Hello everyone,I am currently tackling the issue to numerically solve an integral of higher dimensions numerically. I am comparing models
and their dimension increase with 2^n order.Taking a closer look to its projections along the axes, down to a two dimensions picture, the projections are of Gaussian nature, thus
they show a Gaussian bump.
I already used to approaches:1. brute force: Process the values at discrete grid points and calculate the area of the obtained rectangle, cube, ... with a grid of 5x5x5x5 for a 4th order equation. 2. Gaussian quad: Cascading Gaussian quadrature given from numpy/ scipy with a grid size of 100x100x...
The problem I have:For 1: How reliable are the results and does anyone have experience with equations whose projections are Gaussian like and solved these with the straight-forward-method? But how large should the grid be. For 2: How large do I need to choose the grid to still obtain reliable results? Is a grid of 10x10 sufficiently large?
Thanks in advance for any reply. If needed, I'll directly provide further informations about the problem.
Greetings, Mario
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