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

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In summary, the conversation discusses the ability to calculate an approximation for a quantity U(x) using the numerical value u(x;η) for a small enough parameter η. The error between these values, ξ(x;η), can be controlled by choosing an appropriate tolerance level. However, it is not possible to derive an approximate estimate for the error in the partial derivative of u(x;η) with respect to x based on this information alone, as there is no information about the dependence of x in the equation and there could still be high slopes locally despite everything tending to zero.
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bruno67
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I have a quantity [itex]U(x)[/itex], x>0, which I cannot calculate exactly. Numerically, I can calculate an approximation [itex]u(x;\eta)[/itex], for [itex]\eta>0[/itex], which is very close to [itex]U(x)[/itex] if [itex]\eta[/itex] is small enough. I know that the error [itex]\xi(x;\eta)=u(x;\eta)-U(x)[/itex] satisfies an estimate
[tex]|\xi(x;\eta)|\le E(x;\eta)[/tex]
where [itex]\lim_{\eta\to 0}E(x;\eta)=0[/itex] for all x, and I can use this to choose my parameter [itex]\eta[/itex] 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 [itex]\partial_x u(x;\eta)[/itex], i.e. [itex]\partial_x \xi(x;\eta)[/itex]?
 
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  • #2
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.
 

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

What is the definition of "Approximating Error"?

Approximating error refers to the difference between the exact value and the estimated value of a quantity. In the context of $\partial_x u(x;\eta)$, it is the difference between the exact partial derivative and the approximate partial derivative calculated using a numerical method.

How is "Approximating Error" calculated?

The formula for calculating approximating error in $\partial_x u(x;\eta)$ depends on the specific numerical method used for approximation. Generally, it involves comparing the exact value of the partial derivative with the approximate value obtained from the numerical method.

Why is it important to consider "Approximating Error" in $\partial_x u(x;\eta)$?

When using numerical methods to approximate the partial derivative, the calculated value may not be exactly equal to the exact value. Hence, it is important to consider approximating error to assess the accuracy of the numerical method and to determine the reliability of the results obtained.

What factors can affect the "Approximating Error" in $\partial_x u(x;\eta)$?

The choice of numerical method, the step size used in the calculation, and the complexity of the function can all affect the approximating error in $\partial_x u(x;\eta)$. Additionally, round-off errors and truncation errors in the numerical calculations can also contribute to the overall approximating error.

How can "Approximating Error" in $\partial_x u(x;\eta)$ be reduced?

To reduce approximating error in $\partial_x u(x;\eta)$, one can use more accurate and precise numerical methods, decrease the step size, and simplify the function being differentiated. Additionally, using higher precision data types in the numerical calculations can also help reduce approximating error.

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