Confirm the row vectors of A are orthogonal to the solution vectors?

In summary, the conversation is about finding a general solution to a given system of equations and confirming that the row vectors of the corresponding matrix are orthogonal to the solution vectors. The solution involves finding the dimension of the solution space and showing that the row vectors of the matrix are perpendicular to the solution vectors. The conversation ends with a request for guidance on how to approach the last part of the question.
  • #1
lacrotix
9
0
HI there. I'm taking Linear Algebra classes right now and this question has been bugging me.

Homework Statement



Find a general solution to the system, state the dimension of the solution space, and confirm the row vectors of A are orthogonal to the solution vectors.

The given system is:
(x1) + (x2) + (x3) = 0
2(x1) + 2(x2) + 2(x3) = 0
3(x1) + 3(x2) + 3(x3) = 0

The Attempt at a Solution



This last part about confirming vectors are orthogonal (bolded) confuses me. I have found the general solution can be written as

(x1) = t + s
(x2) = t
(x3) = s

And that the dimension of the solution is 2, since there are two vectors. But I do not understand how to do the last part of the question. What is it asking? Any guidance would be appreciated.
 
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  • #2
Your "solution" doesn't work in the first equation (nor the others).
 
  • #3
The system can be written as a matrix multiplication Ax=0. A row vector is simply a row of the matrix A. You want to show that each of these row vectors is perpendicular to the solution x. As LCKurtz noted, you need to get that right first.
 

Related to Confirm the row vectors of A are orthogonal to the solution vectors?

1. What does it mean for row vectors to be orthogonal to solution vectors?

Orthogonality means that two vectors are perpendicular, or at a 90 degree angle, to each other. In this context, it means that the row vectors of matrix A are perpendicular to the solution vectors of a system of equations.

2. How can I confirm if the row vectors of A are orthogonal to the solution vectors?

To confirm orthogonality, you can use the dot product between the row vectors of A and the solution vectors. If the dot product is equal to 0, then the vectors are orthogonal.

3. Why is it important to confirm orthogonality between row vectors and solution vectors?

Confirming orthogonality ensures that there is no overlap or dependency between the row vectors and the solution vectors. This means that the solution to the system of equations is unique and can be easily solved.

4. Can row vectors and solution vectors ever be non-orthogonal?

Yes, it is possible for row vectors and solution vectors to be non-orthogonal. In this case, the system of equations would have multiple solutions or no solutions at all.

5. Are there any real-life applications of confirming orthogonality between row vectors and solution vectors?

Yes, this concept is used in many fields such as engineering, physics, and computer science. For example, in computer graphics, orthogonality between rows of a transformation matrix and the solution vectors ensures that the transformed image is not distorted.

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