Can Singular Points Be Smoothly Transformed to Achieve Differentiability?

In summary, the conversation discusses the possibility of removing singular points in a mathematically correct way to achieve a smooth continuum that is differentiable everywhere. The use of topological transformations and Bezier curves is suggested as potential methods to achieve this, with the understanding that infinite differentiability may not be possible. The conversation also mentions a constructive method involving isosceles triangles and estimates of tangents.
  • #1
SW VandeCarr
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Is there a correct mathematical procedure to remove singular points so as to create a smooth continuum, differentiable everywhere? For example,for cusp singularities, is some kind of acceptable "cutting and joining" procedure available at the limit? I asked a similar question in the topology forum some time ago but never got an answer.

If we allow topological transformations, it seems to me that (for example) an inscribed equilateral triangle could be smoothly transformed to a circle without cutting and joining such that the points at the tips of the triangle become differentiable points on the circle.

http://mathworld.wolfram.com/SingularPoint.html

EDIT: I know "at the limit" can be problematical, but I'm trying to avoid arbitrary choices.
 
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  • #2
SW VandeCarr said:
Is there a correct mathematical procedure to remove singular points so as to create a smooth continuum, differentiable everywhere?

If all you need is (once-)differentiable* everywhere, you could choose some epsilon around every singularity and rejoin the pieces with Bézier curves. If you want infinite differentiability... nothing immediately comes to mind.

* Or indeed, if all you need is a fixed number of derivatives, just choose a sufficiently large degree.
 
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  • #3
CRGreathouse said:
If all you need is (once-)differentiable* everywhere, you could choose some epsilon around every singularity and rejoin the pieces with Bézier curves. If you want infinite differentiability... nothing immediately comes to mind.

* Or indeed, if all you need is a fixed number of derivatives, just choose a sufficiently large degree.

Thanks GR. Bezier curves seem to be what I was looking for. I was trying a constructive method by defining an isosceles triangle with two points on the limbs of the cusp and the third point at the singular point. I would then bisect the apical angle with a line through the singular point and then take the perpendicular to the bisector at the singular point and call that the first estimate of the tangent. I could refine the estimate by shortening the limbs of the triangle. If I understand Bezier's method correctly, this constructive method seems to follow the same line of reasoning.

I don't really need anything specific in terms of the number of derivatives. As you suggest, I should, in principle, get any finite number of derivatives just by refining the estimate.
 

Related to Can Singular Points Be Smoothly Transformed to Achieve Differentiability?

What is the purpose of removing singular points?

Removing singular points is crucial in data analysis and modeling as these points can distort the overall results and lead to incorrect conclusions. By removing them, we can get a more accurate representation of the data and make better predictions.

How do we identify singular points in a dataset?

Singular points can be identified by looking for data points that are significantly different from the rest of the data, either in terms of their values or their placement in the dataset. These points can also be identified through statistical methods such as outlier detection or data visualization techniques like scatter plots.

What techniques are commonly used for removing singular points?

Some common techniques for removing singular points include data smoothing, interpolation, and outlier removal. Data smoothing involves using mathematical functions to remove noise and irregularities in the data. Interpolation is used to fill in missing data points, while outlier removal involves eliminating data points that are significantly different from the rest of the data.

Are there any potential drawbacks of removing singular points?

Yes, there can be drawbacks to removing singular points. If these points are a result of errors or limitations in data collection, removing them can lead to biased results. Additionally, removing too many points can result in loss of important information and affect the accuracy of the analysis.

Is there a standard approach for removing singular points, or does it vary based on the dataset?

There is no one-size-fits-all approach for removing singular points as it depends on the nature of the dataset and the goals of the analysis. Different techniques may be more suitable for different types of data and it is important to carefully evaluate the impact of removing singular points on the overall results.

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