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Cosmological inference from self-consistent Bayesian forward modelling of deep galaxy redshift surveys Doogesh Kodi Ramanah Guilhem Lavaux Jens Jasche Ben Wandelt Institut dAstrophysique de Paris Statistical challenges for large-scale

  1. Cosmological inference from self-consistent Bayesian forward modelling of deep galaxy redshift surveys Doogesh Kodi Ramanah Guilhem Lavaux Jens Jasche Ben Wandelt Institut d’Astrophysique de Paris Statistical challenges for large-scale structure in the era of LSST, Oxford, 2018

  2. Cosmological data challenges ● Incomplete noisy sky with systematic efgects (masks, complex noise models, ...) ● Transformation: physical (comoving) space observational space Noisy large-scale structure data signal reconstruction Cosmology encoded in expansion & global geometry (Alcock-Paczyński efgect) SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 1

  3. Cosmological data challenges ● Incomplete noisy sky with systematic efgects (masks, complex noise models, ...) ● Transformation: physical (comoving) space observational space Noisy large-scale structure data Credit: Assassin’s Creed (Ubisoft ) AQUILA Consortium HADES BORG ALTAIR ALTAIR ( AL cock-Paczyński cons T r AI ned R econstruction) ( DKR, Lavaux & Wandelt 2018, in prep. ) ● Liberate cosmology → Cosmological parameter inference via the Alcock-Paczyński (AP) test ● Also jointly infer underlying 3D power spectrum + more realistic ( non-linear ) bias model SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 1

  4. Alcock-Paczyński Test Coordinate Transformation Redshift space Comoving space ● Test of the expansion & geometry of the Universe ● No dependence on evolution of galaxies but only on geometry of Universe SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 2

  5. Alcock-Paczyński Test Coordinate Transformation ● Distortions due to assumption of incorrect cosmological parameters ● Structure: Redshift space Comoving space Spherical → Ellipsoidal ● Statistical distribution: Isotropic → Anisotropic ● Test of the expansion & geometry of the Universe ● No dependence on evolution of galaxies but only on geometry of Universe SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 2

  6. Visualising cosmic expansion [Standard ΛCDM] ● Initial conditions SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 3

  7. Visualising cosmic expansion [Standard ΛCDM] ● Initial conditions Final (LPT) density fjeld Comoving space SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 3

  8. Visualising cosmic expansion [Standard ΛCDM] ● Initial conditions Final (LPT+AP) density fjeld Redshift space SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 3

  9. Visualising cosmic expansion [Einstein-de Sitter Universe] ● Initial conditions Final (LPT+AP) density fjeld Redshift space SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 3

  10. ALTAIR reconstruction scheme Data model: SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 4

  11. ALTAIR reconstruction scheme comoving grid coordinate transformation + trilinear interpolation redshift grid ● Redshift space representation allows comparison with data via Data model: likelihood SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 4

  12. ALTAIR reconstruction scheme Transforms Gaussian initial conditions into a non-linearly evolved fjeld comoving grid coordinate transformation + trilinear interpolation redshift grid ● Redshift space representation allows comparison with data via Data model: likelihood SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 4

  13. Validation on mock catalogues (A) - 2M++ 2M++ galaxy compilation : ( Lavaux & Hudson 2011 ) ● Superset of { 2MASS, SDSS-DR7, 6dFGRS-DR3 } redshift surveys ● Greater depth & higher sampling than IRAS survey ● Sub-divided into 2 K -bands ● Anisotropic selection and strong galaxy clustering SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 5

  14. Validation on mock catalogues (A) - 2M++ 2M++ galaxy compilation : ( Lavaux & Hudson 2011 ) ● Superset of { 2MASS, SDSS-DR7, 6dFGRS-DR3 } redshift surveys ● Greater depth & higher sampling than IRAS survey ● Sub-divided into 2 K -bands ● Anisotropic selection and strong galaxy clustering Grid with 32³ voxels Simulation box 1200 Mpc side length ● Tested on low-resolution mock data ● Forward model: LPT + AP ● ~ Linear expansion regime ● Broad posterior for Ω m SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 5

  15. Validation on mock catalogues (B) - SDSSIII Grid with 128³ voxels Simulation box 4000 Mpc side length ● Forward model: LPT + AP ● Highly structured survey geometry & selection efgects Sky completeness SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 6

  16. Validation on mock catalogues (B) - SDSSIII Grid with 128³ voxels Simulation box 4000 Mpc side length ● Forward model: LPT + AP ● Probing higher redshift range; AP distortion due to cosmic expansion is much more informative ● Tight constraints on Ω m Sky completeness SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 6

  17. Ensemble mean & error maps Initial density fjeld Slice through 3D density fjeld Final density fjeld SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 7

  18. Current & future work Current project: ( DKR, Lavaux & Wandelt 2018c, in prep. ) ● Implemented forward model for AP distortion and cosmological parameter sampler ● Tested on low-resolution mock (2M++, SDSS-III) data ● Chain forward models: LPT + AP ● Upgrade forward model to 2LPT and jointly infer mean density of tracers & bias also ● Assess impact of redshift space distortions ( RSDs ) on cosmological constraints SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 8

  19. Current & future work Current project: ( DKR, Lavaux & Wandelt 2018c, in prep. ) ● Implemented forward model for AP distortion and cosmological parameter sampler ● Tested on low-resolution mock (2M++, SDSS-III) data ● Chain forward models: LPT + AP ● Upgrade forward model to 2LPT and jointly infer mean density of tracers & bias also ● Assess impact of redshift space distortions ( RSDs ) on cosmological constraints Future work: ● Encode power spectrum inference in the block sampling scheme Follow-up project ● Account for RSDs in the data model ● Showcase application of ALTAIR on real data sets (e.g. SDSS-III ): → Joint inference of 3D density fjeld, underlying power spectrum & cosmological parameters Relevant for current & next-generation galaxy redshift surveys (Euclid, LSST, ...) SCLSS 2018, Oxford Cosmological inference from Bayesian forward modelling of galaxy surveys 8

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