Crurent and Future Massive Redshift Surveys - LASTRO Light on the Dark - ISDC
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Galaxy Power Spectrum
Size of the Horizon: mass-radiation
equilibrium
3D mapping of the position of Dark Energy:
galaxies non-gaussian initial
fluctuations
Baryonic Acoustic Oscillation
Dark Matter Warm/
Cold
Neutrinos
Masses
Galaxy halo occupation Growth of
distribution (HOD) structure
Distribution of galaxies (SDSS)
EPFL/LASTRO - J.-P. Kneib 2Neutrinos impact on LSS
How sum of neutrino masses affect the density field
28
10
29
10
Density (g/cm3)
30
10
31
10
X X
m⌫ = 0 eV m⌫ = 1eV
eV
EPFL/LASTRO - J.-P. Kneib Figure Credit: Agarwal & Feldman 3Broad BandPower
Broadband Power Spectrum
Spectrum
2025
• 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 Future projects:
photo-z’s
MSE, SSSI (DOE),
EPFL/LASTRO - J.-P. Kneib China, ESO 4Massive Redshift Surveys
• Hubble (1930): expanding Universe
• CfA Redshift Survey (1985): first
large scale structures
• 2dF (2000-6): 1500 deg2
• SDSS (2002-9): 5700 deg2
• zCOSMOS (2005-10): 2 deg2
MOONS
• WiggleZ (2011): 800 deg2 (BAO)
DESI
• SDSS-III/BOSS (2014): 10,000 deg2
eBOSS
BAO/LSS (BAO)
• e-BOSS (2014-2020): 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 ...
EPFL/LASTRO - J.-P. Kneib 5The 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
EPFL/LASTRO - J.-P. Kneib 6eBOSS (2014-2020)
• 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 0.6DESI (2019-2024)
5000 fiber actuators
New 3° field-of-view
corrector
10 New
spectrographs
Mayall 4m Telescope
35 Millions redshifts
• 30 4x4k detectors Most of them will be ELGs
•100 Tb/year •BAO at sub-% level
•Complex data/algo •Gravity
•Neutrino Masses
•Inflationary model
EPFL/LASTRO - J.-P. Kneib 9Euclid (2020-2025)
• Euclid is a major wide-field imaging
and spectroscopy space mission, lead
by ESA (+NASA participation).
Launched in 2020.
• Strong implication of Swiss
Astronomers (UniGe, EPFL, UniZH,
FHNW).
• 15’000 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.
EPFL/LASTRO - J.-P. Kneib 104MOST (2021-2026)
! Cosmology!and!galaxy!evolu0on • Approved by ESO council - Southern Sky
! Euclid spectroscopic survey to start in 2021
• Complementary to DESI in the North
! High4energy!sky
' eROSITA • Complementary to Euclid (focus on 1Number of spectra
Number of spectra
4MOST
DESI
Euclid
BOSS
eBOSS
SDSSI/II
WiggleZ
2MRS
CFA
Year experiment finishes
Shirley Ho
EPFL/LASTRO - J.-P. Kneib 12DESI Data Needs
• Example for DESI (4MOST/Euclid-spectro will be similar)
★ Data Volume (2016-2023):
✦ DESI Imaging Data: 850 Tb
✦ DESI Data: 800 Tb => 100 Tb (once data reduced)
✦ Simulations (for analysis): 150 Tb
✦ Total: 1’800 Tb ~ 2 Pb => 1 Pb (once reduced)
★ CPU hours:
✦ operation 2019-2023 : 10-20 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)
EPFL/LASTRO - J.-P. Kneib 13EPFL/LASTRO - J.-P. Kneib 14
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
EPFL/LASTRO - J.-P. Kneib 15EPFL/LASTRO - J.-P. Kneib 16
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