When this is used to generate a random source via generate_volume_source, this means that additional normalisation of each element will be required, depending on what one would like to achieve, would you agree @marcuspetschlies ? We would like our random source \eta to satisfy:
which means that if we sample the real and imaginary components of the elements of \eta from a Gaussian distribution, we need to apply a normalisation factor:
\sigma_a^\alpha = N(0,1) + iN(0,1)
n = sqrt( (\sigma_a^\alpha)^\ast * \sigma_a^\alpha )
-> \eta_a^\alpha = \sigma_a^\alpha / n
When this is used to generate a random source via
generate_volume_source
, this means that additional normalisation of each element will be required, depending on what one would like to achieve, would you agree @marcuspetschlies ? We would like our random source\eta
to satisfy:which means that if we sample the real and imaginary components of the elements of
\eta
from a Gaussian distribution, we need to apply a normalisation factor:such that
would you agree?
For Z2 x Z2 noise there is no such problem, of course, up to the factor of 1/sqrt(2) which is correctly applied.