Which are the pivot columns? - Linear Algebra

In summary, the given system of equations can be solved using elimination on the augmented matrix, resulting in three pivots: 1, -3, and -6. However, if the last row of the matrix is changed to -3 3 -4 -3 -9, there will only be two pivots: 1 and -3. The pivot columns are col1 and col2, while the rest are free columns.
  • #1
tigrus
2
0

Homework Statement


Given matrix

A=

1 1 -2 1 3
2 -1 2 2 6
3 2 -4 -3 -9

x=

x1
x2
x3
x4
x5

b =

1
2
3

1. Solve the system by elimination (use the augmented matrix) until pivots are found (no backward elimination here).

2. Show that pivots are respectively 1 and -3, and indicate clearly which are the pivot columns and free columns.


Homework Equations



Matrix A and vector b



The Attempt at a Solution



I perform elimination on augmented matrix to solve part 1.

1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 -1 2 -6 -18 | 0


1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 0 0 -6 -18 | 0

What I don't understand is part 2.

As far as I know, for an entry to become a pivot it must be the first non-zero entry on the row and there must be no non-zero entries under it.

1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 0 0 -6 -18 | 0

If that rule applies I would find three pivots instead of two. (1,-3, -6) I know the right answer for this exercise is that there are only two pivots (1, -3), resulting col1 & col2 to be the pivot columns and the rest are free columns.

Can someone explain why -6 is not a pivot in this case?
 
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  • #2
tigrus said:

Homework Statement


Given matrix

A=

1 1 -2 1 3
2 -1 2 2 6
3 2 -4 -3 -9

x=

x1
x2
x3
x4
x5

b =

1
2
3

1. Solve the system by elimination (use the augmented matrix) until pivots are found (no backward elimination here).

2. Show that pivots are respectively 1 and -3, and indicate clearly which are the pivot columns and free columns.


Homework Equations



Matrix A and vector b



The Attempt at a Solution



I perform elimination on augmented matrix to solve part 1.

1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 -1 2 -6 -18 | 0


1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 0 0 -6 -18 | 0

What I don't understand is part 2.

As far as I know, for an entry to become a pivot it must be the first non-zero entry on the row and there must be no non-zero entries under it.

1 1 -2 1 3 | 1
0 -3 6 0 0 | 0
0 0 0 -6 -18 | 0

If that rule applies I would find three pivots instead of two. (1,-3, -6) I know the right answer for this exercise is that there are only two pivots (1, -3), resulting col1 & col2 to be the pivot columns and the rest are free columns.

Can someone explain why -6 is not a pivot in this case?
I don't see an error on your part. Are you sure you have copied the matrix correctly?
 
  • #3
as far as I could tell, there should be 3 pivots in your reduced matrix.

I suspect that you wrote the matrix down wrong, because if you make the last row
-3 3 -4 -3 -9 instead of 3 3 -4 -3 -9, then there should be only two pivots.
 

1. What are pivot columns?

Pivot columns are columns in a matrix that contain a leading entry, which is the first non-zero element in that column. They are important in linear algebra as they help determine the rank of a matrix and are used in various matrix operations.

2. How do you identify pivot columns?

To identify pivot columns in a matrix, you need to use the process of row reduction, also known as Gaussian elimination. Start by converting the matrix into row-echelon form, and any columns with a leading entry are pivot columns.

3. Why are pivot columns important?

Pivot columns are important in linear algebra because they help determine the rank of a matrix, which is the maximum number of linearly independent rows or columns. They are also used in solving systems of linear equations and performing various matrix operations.

4. Can a matrix have more than one pivot column?

Yes, a matrix can have more than one pivot column. The number of pivot columns can range from 0 (for a zero matrix) to the minimum of the number of rows or columns in the matrix. A matrix with n pivot columns has a rank of n, and n is also the number of linearly independent rows or columns in the matrix.

5. How do pivot columns affect the inverse of a matrix?

Pivot columns play a significant role in determining whether a matrix is invertible or not. If a matrix has a pivot in every column, it is said to be a full rank matrix and is invertible. On the other hand, if a matrix does not have a pivot in every column, it is not invertible. Inverse matrices are only defined for square matrices, and the number of pivot columns in a square matrix also determines its rank.

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