Crurent and Future Massive Redshift Surveys

Transcription

1 Crurent and Future Massive Redshift Surveys Jean-Paul Kneib LASTRO Light on the Dark

2 Galaxy Power Spectrum 3D mapping of the position of galaxies non-gaussian initial fluctuations Size of the Horizon: mass-radiation equilibrium Dark Energy: Baryonic Acoustic Oscillation Dark Matter Warm/ Cold Neutrinos Masses Distribution of galaxies (SDSS) Galaxy halo occupation distribution (HOD) Growth of structure 2

3 Neutrinos impact on LSS X m = 0 ev X Density (g/cm3) How sum of neutrino masses affect the density field m = 1eV ev Figure Credit: Agarwal & Feldman 3

4 Broad Broadband Band Power Spectrum Redshig Space DistorPons: Since P is smaller on scales of interest, noise (np) -1 is larger and geqng greater density than DESI would pay off. Different tracers might mipgate cosmic variances. Higher density tracers might trace the dark maber more efficiently Might get more objects at lower S/N by exploipng photo-z s <2025 >2025 Future projects: MSE, SSSI (DOE), China, ESO 4

5 Massive Redshift Surveys MOONS DESI eboss Hubble (1930): expanding Universe CfA Redshift Survey (1985): first large scale structures 2dF (2000-6): 1500 deg2 SDSS (2002-9): 5700 deg2 zcosmos ( ): 2 deg2 WiggleZ (2011): 800 deg2 (BAO) SDSS-III/BOSS (2014): 10,000 deg2 BAO/LSS (BAO) e-boss ( ): BAO/LSS: 7,500deg2 w/ LRG+QSO & 1,500deg2 of ELGs DESI (2019), 4MOST (2021) Optical MOONS (2020) Infrared Euclid (2020) Space mission SKA (2025) Radio Telescope future projects... 5

6 The Sloan Telescope & Spectrograph 90 cm aluminium plate with 1000 holes for fibers, 45 min to plug for typical 1 hour observation on sky up to 9 plates observed per (good) night 1.5 millions redshifts in ~4 years The best multiplexing spectroscopic facility still 6

7 BOSS ( ) Busca et al

8 eboss ( ) eboss = cosmology survey of SDSS-IV Fully funded for 5yr (likely 6) 1/4 of the telescope time Uses BOSS spectrograph, targets from SDSS+WISE imaging ~150 participating scientists extend BOSS to unexplored redshift window 0.6<z<2 ~10 Tb/year Computing at NERSC (simulations) and at Utah University Computing Centre (data reduction) 8

9 DESI ( ) 5000 fiber actuators New 3 field-of-view corrector 10 New spectrographs Mayall 4m Telescope 35 Millions redshifts 30 4x4k detectors 100 Tb/year Complex data/algo Most of them will be ELGs BAO at sub-% level Gravity Neutrino Masses Inflationary model 9

10 Euclid ( ) Euclid is a major wide-field imaging and spectroscopy space mission, lead by ESA (+NASA participation). Launched in Strong implication of Swiss Astronomers (UniGe, EPFL, UniZH, FHNW) sq.deg to be covered with space-images: 260 Gb/day; ~100 Tb/ year. Euclid data will also included other ground-based images/spectroscopy (including LSST) ~10 Pb/year. Switzerland will host one of the Euclid Data Centre. Pierre Dubath presentation for details. 10

11 4MOST ( )! Cosmology!and!galaxy!evolu0on! Euclid! High4energy!sky ' erosita! Galac0c!Archeology ' Gaia Fibre positioner Wide-Field Corrector Approved by ESO council - Southern Sky spectroscopic survey to start in 2021 Complementary to DESI in the North Complementary to Euclid (focus on 1<z<2) Cosmology survey will gather ~20 million of spectra of galaxy and AGNs and focus to z<1 EPFL joined the project in 2016 and is coleading the Cosmology project Fibre Feed Low-Resolution Spectrographs (2x) High-Resolution Spectrograph (1x) 11

12 Number of spectra Number of spectra 4MOST SDSSI/II BOSS DESI Euclid eboss CFA 2MRS WiggleZ Shirley Ho Year experiment finishes 12

13 DESI Data Needs Example for DESI (4MOST/Euclid-spectro will be similar) Data Volume ( ): DESI Imaging Data: 850 Tb DESI Data: 800 Tb => 100 Tb (once data reduced) Simulations (for analysis): 150 Tb Total: Tb ~ 2 Pb => 1 Pb (once reduced) CPU hours: operation : millions CPU-hours/year (mostly for main pipeline 2D images => spectra - data analysis/mining will likely be less) simulations ~20 millions CPU-hours DESI approach is to use NERSC supercomputer facility (not distributed) 13

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15 Example of Data Usage Computing 1D and 2D correlation function (number of pairs of galaxies separated by a distance of r as a function of r ) on data and on mocks (complexity: handling selection function and completness information) Full mocks, including simulated observation strategy (100s of mocks compare to 1 set of cosmological data) Extracting information from spectra & other data: double objects spectra (lenses, AGN and SN signatures) - mining spectra variability spectra - comparison across database combining spectra information with imaging/lensing - combining data information across database 15

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