Polynomials and Numerical Analysis

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SUMMARY

Polynomials are integral to numerical analysis due to their straightforward structure and ease of manipulation, allowing for simple differentiation, integration, and approximation. Their properties enable effective numerical solutions to complex problems, making them a foundational element in the field. Polynomials are dense in function spaces, allowing for the approximation of a wide range of functions, which is particularly useful in solving differential equations through series methods like Frobenius. Additionally, phenomena such as the motion of a round drum head can be modeled using Bessel functions expressed as infinite sums of polynomials.

PREREQUISITES
  • Understanding of polynomial functions and their properties
  • Familiarity with numerical approximation methods
  • Knowledge of differential equations and series methods
  • Basic concepts of function spaces in mathematical analysis
NEXT STEPS
  • Explore polynomial interpolation techniques
  • Learn about numerical methods for solving differential equations
  • Study the Frobenius method for series solutions
  • Investigate the application of Bessel functions in physical modeling
USEFUL FOR

Mathematicians, engineers, and computer scientists involved in numerical analysis, particularly those focused on approximation methods and differential equations.

Suvadip
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Why polynomials are used in numerical analysis?
 
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Re: Numerical analysis

suvadip said:
Why polynomials are used in numerical analysis?

This is a very broad question.. I suppose because their structure is relatively straightforward and well-understood, and they are flexible yet easy to manipulate (it's trivial to differentiate/integrate/add/multiply polynomials, they are well-behaved with respect to numerical approximation methods, we know exactly when they cross the x-axis, we can easily find their minima and maxima, they work the same in the complex plane, and so on..) Can you be more specific?​
 
Re: Numerical analysis

suvadip said:
Why polynomials are used in numerical analysis?

Polynomial are based on the elentary operators of sum and multiplication, the most feasible for humans and computers... that's why N.A., the scope of which is to solve numerically problems, is pratically based on polynomials...

Kind regards

$\chi$ $\sigma$
 
Re: Numerical analysis

I think another reason why numerical analysis uses polynomials is that they are dense in some very large function spaces. That means (in case you weren't already aware of what it means) that you can approximate a very large number of functions with polynomials. This is quite useful in differential equations, with series methods like Frobenius. Indeed, the motion of, say, a round drum head when you hit it can be modeled using Bessel functions, which are written as an infinite sum of polynomials.
 

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