Understand Adam Moulton & Bashforth Methods for Numerical Analysis

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Discussion Overview

The discussion revolves around understanding the Adam Moulton and Adam Bashforth methods in numerical analysis, particularly in the context of solving differential equations. Participants explore graphical interpretations and the underlying concepts of these multi-step methods.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • Some participants express confusion about the graphical understanding of the Adam Moulton method compared to the Adam Bashforth method, which they describe as using an interpolating polynomial based on known solution points.
  • One participant suggests that both methods use previous points to create a polynomial curve for predicting the next point, contrasting this with the weighted approach of the Runge-Kutta methods.
  • A participant mentions the importance of the predictor-corrector algorithm, highlighting that the predictor extrapolates solutions but may be unstable, while the corrector adjusts the solution based on prior information.
  • Another participant proposes visualizing the methods by plotting the numerical results against known analytical solutions to better understand their behavior.
  • Concerns are raised about the output of plots, with one participant noting that their approximations appear as straight lines rather than the expected quadratic or cubic forms, indicating potential issues in their program structure.

Areas of Agreement / Disagreement

Participants generally agree on the basic concepts of the methods discussed but express differing views on their graphical interpretations and implementations. The discussion remains unresolved regarding the best way to visualize and understand these methods.

Contextual Notes

Some limitations are noted regarding the assumptions made in the implementation of the numerical methods and the graphical outputs, which may not fully represent the expected behavior of the algorithms.

steven187
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hello all

I have been researching into numerical analysis, differential equations in particular, I underdstand how the Runge kutta methods work geometrically but I don't quit understand what is the idea behind Adam moultons method And Adam Bashforth method, Is there a graphical way of understanding it? I find it very confusing?

steven
 
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hello all

so far after a bit more research I have come to understand that the adams bashforth requires information about the solution at more than one point, If I assume that we already know these points then what this method does is find an interpolating polynomial that passes through these points and then uses it to obtain the solution of the next point- this occurs when the resulting polynomial is extrapolated over the next interval h, this is pretty understandable graphically but I still don't understand what adams moultons method does graphically does anybody have any ideas

steven
 
Hello Steven,

My understanding of these multi-step methods is that they're similar in that they use previous points to calculate a polynomial curve as a trajectory to the next point as opposed to a "weighted" straight line for Runge-Kutta. However, the Milne's method and Adam-Moulton methods correct the predicted value of the next y before going on to the next step.

I think a nice way of gleaming a geometrical notion of these methods is to work with ODEs that I know what the analytical solution is and then go through the numerical methods and actually plot (in Mathematica of course) the quadratic and cubic curves that are these methods, as well as the "predictors" and "correctors", and see how they follow the actual path.

Why not just work through a few points for y'=Ay. Maybe post some plots too. :smile:
 
Hello Saltydog

well that aint a bad idea, there is always one way of finding out how something works and that is if we demonstrated it graphically, I have been writting a program over the last few days, writting the predictor corrector code wasnt difficult but trying to plot each step all on the same graph is a bit complicated, I have given it some thought but i think the way i have structured my program does not accommodate for my expected outcome which is to see the convergence for each point after running the predictor corector many times consecutively for the same point until it satisfies the stopping criteria, anyway this is my current output which is based upon increasing the subintervals

steven
 

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hello all

to answer my original question, a predictor-corrector algorithm, consists of basically two parts, the predictor extrapolates the solution over some finite range h based on the information at prior points and is inherently unstable and the corrector which allows for this local instability and makes a correction to the solution at the end of the interval which is also based on prior information as well as the extrapolated solution.

steven
 
steven187 said:
Hello Saltydog

well that aint a bad idea, there is always one way of finding out how something works and that is if we demonstrated it graphically, I have been writting a program over the last few days, writting the predictor corrector code wasnt difficult but trying to plot each step all on the same graph is a bit complicated, I have given it some thought but i think the way i have structured my program does not accommodate for my expected outcome which is to see the convergence for each point after running the predictor corector many times consecutively for the same point until it satisfies the stopping criteria, anyway this is my current output which is based upon increasing the subintervals

steven

Hello Steven,

My first though is why didn't you just save the plots in Mathematica as bitmaps and/or convert them to JPEG as I do and then just post the plots directly here without going through Microsoft Office?

Also, the plots seems to have straight line approximations. I was expecting quadratic or cubic approximations for these numerical methods.
 
hello saltydog

well the reason why Iv got straight line approximations is because I have structured my program with the 2nd order runge kutta and the second order adam bashforth and second order adam moulton, upgrading the program shouldn't be too difficult anyway

steven
 

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