J/A+A/584/A53 Code for trispectrum of halo model (Kuntz, 2015)
Cross-correlation of CFHTLenS catalogue and Planck CMB lensing using the halo
model description.
Kuntz A.
<Astron. Astrophys. 584, A53 (2015)>
=2015A&A...584A..53K 2015A&A...584A..53K (SIMBAD/NED BibCode)
ADC_Keywords: Models ; Gravitational lensing
Keywords: large-scale structure of the Universe - cosmology: observations -
cosmology: theory - gravitational lensing: weak
Abstract:
I cross-correlate the galaxy counts from the Canada-France Hawaii
Telescope Lensing Survey (CFHTLenS) galaxy catalogue and cosmic
microwave background (CMB) convergence from the Planck data releases 1
(2013) and 2 (2015).
I improve on an earlier study by computing an analytic covariance from
the halo model, implementing simulations to validate the theoretically
estimated error bars and the reconstruction method, fitting both a
galaxy bias and a cross-correlation amplitude using the joint cross
and galaxy auto-correlation, and performing a series of null tests.
Using a Bayesian analysis, I find a galaxy bias b=0.92±0.02 and
cross-correlation amplitude A=0.850.15-0.16 for the 2015 release,
whereas for the 2013 release, I find b=0.93±0.02 and A=10.5±0.15.
I thus confirm the difference between the two releases found earlier,
although both values of the amplitude now appear to be compatible with
the fiducial value A=1.
Description:
This code computes the trispectrum of the halo model following
equation (A.5) of the paper. Here are the instructions to run it.
- You will need a file named "powerspectrum.dat" containing the linear
power spectrum, given by e.g camb by Anthony Lewis
- You will need cython (I wrote this program in cython to ensure a
quick computation of the trispectrum)
- First run "Mzm.py" to compute the M matrix given in Equation (43)
of the paper
- Then run "kernelsc.pyx" to store the values of the lensing kernels
(equations (3) and (5)). You can then comment lines 64 to 77.
- Finally you can run "trispectrumhalocz_m.pyx" where I define the
function "trispectrum", to be used at your convenience.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
code.tar 1044 1470 All code files
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Description of file: The code.tar file contains:
kernels.py : Kernels functions (Python)
kernelsc.pxd : Kernels functions (pxd)
kernelsc.pyx : Kernels functions (Cython)
Mzm.py : M matrix
Params.py : Physical and numeric parameters
Trispectrumhalocz_m.pxd : Halo trispectrum (pxd)
Trispectrumhalocz_m.pyx : Halo trispectrum (Cython)
Trispectrum_PT.py : PT trispectrum (Python)
Trispectrum_PTc.pxd : PT trispectrum (pxd)
Trispectrum_PTc.pyx : PT trispectrum (Cython)
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Acknowledgements:
Adrien Kuntz, adrien.kuntz(at)ens.fr
(End) Adrien Kuntz [ENS, France], Patricia Vannier [CDS] 10-Nov-2015