Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

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

Open
wants to merge 10 commits into
base: master
Choose a base branch
from

Conversation

Jayashree-Behera
Copy link

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'):
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Why not using cosmo.h and cosmo.Omega_m?

Copy link
Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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):
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Perhaps rename this to FNLGalaxyPower?

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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

Copy link
Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

"Primordial non-gaussian parameter"?

Copy link
Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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):
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Does the literature call this a "corrected bias"? The return value is called a 'total_bias'. This is a bit confusing...

Copy link
Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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

@Jayashree-Behera
Copy link
Author

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

@Jayashree-Behera
Copy link
Author

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

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants