Singular 3x3 Matrix: Solving & Understanding

In summary, the solution is taking the determinant to see if the matrix is singular. One of the three row operations you can do on determinants is replacing a row by the sum of itself and another row. The other two row operations are switching two rows, and replacing a row by a multiple of itself. The reason they replaced R1 by R1 + R3 was to get a zero entry in the first row, which makes finding the determinant easier.
  • #1
Seneka
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Homework Statement
The problem and the statement are attached. I found the solution as shown in the attached files but I don't understand why in the solutions they added R1 and R3 to get a row equivalent to R1. Problem is Q4.
Relevant Equations
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  • #2
In the solution, they are taking the determinant to see if the matrix is singular. One of the three row operations you can do on determinants is replacing a row by the sum of itself and another row. The other two row operations are switching two rows, and replacing a row by a multiple of itself.
The reason they replaced R1 by R1 + R3 was to get a zero entry in the first row, which makes finding the determinant easier.
 
  • #3
Mark44 said:
In the solution, they are taking the determinant to see if the matrix is singular. One of the three row operations you can do on determinants is replacing a row by the sum of itself and another row. The other two row operations are switching two rows, and replacing a row by a multiple of itself.
The reason they replaced R1 by R1 + R3 was to get a zero entry in the first row, which makes finding the determinant easier.

But won't that change the value of R1 which will be equal to 3 instead of 2.
 
  • #4
Seneka said:
But won't that change the value of R1 which will be equal to 3 instead of 2.

Yes. The two equations combined to give an equation which now says 0 = 3, with a right hand side of 3.

The right-hand side doesn't matter in deciding if the determinant is 0, but it does matter if determining whether the system has zero or infinitely many solutions. 0 = 3 is a contradiction, so this system is inconsistent, no solutions. If you got 0 = 0 would be true for all x, y, z.
 
  • #5
Thanks @RPinPA @Mark44

I was more confused as to why row switching worked. A nice explanation I found was by looking at what the determinant does. By looking at a simple two by two the determinant will give you an area of a parallelogram. When you add a row to another one that creates a parallelogram with the same area and therefore doesn't change the value of the determinant.
 

Related to Singular 3x3 Matrix: Solving & Understanding

1. What is a singular 3x3 matrix?

A singular 3x3 matrix is a square matrix with three rows and three columns, where the determinant (a mathematical value that can be calculated from the elements of the matrix) is equal to zero. This means that the matrix is not invertible and has no unique solution.

2. How do you solve a singular 3x3 matrix?

To solve a singular 3x3 matrix, you can use various methods such as Gaussian elimination, Cramer's rule, or the inverse matrix method. However, since a singular matrix has no unique solution, the result will either be an infinite number of solutions or no solution at all.

3. What does it mean to understand a singular 3x3 matrix?

Understanding a singular 3x3 matrix means being able to interpret its properties and characteristics, such as its determinant being equal to zero and its lack of invertibility. It also involves knowing how to solve and handle such matrices in mathematical operations.

4. Can a singular 3x3 matrix be used in real-life applications?

Yes, singular 3x3 matrices can be used in real-life applications, especially in fields such as physics and engineering. For example, they can be used to solve systems of linear equations or to represent transformations in 3D space.

5. How can I check if a matrix is singular or not?

To check if a matrix is singular, you can calculate its determinant. If the determinant is equal to zero, then the matrix is singular. You can also use other methods such as finding the rank of the matrix or checking if it has linearly dependent rows or columns.

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