LU decomposition: Total pivoting

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Discussion Overview

The discussion focuses on the LU decomposition of a specific matrix using total pivoting. Participants explore the definitions and roles of permutation matrices involved in the decomposition process, as well as the implications of these definitions on the relationship between the matrices L, U, and A.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant proposes the LU decomposition of the matrix A and describes the steps taken, including row and column exchanges based on the largest element.
  • Another participant questions the definition of the permutation matrix P0, suggesting it cannot be the identity matrix and proposes a new definition that accounts for the row and column swaps.
  • There is a discussion about whether the relationship LU = PA holds, with some participants suggesting it should be LU = PAQ to account for the column permutations.
  • Participants debate the correct formulation of the matrix L, with one suggesting it can be expressed in terms of the permutation and inverse matrices.
  • Clarifications are made regarding the properties of permutation matrices and their inverses, with some participants agreeing on the definitions while others express uncertainty.
  • One participant confirms the correctness of a derived expression for L after some back-and-forth discussion about the definitions of P and P0.

Areas of Agreement / Disagreement

Participants express differing views on the definitions and roles of the permutation matrices, particularly P0 and P1, and whether the relationship LU = PA or LU = PAQ is more appropriate. The discussion remains unresolved regarding the implications of these definitions on the LU decomposition.

Contextual Notes

There are unresolved assumptions regarding the definitions of the permutation matrices and their inverses, as well as the implications of these definitions on the overall structure of the LU decomposition.

mathmari
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Hey! :o

I want to determine the LU decomposition of
$A=\begin{pmatrix}0 & 2 & 1\\1 & 10 & 1 \\1 & 1 & 1\end{pmatrix}$ with total pivoting. I have done the following:

The biggest element of the whole matrix is $10$, so we exchange the first two rows and the first two columns and then we get $\begin{pmatrix}10 & 1 & 1 \\2 & 0 & 1\\1 & 1 & 1\end{pmatrix}$.
Applying now the Gauss algorithm we get $\begin{pmatrix}10 & 1 & 1 \\0 & -\frac{1}{5} & \frac{4}{5}\\0 & \frac{9}{10} & \frac{9}{10}\end{pmatrix}$.
The biggest element of the submatrix is $\frac{9}{10}$ and so we exchange the last two rows and get: $\begin{pmatrix}10 & 1 & 1 \\ 0 & \frac{9}{10} & \frac{9}{10} \\ 0 & -\frac{1}{5} & \frac{4}{5} \end{pmatrix}$. Now we apply the Gauss algorithm and get: $\begin{pmatrix}10 & 1 & 1 \\ 0 & \frac{9}{10} & \frac{9}{10} \\ 0 & 0 & 1 \end{pmatrix}$.

The matrix $U$ is the resulting matrix, $U=\begin{pmatrix}10 & 1 & 1 \\ 0 & \frac{9}{10} & \frac{9}{10} \\ 0 & 0 & 1 \end{pmatrix}$.

The matrix $L$ is $L=P\cdot P_0\cdot G_1^{-1}\cdot P_1\cdot G_2^{-1}$, or not? (Wondering)

The matrices $G_i^{-1}$ are defined as:
$$G_1^{-1}=\begin{pmatrix}1 & 0 & 0 \\\frac{2}{10} & 1 & 0\\\frac{1}{10} & 0 & 1\end{pmatrix} \ \text{ and } \ G_2^{-1}=\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & -\frac{2}{9} & 1\end{pmatrix}$$ or not? (Wondering)


Are the matrices $P_i$ defined as follows?
$$P_0=\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & 0 & 1\end{pmatrix}$$ since this describes the step at which we exchanged the first two rows and the first two columns. (Wondering)
$$P_1=\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}$$ since this describes the step at which we exchanged the two last rows. (Wondering) If these are correct, it doesn't hold that $LU=PA$, does it? (Wondering)
 
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mathmari said:
Are the matrices $P_i$ defined as follows?
$$P_0=\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & 0 & 1\end{pmatrix}$$ since this describes the step at which we exchanged the first two rows and the first two columns. (Wondering)
$$P_1=\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}$$ since this describes the step at which we exchanged the two last rows.

Hey mathmari!

It should be clear that
$$P_0=\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & 0 & 1\end{pmatrix}$$
cannot be correct. It is the identity matrix, isn't it? (Worried)

Let's define instead:
$$P_0=\begin{pmatrix}0 & 1 & 0 \\1 & 0 & 0\\0 & 0 & 1\end{pmatrix}$$
This is the matrix that swaps either 2 rows or 2 columns, isn't it?
And it's its own inverse. That is, $P_0^{-1}=P_0$.

Swapping 2 rows is a permutation on the left.
However, swapping 2 columns is a permutation on the right.
So after those 2 permutations we have $P_0 A P_0$. (Thinking)

mathmari said:
If these are correct, it doesn't hold that $LU=PA$, does it?

Shouldn't it be $LU=PAQ$, where $P$ reorders the rows of $A$ and $Q$ reorders the columns of $A$? (Wondering)

mathmari said:
The matrix $L$ is $L=P\cdot P_0\cdot G_1^{-1}\cdot P_1\cdot G_2^{-1}$, or not?

I don't think so. We have:
$$R = G_2 \cdot P_1 \cdot G_1 \cdot P_0 \cdot A \cdot P_0$$
From this we have to deduce $L$ such that:
$$LR = PAQ$$
Don't we? (Wondering)
 
We have $R=\begin{pmatrix}10 & 1 & 1 \\ 0 & \frac{9}{10} & \frac{9}{10} \\ 0 & 0 & 1 \end{pmatrix}$.

Since $R = G_2 \cdot P_1 \cdot G_1 \cdot P_0 \cdot A \cdot P_0$ we get that $$L\cdot G_2 \cdot P_1 \cdot G_1 \cdot P_0 \cdot A \cdot P_0=P\cdot A\cdot P_0 \Rightarrow L =P\cdot P_0^{-1}\cdot G_1^{-1}\cdot P_1^{-1}\cdot G_2^{-1} \Rightarrow L=P_1\cdot G_1^{-1}\cdot P_1\cdot G_2^{-1}$$

We have the matrices $$G_1^{-1}=\begin{pmatrix}1 & 0 & 0 \\\frac{2}{10} & 1 & 0\\\frac{1}{10} & 0 & 1\end{pmatrix} \ \text{ and } \ G_2^{-1}=\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & -\frac{2}{9} & 1\end{pmatrix}$$ We also have the matrices $$P_0=\begin{pmatrix}0 & 1 & 0 \\1 & 0 & 0\\0 & 0 & 1\end{pmatrix} \ \text{ and } \ P_1=\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}$$

So we get $$L=\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\\frac{2}{10} & 1 & 0\\\frac{1}{10} & 0 & 1\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & -\frac{2}{9} & 1\end{pmatrix}=\begin{pmatrix}1 & 0 & 0 \\ \frac{1}{10} & 1 & 0 \\ \frac{1}{5} & -\frac{2}{9} & 1\end{pmatrix}$$

Is this correct? (Wondering)
 
mathmari said:
Since $R = G_2 \cdot P_1 \cdot G_1 \cdot P_0 \cdot A \cdot P_0$ we get that $$L\cdot G_2 \cdot P_1 \cdot G_1 \cdot P_0 \cdot A \cdot P_0=P\cdot A\cdot P_0 \Rightarrow L =P\cdot P_0^{-1}\cdot G_1^{-1}\cdot P_1^{-1}\cdot G_2^{-1} \Rightarrow L=P_1\cdot G_1^{-1}\cdot P_1\cdot G_2^{-1}$$

How did you get $P\cdot P_0^{-1}=P_1$ ?
I think that the $P$ we will get, will be incorrect. (Worried)

mathmari said:
So we get $$L=\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\\frac{2}{10} & 1 & 0\\\frac{1}{10} & 0 & 1\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\0 & 0 & 1\\0 & 1 & 0\end{pmatrix}\begin{pmatrix}1 & 0 & 0 \\0 & 1 & 0\\0 & -\frac{2}{9} & 1\end{pmatrix}=\begin{pmatrix}1 & 0 & 0 \\ \frac{1}{10} & 1 & 0 \\ \frac{1}{5} & -\frac{2}{9} & 1\end{pmatrix}$$

Is this correct?

Yes. (Nod)
 
Klaas van Aarsen said:
How did you get $P\cdot P_0^{-1}=P_1$ ?
I think that the $P$ we will get, will be incorrect. (Worried)

Do we not have $P=P_1P_0 \Rightarrow PP_0^{-1}=P_1$ ? (Wondering)
 
mathmari said:
Do we not have $P=P_1P_0 \Rightarrow PP_0^{-1}=P_1$ ?

Ah yes, $P$ has to be whatever row permutation it takes to ensure that $L$ is a lower triangular matrix.

We have:
$$L =P\cdot P_0^{-1}\cdot G_1^{-1}\cdot P_1^{-1}\cdot G_2^{-1}$$
And $G_1^{-1}$ and $G_2^{-1}$ are lower triangular.
Since $P_1\cdot G_1^{-1}\cdot P_1^{-1}$ is a conjugation, it is lower triangular as well.
That is, we swap 2 rows and we also swap the corresponding 2 columns, so that the triangular form is retained. (Nerd)

So we can indeed pick $\smash{P\cdot P_0^{-1}=P_1}$.
I must have made a calculation mistake earlier. (Blush)
 

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