skewspec

Measure large-scale structure skew-spectra

The code reads an input catalog of objects or generates a synthetic density field, and computes skew-spectra corresponding to the contributions to the tree-level galaxy bispectrum in redshift space. For details see https://arxiv.org/abs/2010.14267 (joint work with Azadeh Moradinezhad Dizgah).

Running

• The basic usage is as follows.

  from nbodykit.source.mesh.field import FieldMesh
  from skewspec import smoothing
  from skewspec.skew_spectrum import SkewSpectrum
  
  # Given an nbodykit CatalogSource object `cat' (e.g. containing a halo
  # catalog), paint the overdensity delta on a 3D mesh using nbodykit.
  delta_mesh = FieldMesh(cat.to_mesh(Nmesh=Nmesh, BoxSize=BoxSize,
      window='cic', interlaced=False, compensated=False).compute()-1)
  
  # Make a copy of the density and apply Gaussian smoothing
  delta_mesh_smoothed = FieldMesh(delta_mesh.compute(mode='real'))
  delta_mesh_smoothed = smoothing.GaussianSmoother(R=20.0).apply_smoothing(
      delta_mesh_smoothed)
  
  # Compute skew spectra
  LOS = numpy.array([0,0,1])
  skew_spectra = SkewSpectrum.get_list_of_standard_skew_spectra(
      LOS=LOS, redshift_space_spectra=True)
  for skew_spec in skew_spectra:
      # Compute skew spectrum and store in skew_spec.Pskew
      skew_spec.compute_from_mesh(
        mesh=delta_mesh_smoothed,
        second_mesh=delta_mesh_smoothed,
        third_mesh=delta_mesh)

Running from the command line

• To run the code from the command line, see main_calc_spectra.py. General usage:

  $ python main_calc_spectra.py [-h] [--SimSeed SIMSEED] [--boxsize BOXSIZE]
                          [--ApplyRSD APPLYRSD] [--Rsmooth RSMOOTH]
                          [--Ngrid NGRID] [--SubsampleRatio SUBSAMPLERATIO]
                          [--MaxDisplacement MAXDISPLACEMENT]
                          [--DensitySource DENSITYSOURCE] [--b1 B1]
                          [--b2 B2] [--bG2 BG2] [--fLogGrowth FLOGGROWTH]
  
  optional arguments:
  -h, --help            show this help message and exit
  --SimSeed SIMSEED     Simulation seed to load.
  --boxsize BOXSIZE     Boxsize in Mpc/h.
  --ApplyRSD APPLYRSD   0: No RSD. 1: Include RSD in catalog.
  --Rsmooth RSMOOTH     Smoothing of quad field.
  --Ngrid NGRID         Ngrid used to compute skew spectra.
  --SubsampleRatio SUBSAMPLERATIO
                        Subsample ratio of DM snapshot to use as input.
  --MaxDisplacement MAXDISPLACEMENT
                        Maximum RSD displacement in Mpc/h.
  --DensitySource DENSITYSOURCE
                        Source from which to compute the density. catalog or
                        delta_2SPT
  --b1 B1               b1 bias. Only used if DensitySource=delta_2SPT.
  --b2 B2               b2 bias. Only used if DensitySource=delta_2SPT.
  --bG2 BG2             bG2 bias. Only used if DensitySource=delta_2SPT.
  --fLogGrowth FLOGGROWTH
                        Logarithmic growth factor f. Only used if
                        DensitySource=delta_2SPT.

• For an example SLURM script to run on a cluster, see main_calc_spectra.job.helios.spawn.py and use

  $ python main_calc_spectra.job.helios.spawn.py

• The output is stored in text files.

Jupyter notebooks

• Notebooks to plot results are in the notebooks folder.

Installation

The code requires nbodykit version 0.3.x or higher.

To install this it is best to follow the instructions on the nbodykit website.

To install in a new anaconda environment, use for example

$ cd ~/anaconda/anaconda/envs
$ conda create -n nbodykit-0.3.7-env -c bccp -c astropy python=2.7 nbodykit=0.3.7 bigfile pmesh ujson

Newer versions of nbodykit should also work fine.

To activate the environment, use

$ source activate nbodykit-0.3.7-env

To deactivate it, use

$ source deactivate

To run the skewspec code, clone the github repository to a local folder. Then add it to your PYTHONPATH by adding this line to ~/.bash_profile:

export PYTHONPATH=/Users/mschmittfull/Dropbox/CODE/skewspec:$PYTHONPATH

Contributing

To contribute, create a fork on github, make changes and commits, and submit a pull request on github.