MHB Explore the Multiple Grid Method: Get Accurate Solution Faster

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The multiple grid method is designed to solve linear systems of differential equations more efficiently by utilizing both coarse and fine grids, allowing for faster convergence and improved accuracy. It begins with a coarse grid approximation, gradually refining the solution by switching between grids to address both low and high frequency errors. The finite difference method is employed to formulate the problem as a linear system, while eigenvalues and eigenvectors derived from Fourier analysis help in understanding the solution's behavior. The Jacobi method is used iteratively to update approximations, and the process involves constructing new systems based on errors calculated on coarse grids. This multigrid approach ultimately enhances computational efficiency in solving complex differential equations.
  • #31
mathmari said:
Ahh. What have I done differently as at the V-cycle shema?

So, what I did has no specific shema?

We applied the 2-grid method (ZG or Zweigitterverfahren) that is specified on page 363.
The multigrid method (MV or Mehrgitter-V-cyclus) is specified on page 366. (Thinking)
 
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  • #32
I like Serena said:
We applied the 2-grid method (ZG or Zweigitterverfahren) that is specified on page 363.
The multigrid method (MV or Mehrgitter-V-cyclus) is specified on page 366. (Thinking)

Yes, but which is the difference with what I did? (Wondering)
 
  • #33
mathmari said:
Yes, but which is the difference with what I did? (Wondering)

The Mehrgitter-V-cyclus doesn't have a residue $r$ or an error $e$ does it?
Instead it just has an approximation $v_H$ that is refined through coarser and finer grids. (Thinking)
 
  • #34
I like Serena said:
The Mehrgitter-V-cyclus doesn't have a residue $r$ or an error $e$ does it?
Instead it just has an approximation $v_H$ that is refined through coarser and finer grids. (Thinking)

Do we not have the residue problem at the step 2 if we are not on the coarsest grid, i.e. if we don't have $H=2^jh$ and so we calculate $f_{2h}$ and $v_{2h}$? (Wondering)
 
  • #35
Could you explain to me the natrices $I_h^{2h}$ and $I_{2h}^h$ and especially the graphs Fig. 25 and Fig. 26? (Wondering)

Consider the Fig. 25: Do we consider three points on the fine grid and we take from there the average and the result is then one point on the coarse grid, i.e. the first box? (Wondering)
 
  • #36
mathmari said:
Do we not have the residue problem at the step 2 if we are not on the coarsest grid, i.e. if we don't have $H=2^jh$ and so we calculate $f_{2h}$ and $v_{2h}$? (Wondering)

Ah yes. I overlooked that. (Tmi)

Turns out that $v_{2h}$ is actually a residue instead of an actual approximation on the coarser grid.

mathmari said:
Could you explain to me the natrices $I_h^{2h}$ and $I_{2h}^h$ and especially the graphs Fig. 25 and Fig. 26? (Wondering)

Consider the Fig. 25: Do we consider three points on the fine grid and we take from there the average and the result is then one point on the coarse grid, i.e. the first box? (Wondering)

In figure 25 we want to keep only about half of the points, so that the calculations become easier.
But we don't just want to discard the information that is contained in the points.
So we pick which points we want to keep, and we take a weighted average at a ratio of 1:2:1 with the neighboring points that are discarded.
In the example of figure 25 we keep points 2 and 4 while discarding points 1, 3, and 5.
Since we don't just want to throw the information away, we replace points 2 and 4 by a weighted average that includes points 1, 3, and 5. (Thinking)

In figure 26 we go into the other direction: coarser to finer grid.
In the example we have only 2 points, but we need to get back to 5 points.
To find the missing points we interpolate linearly between the points we have.
Points 2 and 4 remain the same, point 1 is found as the average of 0 and point 2, and point 3 is found by taking the average of point 2 and 4. (Thinking)
 
  • #37
Thank you so much for your help! (Bow) (Sun)
 

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