Smoothness of Discrete Functions

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    Discrete Functions
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Discussion Overview

The discussion revolves around the concept of measuring the smoothness of discrete functions, particularly in relation to how small changes in input affect the output. Participants explore various examples and seek terminology or existing research on the topic.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant defines smoothness in discrete functions as the property where small changes in input lead to minimal jumps in output, providing examples such as the Closest String Problem and the Traveling Salesman Problem.
  • Another participant questions the specific domain of the function being discussed, suggesting that methods analogous to differentiable functions, such as the calculus of finite differences, could be relevant.
  • A third participant references a criterion from actuarial science regarding n-th order smoothness, indicating a specific mathematical condition related to life tables.
  • Another claim is made regarding the smoothness of a discrete function based on its growth rate, referencing a source that categorizes functions as smooth or not based on their behavior at specific inputs.

Areas of Agreement / Disagreement

Participants express various viewpoints on the definition and measurement of smoothness in discrete functions, with no consensus reached on a singular approach or terminology. Multiple competing ideas and examples are presented.

Contextual Notes

The discussion includes assumptions about the nature of the functions being analyzed, such as their domains and the mathematical frameworks applicable to them. There are also references to specific mathematical conditions that may not be universally applicable across all contexts of discrete functions.

The Number Juggler
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Hi Physics Forums

Is there a specific technique to measure how smooth a discrete function is?

By smooth I mean that if you change the input by a minimum amount then you know that the objective function result will not have a big jump.

For example The Closest String Problem is completely smooth function, since if you change the input string by only one letter, then the distance to the furthest string will change by at most one.

The Traveling Salesman Problem is also smooth, but not completely so. If you change only the order that you visit two cities then the total distance traveled could not change as much as if you altered more. However there could be larger and smaller jumps.

Moving around a grid of random numbers would be completely unsmooth.

I'm sure there must be another word for this phenomena and some research done already. But google is providing anything except "smoothing discrete functions" which is a completely different thing altogether!
 
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The Number Juggler said:
Hi Physics Forums

Is there a specific technique to measure how smooth a discrete function is?

By smooth I mean that if you change the input by a minimum amount then you know that the objective function result will not have a big jump.

It isn't clear what you have in mind for the domain of the function - one real variable ?, a vector of variables ?

If you want to look at methods that are analogous to those used for differentiable functions (e.g. first derivative being bounded or partial derivatives being bounded) investigate "the calculus of finite differences".
 
The only thing I can recall is a function is from actuarial science: Barnett n-th order smooth iff ##|{\Delta^n a_x}| \cdot 7^n < a_x##. But this is really for life tables.
 
A discrete function is smooth if f(2n) = Θ(n) (theta of n). If f(2n) = o(n), it is not smooth. Source: Algorithms by Neapolitan, Appendix B.2.
 

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