10-Two solved problems for 3×3 matrix by Crout’s LU-option 1.

Last Updated on December 14, 2025 by Maged kamel

Two solved problems for a 3×3 matrix by Crout’s LU-option -1.

We have two solved problems for the 3×3 matrix by Crout’s LU decomposition. For which we will apply the same technique used to derive the elements of the lower matrix and the upper matrix. Option 1 is finding the lower matrix first.

The first solved problem for the 3×3 matrix by Crout’s LU-Option-1.

The first problem for the 3×3 matrix is Crout’s LU decomposition. It is required to find both the Lower and upper matrix decomposition LU by using Crout’s method through a given matrix A. The given matrix is 3×3.

We will apply the previous post technique to get the L1 and U1 matrix components by using the following steps.

Step-1 Convert matrix A to a lower matrix (Option 1).

First, we have the matrix A as (1 1 1, 4 3 -1, 3 5 3). We will estimate the determinant of this matrix A, which we set to +10. Since the determinant value is not equal to zero, then the matrix is invertible and we can proceed to find L and U matrices based on Crout’s method.

 The three elements in the first column vector of the A matrix which are 1 4 3 will be set as L11 &L21 and L31. L11=1, L21=4,L31=3. While for U12, we will divide a21/a11=1/1=1. While U13=a13/a11=1.

As for the upper matrix U1, the u11=1, U12=a21/a11=1/1=1 and u13=a13/a11=1/1=1. The detailed procedures are shown in the slide image.

The first solved problem of the two solved problems for 3x3 matrix by Crout's LU decomposition.

Step-2-Derive the values for the L22, L23, and U23-option-1.

We will use a11 as a pivot, we multiply (-1)*(a12/a11)*column 1 and add the result to the 2nd column, similarly, we multiply (-1)*(a13/a11)*column 1 and add the result to the 3rd column.  If we call the new matrix L1, the elements of the matrix are as follows:

The first row is (1, 0, 0). The second row is (4 -1 -5). The third row is (3  2   0). If we compare the first row of L1 to the following matrix, we have (L11 0 0), so L11 = 1. If we compare the second row of L1 to the following matrix, we have (L21 L22 L22*U23), so L21 = 4.

If we compare the third row of L1 to the next matrix, we have (L31 L32 L32*U23 + L33), so L31 = 3 and L32 = 2.

First solved problem -How to get the value of L22 for L1 matrix?

Step-3-Derive the value for the L33.

We want to proceed to get the final l matrix, we want to let  -5 equal zero. We multiply (-1)*(-5/-1)*column 2 and add the result to the 3rd column. The final elements of the Lower matrix l will be as follows:

The first row is (1   0   0). The second row is (4 -1 -5*-1 + (-5)). The third row is (  3  2  -5*2+(0)).

1st solved problem-How to get the value of L33?

Step 4- Check the product of(L*U)=A-matrix for a 3×3 matrix.

As the final verification step in our series, we multiply L and U to confirm that it reconstructs our original matrix A.” 

In the final slide, we have all the elements in the first column of the matrix identical to the first column of the lower matrix. The diagonals of the U matrix U11=U22=U33=1. L22=-1. U23=+5 while L33=-10. U12=1 and u13=1.

We can write both the lower and upper matrices and check whether multiplying the lower by the upper yields the final A matrix. Using row-by-column multiplication, we can see that L*U gives the matrix A.

How to derive the expression of L and U matrices?

The second solved problem-Crout’s LU-Option-1.

Convert matrix A to a lower matrix (Option 1)

First, we have matrix A as ( 10 3 4, 2 – 10 3, 3 2 -10 ). We will estimate the determinant of this matrix A, which is estimated to be +1163. Since the determinant value is not equal to zero, then the matrix is invertible, and we can proceed to find L and U matrices based on Crout’s method.

The second solved problem, the detailed procedure to estimate the determinant, is shown in the next slide image.

2nd solved problem-check whether matrix is invertible.

Step-1 Convert matrix A to a lower matrix.

The three elements in the first column vector of the A matrix which are 10 2 3 will be set as L11 &L21 and L31. L11=10, L21=2,L31=3. While for U12, we will divide a21/a11=3/10=3/10. While U13=a13/a11=4/10.

The second solved problem of the two solved problems for 3x3 matrix by Crout's LU decomposition.

Step 2: Derive the values for the L22, L23, and U23.

We will use a11 as a pivot, we multiply (-1)*(a12/a11)*column 1 and add the result to the 2nd column, similarly, we multiply (-1)*(a13/a11)*column 1 and add the result to the 3rd column.  If we call the new matrix L1, the elements of the matrix are as follows:

The first row is (10 3 4). The second row is (2 -10 3). The third row is (3  2   -10). If we compare the first row of L1 to the next matrix, we have (L11 0 0), so L11 = 1. If we compare the second row of L1 to the following matrix, we have (L21 L22 L22*U23), so L21 = 2.

If we compare the third row of L1 to the next matrix, we have (L31 L32  L32*U23+L33), then L31=3 and L32 =.1. To get U23 divide ((2.2)/(-10.6)=-11/53.

Second solved problem.Derive the values for L22 and L32.

Step-3-Derive the value for the L33-Crout’s LU decomposition.

We want to proceed to get the final l matrix, we want to let  2.2 to be equal zero. We multiply (-1)*(2.2/-10.60)*column 2 and add the result to the 3rd column. The final elements of the Lower matrix l will be as follows:

The first row is (10   0   0). The second row is (2 -10. 6 0 0). The third row is (3, 1.1, -1163/106). As we can see, L33 will be equal to -1163/106.

The 2nd solved problem -Find the value of L33.

Step-4-Check the product of(L*U)=A-matrix for a 3×3 matrix.

Using row-by-column multiplication, we can see that L*U gives the matrix A.

2nd solved problem check L*U product.

The complete detailed steps are shown in the previous slide images. At the end, we will check the product L*U against the Matrix A.

This is a link to the next post, which introduces the permutation matrix.

References

This is the Omni calculator for estimating various linear algebra items – LU Decomposition Calculator.

This is a link to another –Calculator for matrices.