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Title: Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps

Abstract

It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (kappa_WL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the Counts in Cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey (DES) Science Verification data over 139 deg^2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that the galaxy density contrast distribution is well modeled by a lognormal PDF convolved with Poisson noise at angular scales from 10-40 arcmin (corresponding to physical scales of 3-10 Mpc). We note that as kappa_WL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the kappa_WL distribution is well modeled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fit chi^2/DOF of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 andmore » 0.07 respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check we compare the variances derived from the lognormal modelling with those directly measured via CiC. Our methods are validated against maps from the MICE Grand Challenge N-body simulation.« less

Authors:
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Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1352544
Report Number(s):
FERMILAB-PUB-16-161-AE; arXiv:1605.02036
Journal ID: ISSN 0035-8711; 1456127
Grant/Contract Number:
AC02-07CH11359; 291329; AC02-76SF00515; AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 466; Journal Issue: 2; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; gravitational lensing: weak; cosmology: observations; large-scale structure of Universe

Citation Formats

Clerkin, L., Kirk, D., Manera, M., Lahav, O., Abdalla, F., Amara, A., Bacon, D., Chang, C., Gaztañaga, E., Hawken, A., Jain, B., Joachimi, B., Vikram, V., Abbott, T., Allam, S., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carrasco Kind, M., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kent, S., Kuehn, K., Kuropatkin, N., Lima, M., Melchior, P., Miquel, R., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Sanchez, E., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., and Walker, A. R.. Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps. United States: N. p., 2016. Web. doi:10.1093/mnras/stw2106.
Clerkin, L., Kirk, D., Manera, M., Lahav, O., Abdalla, F., Amara, A., Bacon, D., Chang, C., Gaztañaga, E., Hawken, A., Jain, B., Joachimi, B., Vikram, V., Abbott, T., Allam, S., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carrasco Kind, M., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kent, S., Kuehn, K., Kuropatkin, N., Lima, M., Melchior, P., Miquel, R., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Sanchez, E., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., & Walker, A. R.. Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps. United States. doi:10.1093/mnras/stw2106.
Clerkin, L., Kirk, D., Manera, M., Lahav, O., Abdalla, F., Amara, A., Bacon, D., Chang, C., Gaztañaga, E., Hawken, A., Jain, B., Joachimi, B., Vikram, V., Abbott, T., Allam, S., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carrasco Kind, M., Crocce, M., Cunha, C. E., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kent, S., Kuehn, K., Kuropatkin, N., Lima, M., Melchior, P., Miquel, R., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Sanchez, E., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., and Walker, A. R.. 2016. "Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps". United States. doi:10.1093/mnras/stw2106. https://www.osti.gov/servlets/purl/1352544.
@article{osti_1352544,
title = {Testing the lognormality of the galaxy and weak lensing convergence distributions from Dark Energy Survey maps},
author = {Clerkin, L. and Kirk, D. and Manera, M. and Lahav, O. and Abdalla, F. and Amara, A. and Bacon, D. and Chang, C. and Gaztañaga, E. and Hawken, A. and Jain, B. and Joachimi, B. and Vikram, V. and Abbott, T. and Allam, S. and Armstrong, R. and Benoit-Lévy, A. and Bernstein, G. M. and Bernstein, R. A. and Bertin, E. and Brooks, D. and Burke, D. L. and Rosell, A. Carnero and Carrasco Kind, M. and Crocce, M. and Cunha, C. E. and D'Andrea, C. B. and da Costa, L. N. and Desai, S. and Diehl, H. T. and Dietrich, J. P. and Eifler, T. F. and Evrard, A. E. and Flaugher, B. and Fosalba, P. and Frieman, J. and Gerdes, D. W. and Gruen, D. and Gruendl, R. A. and Gutierrez, G. and Honscheid, K. and James, D. J. and Kent, S. and Kuehn, K. and Kuropatkin, N. and Lima, M. and Melchior, P. and Miquel, R. and Nord, B. and Plazas, A. A. and Romer, A. K. and Roodman, A. and Sanchez, E. and Schubnell, M. and Sevilla-Noarbe, I. and Smith, R. C. and Soares-Santos, M. and Sobreira, F. and Suchyta, E. and Swanson, M. E. C. and Tarle, G. and Walker, A. R.},
abstractNote = {It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (kappa_WL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the Counts in Cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey (DES) Science Verification data over 139 deg^2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that the galaxy density contrast distribution is well modeled by a lognormal PDF convolved with Poisson noise at angular scales from 10-40 arcmin (corresponding to physical scales of 3-10 Mpc). We note that as kappa_WL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the kappa_WL distribution is well modeled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fit chi^2/DOF of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07 respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check we compare the variances derived from the lognormal modelling with those directly measured via CiC. Our methods are validated against maps from the MICE Grand Challenge N-body simulation.},
doi = {10.1093/mnras/stw2106},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 2,
volume = 466,
place = {United States},
year = 2016,
month = 8
}

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  • It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (kappa_WL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the Counts in Cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey (DES) Science Verification data over 139 deg^2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirmmore » that the galaxy density contrast distribution is well modeled by a lognormal PDF convolved with Poisson noise at angular scales from 10-40 arcmin (corresponding to physical scales of 3-10 Mpc). We note that as kappa_WL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the kappa_WL distribution is well modeled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fit chi^2/DOF of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07 respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check we compare the variances derived from the lognormal modelling with those directly measured via CiC. Our methods are validated against maps from the MICE Grand Challenge N-body simulation.« less
  • It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (κWL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the counts-in-cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey Science Verification data over 139 deg 2. We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that themore » galaxy density contrast distribution is well modelled by a lognormal PDF convolved with Poisson noise at angular scales from 10 to 40 arcmin (corresponding to physical scales of 3–10 Mpc). We note that as κWL is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the κWL distribution is well modelled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fitting χ 2/dof of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07, respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check, we compare the variances derived from the lognormal modelling with those directly measured via CiC. Finally, our methods are validated against maps from the MICE Grand Challenge N-body simulation.« less
  • We measure the redshift evolution of galaxy bias from a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for amore » $$\sim$$116 deg$$^{2}$$ area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al., in prep) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a magnitude-limited galaxy sample. We find the galaxy bias and 1$$\sigma$$ error bars in 4 photometric redshift bins to be 1.33$$\pm$$0.18 (z=0.2-0.4), 1.19$$\pm$$0.23 (z=0.4-0.6), 0.99$$\pm$$0.36 ( z=0.6-0.8), and 1.66$$\pm$$0.56 (z=0.8-1.0). These measurements are consistent at the 1-2$$\sigma$$ level with mea- surements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing. In addition, our method provides the only $$\sigma_8$$-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.« less
  • We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ~116 deg 2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars inmore » four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2–0.4), 0.97 ± 0.15 (z = 0.4–0.6), 1.38 ± 0.39 (z = 0.6–0.8), and 1.45 ± 0.56 (z = 0.8–1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Moreover, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.« less
  • Here, we measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ~116 deg 2 area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al. 2016) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy biasmore » and 1σ error bars in 4 photometric redshift bins to be 1.12±0.19 (z=0.2-0.4), 0.97±0.15 (z=0.4-0.6), 1.38±0.39 (z=0.6-0.8)), and 1.45±0.56 (z=0.8-1.0). These measurements are consistent at the 2σ level with measurements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing, with most of the redshift bins consistent within the 1{\sigma} error bars. In addition, our method provides the only σ8-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.« less