Error for perturbed solution vs Numeric

In summary, the conversation is about solving a PDE using a naive expansion and comparing the numerical solution to the analytic and asymptotic solutions. The error should be proportional to the small parameter epsilon squared, but even for relatively small values of epsilon, the error is not decreasing as expected. It is suggested to try using a smaller value of epsilon to see if the results improve and to consider the possibility that the approximate solution may not be accurate enough.
  • #1
member 428835
Hi PF!

I'm solving an PDE where the analytic solution is called ##F(x)## (unknown). To approximate the analytic solution I made a naive expansion in some small parameter ##\epsilon## such that ##F(x) = f_0(x)+\epsilon f_1(x)+O(\epsilon^2)##, where I know ##f_0(x)## and ##f_1(x)##. I then solved the PDE numerically, let's call that solution ##F_n##. Then the error ##(F_n - (f_0(x)+\epsilon f_1(x)))/F_n## should be ##O(\epsilon^2)##. However, when I let ##\epsilon=.9## and then ##\epsilon=.8## my error is still about ##0.15##. How can this be?

I should say I know the numeric and asymptotic solutions are correct.
 
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  • #2
joshmccraney said:
Hi PF!

I'm solving an PDE where the analytic solution is called ##F(x)## (unknown). To approximate the analytic solution I made a naive expansion in some small parameter ##\epsilon## such that ##F(x) = f_0(x)+\epsilon f_1(x)+O(\epsilon^2)##, where I know ##f_0(x)## and ##f_1(x)##. I then solved the PDE numerically, let's call that solution ##F_n##. Then the error ##(F_n - (f_0(x)+\epsilon f_1(x)))/F_n## should be ##O(\epsilon^2)##. However, when I let ##\epsilon=.9## and then ##\epsilon=.8## my error is still about ##0.15##. How can this be?

I should say I know the numeric and asymptotic solutions are correct.
##\epsilon=.9## isn't really all that small. Do you get better results for, say, ##\epsilon=.1##?
 
  • #3
Mark44 said:
##\epsilon=.9## isn't really all that small. Do you get better results for, say, ##\epsilon=.1##?
So for ##\epsilon=0.01## I'm getting an error of 0.165 but for ##\epsilon=0.2## the error is 0.14. How could this ever be possible?
 
  • #4
Maybe your approximate solution isn't that close to the actual solution...
 

1. What is the difference between error for perturbed solution and numeric?

The error for perturbed solution refers to the difference between the exact solution and the approximate solution obtained by perturbing or changing the initial conditions of a problem. On the other hand, the numeric error is the difference between the exact solution and the approximate solution obtained through numerical methods.

2. How can error for perturbed solution and numeric error be calculated?

The error for perturbed solution can be calculated by subtracting the exact solution from the perturbed solution. Numeric error can be calculated by subtracting the exact solution from the approximate solution obtained through numerical methods.

3. Why is it important to calculate error for perturbed solution and numeric error?

Calculating error for perturbed solution and numeric error allows us to assess the accuracy of our approximations and the impact of perturbations on the solution. It also helps us to determine the reliability of our numerical methods and make improvements if needed.

4. How does the magnitude of the error for perturbed solution and numeric error affect the accuracy of the solution?

The larger the error for perturbed solution and numeric error, the less accurate the solution is. This means that the solution obtained is farther away from the exact solution and may not be reliable for making predictions or decisions.

5. Can error for perturbed solution and numeric error be reduced?

Yes, error for perturbed solution and numeric error can be reduced by using more accurate numerical methods, increasing the precision of calculations, and reducing the size of perturbations. However, it is important to note that some error is inevitable in numerical methods and perturbations can also be caused by external factors beyond our control.

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