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Super Sample Covariance with linear galaxy bias approximation #947

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merged 8 commits into from
Jun 28, 2022

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carlosggarcia
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@carlosggarcia carlosggarcia commented Jun 27, 2022

As a first implementation in TJPCov, in order to avoid the user to have to define several halo model parameters, it might be useful to have an approximation of the SSC. What I have implemented here is tkk_ssc ~ b1 * b2 * First_term_for_a_NFW_profile + (b1 * delta_1_nc + b2 * delta_2_nc) * Pmm_for_a_NFW_profile (see Eq. A13 in 1601.05779), where delta_1_nc = 1 if the first quantity is for number counts and 0 if not.

I have also fixed the docstring for the SSC trispectrum function.

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coveralls commented Jun 27, 2022

Pull Request Test Coverage Report for Build 2575225889

  • 62 of 64 (96.88%) changed or added relevant lines in 1 file are covered.
  • No unchanged relevant lines lost coverage.
  • Overall coverage decreased (-0.004%) to 97.102%

Changes Missing Coverage Covered Lines Changed/Added Lines %
pyccl/halos/halo_model.py 62 64 96.88%
Totals Coverage Status
Change from base Build 2542833097: -0.004%
Covered Lines: 4557
Relevant Lines: 4693

💛 - Coveralls

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@carlosggarcia
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@damonge back to you!

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Alright, looking good! Just a couple of final comments

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@damonge back to you!

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LGTM!

@damonge damonge merged commit d5408a7 into master Jun 28, 2022
@damonge damonge deleted the ssc_linear_bias branch June 28, 2022 18:21
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3 participants