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

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SUMMARY

The discussion focuses on LU factorization of matrices, specifically proving the uniqueness of the factorization and computing the matrices L and U. The proof of uniqueness involves demonstrating that if two factorizations exist, the corresponding upper triangular matrices U and U' must be identical, leading to L and L' also being identical. The computation of L and U is achieved by applying a series of lower triangular matrices to transform the matrix A into upper triangular form, ensuring that all diagonal entries of U are 1. Additionally, it is established that every invertible matrix can be expressed as a product LPU, where P is a permutation matrix.

PREREQUISITES
  • Understanding of LU factorization in linear algebra
  • Familiarity with triangular matrices and their properties
  • Knowledge of elementary matrices and their role in matrix transformations
  • Proficiency in proof techniques, particularly proof by contradiction
NEXT STEPS
  • Study the properties of lower and upper triangular matrices in detail
  • Learn about the role of permutation matrices in LU factorization
  • Explore proof techniques in linear algebra, focusing on proof by contradiction
  • Investigate algorithms for computing LU factorization, such as Doolittle's method
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Students and educators in linear algebra, mathematicians interested in matrix theory, and anyone involved in numerical methods requiring matrix factorization techniques.

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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

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

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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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'
 
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).
 

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