cosmo_seed #700
cosmo_seed #700
Conversation
…y realization from the sampling realization
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Sorry I don’t quite remember how you can get a different displacement field
of a different seed from the density field of another seed.
I remember the solution (displacement) to the laplacian equation is
deterministic. Could you elaborate a bit more how this works?
…On Fri, Oct 24, 2025 at 12:17 PM Owen Chase ***@***.***> wrote:
I added a cosmo_seed parameter to give the option for separating the
density realization from the sampling realization. That gives the ability
to sample the same initial conditions repeatedly and getting different
discrete points. That way, one can build up a large catalog by adding up
smaller catalogs without generating the large one all at once.
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You can view, comment on, or merge this pull request online at:
#700
Commit Summary
- 35b915c
<35b915c>
added a cosmo_seed parameter to give option for separating the density
realization from the sampling realization
File Changes
(1 file <https://github.com/bccp/nbodykit/pull/700/files>)
- *M* nbodykit/source/catalog/lognormal.py
<https://github.com/bccp/nbodykit/pull/700/files#diff-36fd973f736c69e9a72faad08b462f322722965e6d69a86aa4f64adc7899eafd>
(16)
Patch Links:
- https://github.com/bccp/nbodykit/pull/700.patch
- https://github.com/bccp/nbodykit/pull/700.diff
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Is it just that you want to sample the HOD mocks separately from the initial density field? |
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What I am updating here is the code for generating log normal mock catalogs. How those work is by first using a random number to create a density field which follows some power spectrum. You need the random number because there are many possible random fields for a given power spectrum. Once you have a density field, you then look in each grid cell and do Poisson sampling to determine whether there is a source there. This is, of course, random. Therefore, there are 2 separate stages of randomness involved in making a mock catalog. First, one needs the initial conditions to determine the exact density field, and two, the density field needs to be randomly sampled to generate sources. The way the code currently works is to use the same seed for both of these random processes (making the density field and sampling it). Now suppose I make a mock catalog and realize it was too small. If I use a new seed for the density field (with the same power spectrum), the two mocks will be incompatible at the field level because the specific locations of the density peaks would be uncorrelated between them. Their power spectra would match, but if you combined them and computed a power spectrum you would not get the right answer. However, in the current implementation, the only way to use the same initial conditions (same density field) again for a new mock is to also use the same Poisson sampling. In other words, there is only 1 random sample of sources possible from each random density field. So, if I ever want to increase the size of my mock, I have to recreate all the sources I already have. This is an issue not only due to wasted compute, it limits the size of mocks I can possibly make to the density I can fit in the RAM. If I want anything bigger (more dense), I simply cannot do it because I will always get the same source catalog from a given set of initial conditions. What my update does is separate the seeds for these two random processes to allow for each set of initial conditions to result in myriad possible source instantiations. If only the standard 'seed' is provided or no seed is provided at all, the behavior is identical to before and should preserve the functionality of all legacy code (I think). There is simply a new argument which allows me to fix the initial conditions (using the random seed for the density field) while leaving the sampling seed free to vary. Or, at least, that is its intention. |
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Thanks, it makes sense. Can you confirm what tests you did to make sure it works? Also can you please add a comment to the documentation surrounding seed and cosmo_seed summarizing your last reply and explaining why one may want to use different values for the two seeds? Once those are done, I am happy to merge, the changes are modest. Thanks! |
3 participants
I added a cosmo_seed parameter to give the option for separating the density realization from the sampling realization. That gives the ability to sample the same initial conditions repeatedly and getting different discrete points. That way, one can build up a large catalog by adding up smaller catalogs without generating the large one all at once.