LU Factorization of Matrices: How to Prove Uniqueness and Compute L and U

In summary, most invertible matrices can be written as a product A=LU of a lower triangular matrix L and an upper triangular matrix U, where all diagonal entries of U are 1. To prove uniqueness, a proof by contradiction can be used. For computing L and U, a general process involves multiplying by a series of lower triangular matrices to "kill" entries under the diagonal of A. Finally, every invertible matrix can be written as a product LPU, where L and U are as described and P is a permutation matrix.
  • #1
Dunkle
56
0

Homework Statement


Most invertible matrices can be written as a product A=LU of a lower triangular matrix L and an upper triangular matrix U, where in addition all diagonal entries of U are 1.

a. Prove uniqueness, that is, prove that there is at most one way to write A as a product.
b. Explain how to compute L and U when the matrix A is given.
c. Show that every invertible matrix can be written as a product LPU, where L, U, are as above and P is a permutation matrix.


Homework Equations


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The Attempt at a Solution


b. The general process involves multiplying by a series of lower triangular matrices to "kill" entries under the diagonal of A. Eventually, A will be in upper triangular form. We will have

[tex]U = L_k...L_1A \Rightarrow A = LU[/tex] where [tex]L = L_1^{-1}...L_k^{-1}[/tex]

Notes: The product of lower triangular matrices is also triangular. Also, lower triangular matrices are invertible.

I'm stuck on parts a. and c.

Thanks in advance for any help!
 
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  • #2
For part a, a proof by contradiction should work.

Suppose that LU=L'U' where L, L' are lower triangular and U, U' are upper triangular. You need some way to prove that U=U' and L=L'
 
  • #3
That was the approach I was attempting to take, but I couldn't figure out to show this explicitly. I think the key here is that all the diagonal entries of U are 1. It sort of makes sense that the algorithm I used in part b will give a unique upper triangular matrix, and then one would simply scale all the rows using elementary matrices (these scaling matrices are also lower diagonal) until the diagonal entries are 1. But, since part a should not rely on part b, it seems like there must be a better way (especially one not as sloppy).
 

1. What is LU factorization of matrices?

LU factorization, also known as LU decomposition, is a method used to decompose a square matrix into a lower triangular matrix (L) and an upper triangular matrix (U). This factorization is often used to simplify systems of linear equations and to compute determinants and inverses of matrices.

2. Why is LU factorization useful?

LU factorization can simplify the solution of systems of linear equations, as it reduces the number of operations needed to solve the system. It is also useful for finding the determinant and inverse of a matrix, as these calculations can be done more efficiently on the lower and upper triangular matrices.

3. How is LU factorization performed?

LU factorization is typically done using Gaussian elimination, a method that involves row operations to transform the original matrix into its lower and upper triangular form. The process involves finding the elements of the lower and upper triangular matrices using a series of steps, such as eliminating variables and reducing the matrix to echelon form.

4. What are the benefits of using LU factorization over other methods?

LU factorization can be more efficient than other methods, such as Gaussian elimination, when solving systems of linear equations because it requires fewer operations. It also allows for easier computation of the determinant and inverse of a matrix, which can be useful in various applications.

5. Can LU factorization be used on any type of matrix?

LU factorization can only be performed on square matrices, meaning that the number of rows is equal to the number of columns. Additionally, the matrix must be non-singular, meaning it has a non-zero determinant, in order for the factorization to be possible.

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