How could you use the implicit function theorem to prove something like this?

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SUMMARY

The discussion centers on applying the implicit function theorem to demonstrate that the function f(x,y,z) = g(x,y,z) + C h(x,y,z) has a minimum at a point (x_c,y_c,z_c) close to a known unique, non-degenerate minimum (x_0,y_0,z_0) of g. The participants confirm that a non-degenerate minimum implies a positive definite Hessian matrix. They emphasize the importance of diagonalizing the Hessian and relating the constant C to its eigenvalues to establish the necessary conditions for the proof.

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Suppose you know that a function [itex]g(x,y,z)[/itex] has a unique, non-degenerate minimum at some point [itex](x_0,y_0,z_0)[/itex]. How could you go about using the implicit function theorem to prove that [itex]f(x,y,z) = g(x,y,z) + C h(x,y,z)[/itex], where [itex]C[/itex] is some constant, has a minimum at some point [itex](x_c,y_c,z_c)[/itex]? Could we further show that [itex](x_c,y_c,z_c)[/itex] would need to be close to [itex](x_0,y_0,z_0)[/itex]?

I realize that I've left so many things unspecified that a lot of details will have to be omitted. But could you walk me through the basic program for proving something like this (e.g., things I'd have to show about the function [itex]h[/itex] or the constant [itex]C[/itex])?
 
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I suppose "non-degenerate" means the Hessian is positive definite? Then you need to diagonalize Hessian matrix and take C related to its eigenvalues.
 
g_edgar said:
I suppose "non-degenerate" means the Hessian is positive definite? Then you need to diagonalize Hessian matrix and take C related to its eigenvalues.
Hehe...yeah, that's the thing...I'm not really sure what a "non-degenerate" minimum is. Is that kind of an accepted definition for non-degenerate minimum?
 

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