MHB LU Factorization: Introduction with Real Impact Example

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LU factorization is a crucial computational method for solving linear systems of equations, particularly in applications like circuit analysis and finite element modeling. It allows for efficient solutions when multiple right-hand sides (RHS) are involved, as the matrices L and U remain constant across different RHSs. In engineering contexts, such as aircraft landing gear modeling, LU factorization aids in handling large, sparse linear systems, although specialized methods are often used for very large problems. Additionally, LU factorization can be adapted for second-order differential systems, leveraging properties of symmetric and positive definite matrices. Overall, LU factorization is a powerful tool in numerical linear algebra with significant real-world applications.
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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.
 
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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 $z''=Dz$.
 
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I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

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