Exploring the Need for a Second Pivot in LU Factorization with Partial Pivoting

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In summary, the conversation discusses using LU factorization with partial pivoting to solve a set of equations. The individual made an attempt to solve the problem but their answer was different from the one in the book. They noticed an additional partial pivot after setting two elements equal to zero and wanted to know why. They also provided their L and U matrices and asked if they give the original matrix when multiplied together. They also requested for a step-by-step explanation.
  • #1
aaronfue
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Homework Statement



Use LU factorization with partial pivoting for the following set of equations:

3x1 - 2x2 + x3 = -10
2x1 + 6x2 - 4x3 = 44
-8x1 - 2x2 + 5x3 = -26

The Attempt at a Solution


I made an attempt to solve this problem, but my answer was wrong compared to the book. There was an additional partial pivot after setting elements 21 & 31 equal to zero. I just would like to know why?

The following is what I got for my L and U matrices:

U=
[ -8 -2 5 ]
[ 0 5.5 -3.25]
[ 0 0 1.25]

L=
[1 0 0]
[.25 1 0]
[.775 0.5 1]
 
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  • #2
Do your L and U matrices, when multiplied together, give the original matrix of coefficients? The first row of your U is identical to the third row of the coefficient matrix. Coincidence?
 
  • #3
aaronfue said:

Homework Statement



Use LU factorization with partial pivoting for the following set of equations:

3x1 - 2x2 + x3 = -10
2x1 + 6x2 - 4x3 = 44
-8x1 - 2x2 + 5x3 = -26


The Attempt at a Solution


I made an attempt to solve this problem, but my answer was wrong compared to the book. There was an additional partial pivot after setting elements 21 & 31 equal to zero. I just would like to know why?

The following is what I got for my L and U matrices:

U=
[ -8 -2 5 ]
[ 0 5.5 -3.25]
[ 0 0 1.25]

L=
[1 0 0]
[.25 1 0]
[.775 0.5 1]

Please show your work details, step-by-step. When I do it (with [-8,-2,5] in row 1 and [3,-2,1] in row 3) I get a different U from yours and do not need any more "partial" pivots; straight pivoting works perfectly well. Or, maybe, I have not understood your question---but I still get a different U.
 

Related to Exploring the Need for a Second Pivot in LU Factorization with Partial Pivoting

Question 1: What is a pivot and why is there a need for a second one?

A pivot is a point or axis around which something rotates or turns. In scientific experiments or studies, a pivot is often used as a reference point for measurements or observations. A second pivot may be necessary in order to obtain more accurate or precise data, or to account for multiple variables in an experiment.

Question 2: Can't the first pivot be used for all measurements? Why add a second pivot?

While the first pivot may be suitable for some measurements, it may not account for all variables or factors involved in the experiment. Adding a second pivot can help to provide a more comprehensive understanding of the data being collected.

Question 3: How do scientists determine where to place the second pivot?

The placement of the second pivot is based on the specific variables and factors being studied in the experiment. Scientists use their knowledge and understanding of the subject matter to determine the most appropriate placement for the second pivot.

Question 4: Is the use of a second pivot a common practice in scientific research?

Yes, the use of multiple pivots is a common practice in scientific research. It allows for a more thorough analysis of the data and helps to minimize potential errors or limitations in the experiment.

Question 5: Are there any alternatives to using a second pivot in an experiment?

Yes, there are alternative methods for obtaining accurate data, such as using multiple reference points or using advanced technology. However, in some cases, a second pivot may still be necessary to account for all variables and ensure the validity of the results.

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