant is zero, the matrix is considered singular, and it does not have an inverse.

4. How does finding the inverse of a matrix help solve equations?

Finding the inverse of a matrix allows us to solve equations involving matrices. For example, if we have the equation Ax = b, we can multiply both sides by A-1 to get x = A-1b. This is particularly useful in systems of linear equations, where we can represent the equations in matrix form and use the inverse to solve for the variables.

5. Are there any real-life applications of inverse matrices?

Yes, inverse matrices have various real-life applications. They are used in computer graphics, engineering, economics, and many other fields. In computer graphics, inverse matrices are used to transform objects in 3D space. In engineering, they are used to solve systems of equations representing physical systems. In economics, they are used to analyze supply and demand equations.

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