LU Factorization: Introduction with Real Impact Example

  • Context: MHB 
  • Thread starter Thread starter matqkks
  • Start date Start date
  • Tags Tags
    Factorization
Click For Summary
SUMMARY

LU factorization is a critical computational technique used to solve linear systems of equations represented as $\mathbf{Ax}=\mathbf{b}$. It is particularly efficient for multiple right-hand sides (RHS) since the matrices L and U remain constant across different RHSs. Applications include solving large circuit equations and performing Finite Element Analysis in engineering, such as modeling aircraft landing gear. The method also extends to second-order differential systems, where Choleski's factorization is applicable for symmetric positive definite matrices.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically matrix factorization.
  • Familiarity with solving linear systems of equations.
  • Knowledge of Finite Element Analysis (FEA) principles.
  • Basic understanding of differential equations and their applications.
NEXT STEPS
  • Study LU factorization algorithms and their implementations in numerical software.
  • Learn about sparse matrix techniques and their relevance in large-scale problems.
  • Explore Choleski's factorization and its applications in solving symmetric positive definite systems.
  • Investigate the Spectral Theorem and its implications in transforming linear systems.
USEFUL FOR

Mathematicians, engineers, and computer scientists involved in numerical analysis, particularly those working with linear systems, circuit simulations, and structural modeling in engineering applications.

matqkks
Messages
282
Reaction score
6
What is the most motivating way to introduce LU factorization of a matrix? I am looking for an example or explanation which has a real impact.
 
Physics news on Phys.org
Well, LU is one of the fastest ways computers use to solve linear systems of equations of the form $\mathbf{Ax}=\mathbf{b}$. It's especially useful if you have a lot of RHS's for which you want to find solutions, because once you find L and U, you're off to the races (they don't change for different RHS's).

One good application would be in solving a large circuit. You could easily get 10 or 20 linear equations to solve, and the computer can do that faster than a person, typically.

Solving linear systems is important in modeling parts, like a landing gear for an aircraft, for example. There you'd typically do a Finite Element Analysis, resulting in a large, sparse linear system to solve. For those size problems, you're not going to use an exact method like LU, but methods tailored to sparse matrices.
 
The $LU$ factorization is also useful to solve the second order differential system $Bx''=Ax$ with $A,B\in\mathbb{R}^{n\times n}$ symmetric and $B$ positive definite. The $LU$ factorization can be written ($B$ positive definite) as $B=LL^t$ (Choleski's factorization). We can find $C$ such that $A=LCL^t$ ($C=L^{-1}A(L^{-1})^t$).

Being $C$ symmetric, and using the Spectral Theorem we can write $C=PDP^t$ with $P$ orthogonal. The substitutions $y=L^tx$ and $z=P^ty$ transforms $Bx''=Ax$ into a diagonal system $z''=Dz$.
 
Last edited:

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 17 ·
Replies
17
Views
2K
  • · Replies 9 ·
Replies
9
Views
4K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 3 ·
Replies
3
Views
2K
Replies
1
Views
10K