Matrix Derivative: Solving for \partial_{x}[\det(\textbf{1}-\textbf{M})]

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SUMMARY

The discussion centers on the mathematical expression for the derivative of the determinant of a matrix, specifically \(\partial_{x}[\det(\textbf{1}-\textbf{M})]\), where \(\textbf{M}\) is a square matrix dependent on the variable \(x\). It is established that \(\partial_{x}[\det(\textbf{1}-\textbf{M})]\) cannot be simplified to \(\det(\textbf{1}-\partial_{x}\textbf{M})\). The participants seek a theorem or formula that accurately expresses this derivative in terms of \(\textbf{M}\) and its derivative with respect to \(x\).

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guerom00
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Hello :smile:

I scratch my head on trying to express [tex]\partial_{x}[\det(\textbf{1}-\textbf{M})][/tex] , where [tex]\textbf{M}[/tex] is a square matrix whose elements depend on x, as an expression involving [tex]\textbf{M}[/tex] and/or [tex]\partial_{x}\textbf{M}[/tex].
For instance, I have painfully noticed that it is not equal to [tex]\det(\textbf{1}-\partial_{x}\textbf{M})[/tex] :biggrin:

Any help would be much apprciated :smile: TIA
 
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Nevermind…
This is the theorem I'm looking for exactly :)
 

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