Undergrad Consequences on a system of ODEs after performing operations

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The discussion revolves around the validity of using Gauss elimination followed by the exponential function on a matrix derived from a system of ordinary differential equations (ODEs). The original matrix, after Gauss elimination, simplifies to a form that leads to an identity matrix, raising concerns about potential loss of critical information. Participants highlight that numerical errors, particularly due to very small values being rounded to zero, can distort results, leading to misinterpretations of the system's behavior. The conversation emphasizes the importance of algorithmic stability and the implications of matrix operations on the integrity of ODE solutions. Ultimately, the need to address numerical inaccuracies is recognized as essential for accurate analysis.
SeM
Hi, I have derived a matrix from a system of ODE, and the matrix looked pretty bad at first. Then recently, I tried the Gauss elimination, followed by the exponential application on the matrix (e^[A]) and after another Gauss elimination, it turned "down" to the Identity matrix. This is awfully simple, and I may wonder if the system at hand is either completely redundant, or if the procedure of using Gauss elimination on a matrix for a system of ODEs, followed by e^A and then another Gauss elimination is a reasonable and valid approach to solve ODE systems, and does not "make critical information of the ODE vanish along the way"?

Thanks!
 
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Not clear what you are doing. What is in the first matrix ? What does Gauss elimination give you when you do that ? Can you give an example ?
 
BvU said:
Not clear what you are doing. What is in the first matrix ? What does Gauss elimination give you when you do that ? Can you give an example ?
The first matrix is:

A = \begin{bmatrix}
1.0545718E-68 & 1.1271866E-(61i) \\
1 & -1\\
\end{bmatrix}

the first operation in gauss elimination with rref[A] in matlab

that gives:

B = \begin{bmatrix}
1 & -1 \\
0 & 0\\
\end{bmatrix}

the exponential of B gives then:

C= \begin{bmatrix}
2.7183 & 0.3679 \\
1.0000 & 1.0000 \\
\end{bmatrix}

finally gauss elim of C with rref[C] gives the identity matrix

Does that make sense? I suspect MATLAB is rounding exponentially small values to 0, and this is not a correct result.Thanks
 
Due to the very small first row, the matrix has been interpreted as ##A=\begin{bmatrix}0&0\\1&-1\end{bmatrix}## by the program, which is a singular matrix. It results in ##\exp(A)=\begin{bmatrix}1&0\\1+e^{-1}&e^{-1}\end{bmatrix}##.

Now that you exchanged the rows of ##A## for whatever reason, you have ##B=\begin{bmatrix}1&-1\\0&0\end{bmatrix}## instead, which leads to ##\exp(B)=\begin{bmatrix}e&e^{-1}\\0&1\end{bmatrix}##, if I made no mistakes by exponentiation.

So what do you want to do or say? As it is a numerical error, which led to that result, almost zero instead of equal to zero, we have algorithmic stability as one topic, or the general case of a Lie Group and its tangent space: ##\mathfrak{g} \stackrel{\exp}{\longrightarrow} G## as another.
 
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Thanks, I prefer to rectify the numerical error! Cheers
 
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