Shadab Alam | 
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Multi-Tracer HOD model
We develop a new Multi-Tracer Halo Occupation Distribution (MTHOD) framework for the galaxy distribution. Here you can find some code and data released with publications based on this model.The MTHOD framework essentially try to model multiple population of galaxies in a single framwork with flexibility to associat properties and model of individual galaxies as well as introduce interaction between them.
The first paper where we propose the framework and apply it to the extended Baryon Oscillation Spectroscopic Survey (eBOSS) final data between $z=0.7-1.1$ can be found on arXiv:1910.05095.
We obtain a best fit MTHOD for each tracer and describe the host halo properties of these galaxies. The mean halo masses for LRGs, ELGs and QSOs are found to be $1.9 \times 10^{13} \msolaroh$, $1.1 \times 10^{12} \msolaroh$ and $5 \times 10^{12} \msolaroh$ respectively in the eBOSS data. We use the \mthod\, framework to create mock galaxy catalogues and predict auto- and cross-correlation functions for all the tracers. Comparing these results with data, we investigate galactic conformity, the phenomenon whereby the properties of neighbouring galaxies are mutually correlated in a manner that is not captured by the basic halo model. We detect \textsl{1-halo} conformity at more than 3$\sigma$ statistical significance, while obtaining upper limit on \textsl{2-halo} conformity. We also look at the environmental dependence of the galaxy quenching efficiency and find that halo mass driven quenching successfully explains the behaviour in high density regions, but it fails to describe the quenching efficiency in low density regions. In particular, we show that the quenching efficiency in low density filaments is higher in the observed data, as compared to the prediction of the MTHOD with halo mass driven quenching.
The mock galaxy catalogue constructed in the above paper are following:
- Mock with HMQ model for ELG is here, subsampled to eBOSS density here and one including environments here
- Mock with erf model for ELG (Note this is only for comparision and non physical model for star-forming galaxies) is here, subsampled to eBOSS density here and one including environments here
How to create the MTHOD mock catalog
You can download the required code from here.It requires python 2.7 with python libraries numpy, scipy, fitsio, pylab, time, collections.
Follow these steps once you have the code to create these mocks:
- Download the halo catalog:
MDPL2 halo catalog at z~0.85 - The downloaded halo catalog is in ascii format. We need to convert them to FITS format for efficiency purpose. This can be achieved following this command:
python convert-halo-fits.py -halo_cat < downloaded_hal_file_name > -out_fits < output_halo_fits_file_name > - Create mock with HMQ model for ELG using following command (The parameters are from Table 1 of the paper):
python MultiHOD_populate.py -Lbox 1000 -samples S1 S2 S3 -LMcut_S1 12.99 -LM1_S1 14.24 -sigma_S1 0.60 -alpha_S1 0.40 -kappa_S1 0.98 -pmax_S1 0.33 -gammaIHV_S1 0.577 -HODmodel_S1 normal -LMcut_S2 12.21 -LM1_S2 14.09 -sigma_S2 0.60 -alpha_S2 0.39 -kappa_S2 1.0 -pmax_S2 0.33 -gammaIHV_S2 0.577 -HODmodel_S2 QSO -LMcut_S3 11.88 -LM1_S3 13.94 -sigma_S3 0.56 -alpha_S3 0.40 -kappa_S3 1.02 -pmax_S3 0.33 -gammaIHV_S3 0.577 -HODmodel_S3 normal -halo_type MDPL2 -satelite scalers -redshift 0 -xispace Real -subhalo 0 -outgal whaloid -hcat < halo_cat.fits > -outroot < mock_output_file > - Create mock with erf model for ELG using following command
python MultiHOD_populate.py -Lbox 1000 -samples S1 S2 S3 -LMcut_S1 12.99 -LM1_S1 14.24 -sigma_S1 0.60 -alpha_S1 0.40 -kappa_S1 0.98 -pmax_S1 0.33 -gammaIHV_S1 0.577 -HODmodel_S1 normal -LMcut_S2 12.21 -LM1_S2 14.09 -sigma_S2 0.60 -alpha_S2 0.39 -kappa_S2 1.0 -pmax_S2 0.33 -gammaIHV_S2 0.577 -HODmodel_S2 QSO -LMcut_S3 11.75 -LM1_S3 13.53 -sigma_S3 0.58 -alpha_S3 1.0 -kappa_S3 0.01 -pmax_S3 0.33 -gammaIHV_S3 0.577 -gamma_S3 4.12 -HODmodel_S3 ELG -halo_type MDPL2 -satelite scalers -redshift 0 -xispace Real -subhalo 0 -outgal whaloid -hcat < halo_cat.fits > -outroot < mock_output_file >
We are working on tidying up the associated code to measure environment, galactic conformity and find best fit MTHOD parameters. These will be made available in the future.