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mocks from galaxy power spectrum for a non-gaussian field #662

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in response to issue #660

the type of transfer function used
"""

def __init__(self, cosmo, redshift ,b0 ,fNL ,p ,Omega_m ,H0=73.8 ,c=3e5 ,transfer='CLASS'):
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Why not using cosmo.h and cosmo.Omega_m?

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Oh I completely missed that. That would be so much better. Thanks. Any other recommendations?

from ..cosmology import Cosmology
from .linear import LinearPower

class GalaxyPower(object):
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Perhaps rename this to FNLGalaxyPower?

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Is there a paper that we can reference for the formula used here? Perhaps we can name the class after that paper?

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Hi, here is a paper that has all the formulas and explanations.

https://arxiv.org/pdf/2106.13725.pdf

b0 : float
the linear bias of the galaxy in a gaussian field
fnl : float
the non-gaussian parameter
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"Primordial non-gaussian parameter"?

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Thanks. I have made all those changes and updated the repo. I will add the unit test part soon. Thanks again.

the linear bias of the galaxy in a gaussian field
fnl : float
the non-gaussian parameter
p : float
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Does this parameter have a more descriptive name from the literature? It is like a bias correction parameter (removed from b)? larger p -> lower clustering?

What is a recently merged halo? A halo that recently experienced a merger event from progenitors of similar masses?

self.redshift = redshift


def corrected_bias(self, k):
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Does the literature call this a "corrected bias"? The return value is called a 'total_bias'. This is a bit confusing...

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Both are right but yes, it was confusing to use 2 different terms so I only used "total bias". Some works also refer to it as the "non-gaussian bias" or "fnl-bias". I am not sure which one would be ideal to use here. Let me know your thoughts on this. Thanks.

@@ -1,4 +1,5 @@
from .galaxy import GalaxyPower
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Let's also add a unit test or two that exercises this file,, e.g., in this file: https://github.com/bccp/nbodykit/blob/a387cf429d8cb4a07bb19e3b4325ffdf279a131e/nbodykit/cosmology/tests/test_power.py

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Hi. I have made all the changes and added the unit test functions. Please take a look and let me know.

@Jayashree-Behera
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Hi, Did you get a chance to take a look into the pull request?
Thanks.

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2 participants