Numerical Methods - Newton Raphson

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Discussion Overview

The discussion focuses on the Newton-Raphson method for finding roots of functions, including its application to single-variable functions and systems of non-linear equations. Participants explore its use in division and series expansions, as well as its practical implications in numerical methods.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant presents a two-page example illustrating the Newton-Raphson technique for solving roots of functions, including both single-variable and non-linear systems.
  • Another participant expresses appreciation for the formatting and examples, noting the interest in the application of the method to non-linear systems.
  • A participant emphasizes the importance of clarity and practical examples in understanding the method, suggesting that many others share this need.
  • A further contribution discusses using the Newton-Raphson method for division, specifically computing 1/y by solving the equation 1/x - y = 0, and presents the iterative formula derived from this approach.
  • This participant claims that the division algorithm does not involve any divisions and highlights its quadratic convergence, which purportedly doubles the number of significant digits at each step.
  • Additionally, the same participant explains how the algorithm can be adapted to compute the Taylor series of 1/f(x) if the Taylor series of f(x) is known, detailing the iterative process involved.
  • The discussion also touches on the potential for computing series expansions of logarithmic and exponential functions using similar techniques, suggesting a broad applicability of the method.

Areas of Agreement / Disagreement

No consensus is reached regarding the various applications and implications of the Newton-Raphson method, as participants present differing perspectives and approaches without resolving the discussion.

Contextual Notes

Participants do not clarify certain assumptions regarding the convergence properties of the method or the specific conditions under which the discussed algorithms apply. The limitations of the method in various contexts are not fully explored.

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The following 2 page example illustrates the use of the Newton-Raphson technique for solving for roots of functions. Examples included:

1. Function in a single variable
2. System of non-linear equations
 

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Nicely formatted... great examples too; interesting to finally find something on its use with non-linear systems. :)
Thanks!
 
Thanks for the nice comments. My objective is to make things clear, concise, and practical. I need to see examples to understand things, so I figured others do also.:cool:
 
Division using Newton-Raphson. :smile:

We want to compute 1/y for some number y. This amounts to solving the equation:

<br /> \frac{1}{x} - y = 0<br />

for x. If we do that using Newton-Raphson, we get:

<br /> x_{n+1} = 2x_{n} - x_{n}^{2}y<br />

This is indeed a true division algorithm as it doesn't contain any divisions. Also, due to quadratic convergence, you double the number of significant digits at each step. Long division will only yield one significant digit per step.

The above algorithm can also be used to compute the Taylor series of a function 1/f(x) if the Taylor series of f(x) is known. You just take P_{0}(x) to be the first term of the expansion, e.g. if f(0) is nonzero then P_{0}=1/f(0) and you iterate using the algorithm:

<br /> P_{n+1}(x) = 2P_{n}(x) - P_{n}(x)^{2}f(x)<br />

At each step the number of correct terms will double, so P_{n}(x) will contain the first 2^{n} terms of the series expansion of 1/f(x). Note that this means that the term P_{n}(x)^{2}f(x) has to be computed to order \mathcal{O}\left(x^{2^{n+1}-1}\right).

So, computing the first billion terms of 1/f(x) only requires 30 iterations :smile: But we can do much more than computing reciprocals. Computing the series expansion of \log(f(x)) is almost as easy as computing the reciprocal of f(x) as all you have to do is integrate f&#039;(x)/f(x) term by term. And using this algorithm for \log(f(x)) you can also compute \exp\left(f(x)\right) using Newton-Raphson to solve for that function that yields f(x) after taking the logarithm using Newton-Raphson and the algorithm for computing the logarithm of a series expansion.

Since a large class of functions can be expressed in terms of logarithms and exponentials, the series expansion of pretty much any awkward function can be computed this way.
 
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