Approximating Error in $\partial_x u(x;\eta)$

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The discussion centers on approximating the error in the derivative of a numerical solution, specifically in the context of the quantity U(x) and its approximation u(x; η). The error term ξ(x; η) is defined as ξ(x; η) = u(x; η) - U(x), with an upper bound E(x; η) that approaches zero as η approaches zero. However, it is concluded that deriving an approximate estimate for the error in the derivative ∂_x u(x; η) is not feasible due to the lack of information on the dependence of x, despite the error tending to zero.

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I have a quantity U(x), x>0, which I cannot calculate exactly. Numerically, I can calculate an approximation u(x;\eta), for \eta>0, which is very close to U(x) if \eta is small enough. I know that the error \xi(x;\eta)=u(x;\eta)-U(x) satisfies an estimate
|\xi(x;\eta)|\le E(x;\eta)
where \lim_{\eta\to 0}E(x;\eta)=0 for all x, and I can use this to choose my parameter \eta so that the error lies under a specified tolerance.

Based only on the above, is it possible to derive an approximate estimate for the error in \partial_x u(x;\eta), i.e. \partial_x \xi(x;\eta)?
 
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No. As far as I can tell from the description, we have good information for any specific value of ##x## but none about the dependence of ##x##. And even if everything tends to zero, there could still be high slopes locally.
 

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