How can I accurately interpolate a C1 function with infinite second derivative?

In summary, the discussion suggests that for interpolating a function between a small number of points with known values and first derivatives, polynomial interpolation is usually recommended. However, if the function has an infinite second derivative at one end of the range, the interpolation function should be chosen accordingly to avoid systematic errors and reduce the order of accuracy. This may involve incorporating a general form of the function near the end point, such as using square roots or special functions like Bessel functions, rather than a polynomial.
  • #1
bruno67
32
0
I have to interpolate a function between a small number of points n (say, 3-5), at which I know both the value of the function and its first derivative. Normally, this would be a good candidate for polynomial interpolation.

The only problem is that at the first point the function is only once differentiable (its second derivative is infinite), while it is perfectly smooth in the rest of the interval. How can I get an estimate of the interpolation error? The usual estimate found in textbooks requires the function to have at least n+1 continuous derivatives in the closed interval in which one is interpolating.

Thanks.
 
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  • #2
If you know the second derivative is infinite at one end of the range, you should use that fact to choose the form of your interpotation function, otherwise you will be introducing systematic errors and reducing the order of accuracy.

Presumably you know the general form of the function near the end point, so you should include it in your interpolation, for eample

y = ax3/2 + b + cx + dx2 + ...

or
y = sqrt(x)(ax + bx2 + cx3 + ...)
or whatever.

The square roots are just an example of a function that gives an infinite second derivative. Use the function that fits the physics of your situation. That may be a "special function" like a Bessel function etc, not a polynomial.
 

1. What is interpolation for C1 function?

Interpolation for C1 function is a method used to estimate the values of a function at points between known data points. It involves fitting a smooth curve or line through the data points to approximate the behavior of the function.

2. What is the difference between interpolation and extrapolation?

Interpolation involves estimating values within the range of known data points, while extrapolation involves estimating values outside of the range of known data points. In other words, interpolation is used to fill in the gaps between data points, while extrapolation is used to predict values outside of the known data range.

3. How is the C1 continuity of a function related to interpolation?

C1 continuity refers to a function that is continuous and has a continuous first derivative. Interpolation for C1 function ensures that the fitted curve or line is also C1 continuous, meaning it has no sharp corners or discontinuities in its slope.

4. What are some common interpolation methods for C1 functions?

Some commonly used methods for interpolation of C1 functions include linear interpolation, polynomial interpolation, and spline interpolation. Each method has its own advantages and drawbacks, and the choice of method depends on the specific application and data set.

5. How accurate is interpolation for C1 functions?

The accuracy of interpolation for C1 functions depends on several factors, such as the quality and density of the data points, the chosen interpolation method, and the behavior of the underlying function. In general, the accuracy of interpolation improves as the number of data points increases, but it may still be subject to some error or uncertainty.

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