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

Journal Article · · Monthly Notices of the Royal Astronomical Society
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  1. Univ. College London, London (United Kingdom)
  2. Univ. College London, London (United Kingdom); Rhodes Univ., Grahamstown (South Africa)
  3. ETH Zurich, Zurich (Switzerland)
  4. Univ. of Portsmouth, Portsmouth (United Kingdom)
  5. Institut de Ciencies de l'Espai (ICE, IEEC/CSIC), Bellaterra (Barcelona) (Spain)
  6. Istituto Nazionale di Astrofisica - Osservatorio Astronomico di Brera, Merate (Italy)
  7. Univ. of Pennsylvania, Philadelphia, PA (United States)
  8. Cerro Tololo Inter-American Observatory, La Serena (Chile)
  9. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  10. Princeton Univ., Princeton, NJ (United States)
  11. Univ. College London, London (United Kingdom); Institut d'Astrophysique de Paris, Paris (France)
  12. Carnegie Observatories, Pasadena, CA (United States)
  13. Institut d'Astrophysique de Paris, Paris (France)
  14. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
  15. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Observatorio Nacional, Rio de Janeiro (Brazil)
  16. Univ. of Illinois, Urbana, IL (United States); National Center for Supercomputing Applications, Urbana, IL (United States)
  17. Stanford Univ., Stanford, CA (United States)
  18. Univ. of Portsmouth, Portsmouth (United Kingdom); Univ. of Southampton, Southampton (United Kingdom)
  19. Excellence Cluster Universe, Garching (Germany); Ludwig-Maximilians-Univ., Munich (Germany)
  20. Univ. of Pennsylvania, Philadelphia, PA (United States); California Inst. of Technology (CalTech), Pasadena, CA (United States)
  21. Univ. of Michigan, Ann Arbor, MI (United States)
  22. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Univ. of Chicago, Chicago, IL (United States)
  23. The Ohio State Univ., Columbus, OH (United States)
  24. Australian Astronomical Observatory, North Ryde, NSW (Australia)
  25. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Univ. de Sao Paulo, Sao Paulo (Brazil)
  26. Institucio Catalana de Recerca i Estudis Avancats, Barcelona (Spain); The Barcelona Institute of Science and Technology, Bellaterra (Barcelona) (Spain)
  27. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  28. Univ. of Sussex, Brighton (United Kingdom)
  29. SLAC National Accelerator Lab., Menlo Park, CA (United States); Univ. of Chicago, Chicago, IL (United States)
  30. Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain)
  31. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Univ. Estadual Paulista, Sao Paulo (Brazil)
  32. National Center for Supercomputing Applications, Urbana, IL (United States)
+ Show Author Affiliations

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 deg2. 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 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 χ2/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. Lastly, our methods are validated against maps from the MICE Grand Challenge N-body simulation.

Research Organization:
SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); The Ohio State Univ., Columbus, OH (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Organization:
DES Collaboration
Grant/Contract Number:
291329; AC02-76SF00515; AC02-07CH11359; AC05-00OR22725; SC0011726
OSTI ID:
1352544
Alternate ID(s):
OSTI ID: 1288751; OSTI ID: 1352813; OSTI ID: 1602513
Report Number(s):
FERMILAB-PUB-16-161-AE; arXiv:1605.02036; TRN: US1701683
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 466, Issue 2; ISSN 0035-8711
Publisher:
Royal Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 44 works
Citation information provided by
Web of Science

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Cited By (13)

High-precision Monte Carlo modelling of galaxy distribution journal January 2020
A nulling strategy for modelling lensing convergence in cones with large deviation theory journal January 2020
Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV journal May 2018
Testing (modified) gravity with 3D and tomographic cosmic shear journal August 2018
Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data journal October 2018
Cylinders out of a top hat: counts-in-cells for projected densities journal March 2018
Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: Application to DES SV text January 2018
Cylinders out of a top hat: Counts-in-cells for projected densities text January 2018
Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing text January 2017
Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data text January 2017
Cylinders out of a top hat: counts-in-cells for projected densities text January 2017
Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data text January 2018
High-precision Monte-Carlo modelling of galaxy distribution text January 2019

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