Galaxy Survey data analysis using SDSS-III as an example

Galaxy Survey data analysis 


using SDSS-III as an example


Will Percival (University of Portsmouth)


showing work by the BOSS galaxy clustering working group"

Cosmology from Spectroscopic Galaxy Surveys"

Galaxy Redshift"

Survey"

What are the constituents of matter?" What is the physics of inflation?" e.g. neutrino mass, primordial P(k)"

What is the expansion rate of the Universe?" e.g. quintessence, Λ"

How does structure form within this background?" e.g. modified gravity, GR"

Is the Universe homogeneous " on large scales?"

Copernican principle, Non-Gaussianity"

Other non-cosmology science" e.g. galaxy formation & evolution" Redshift-space distortions"

Understanding " acceleration"

What does “galaxy clustering” mean?"

P(k) = _k(k)2

⇥(d) = (r) (r + d)

Clustering strength = number of galaxy pairs"

" "beyond random"

Correlation function (preview)" ⇠₀(s) = Z 1 0 dµ⇠(s, µ) ⇠₂(s) = 5 Z 1 0 dµ⇠(s, µ)L₂(µ) Monopole ξ_0! Quadrupole ξ_2!

Power spectrum (preview)"

Spherically averaged

power spectrum P(k)"

SDSS-III BOSS summary"

•  Duration: Fall 2009 - Summer 2014, dark time"

•  Telescope: 2.5m Sloan "

•  Upgrade to SDSS-II spectrograph"

–  1000 smaller fibers" –  higher throughput" •  Spectra: " –  3600 ̊A < λ < 10,000 ̊A New spectrograph" –  R = λ/∆λ = 1300 − 3000" –  (S/N) at mag. limit"

•  22 per pix. (averaged over 7000-8500Å)"

•  10 per pix. (averaged over 4000-5500Å) "

•  Area: 10,000 deg2 "

•  Targets: "

–  1.5 × 106 _{massive galaxies, z < 0.7, i < 19.9"}

–  1.5×105 _{quasars, z>2.2, g<22.0 selected from 4 × 10}5 _{candidates "}

–  75,000 ancillary science targets, many categories "

•  Measurements from Galaxies: "

–  d_A(z) to 1.2% at z = 0.35 and 1.2% z = 0.6 " –  H(z) to 2.2% at z = 0.35 and 2.0% at z = 0.6 "

•  Measurements from Lyα Forest: "

Data served to the public"

•  Availability through DAS, CAS & CASJOBS"

•  DAS (Data Archive Server)"

–  provides raw data in “fits” files" –  expert users only"

•  CAS (Catalog Archive Server)"

–  SQL database with fast search " "capabilities"

•  CASjobs"

–  online workbench"

–  includes “history”, “user personalized database”, group options, download options, interface options"

•  Periodic (yearly) data releases"

•  SDSS collaboration published 516 papers to end 2008"

Galaxy distribution" SDSS-II main " galaxies" SDSS-II LRGs" BOSS CMASS " galaxies"

147 pages on “large-scale galaxy clustering”"

•  Anderson et al. (alphabetical) arXiv:1203.6565 - BAO measurement in power-spectrum and correlation

function. "

•  Reid et al. arXiv:1203.6641- Anisotropic clustering,

redshift-space distortion measurements. "

•  Sanchez et al. arXiv:1203.6616 - Fits to the full shape of

the correlation function. "

•  Ross et al. arXiv:1203.6499 - Large-scale systematics. " •  Manera et al. arXiv:1203.6609 - 600 PTHalo mocks. " •  Tojeiro et al. arXiv:1203.6565 - Enhanced

redshift-space distortion measurements."

•  Samushia et al. arXiv:1206.5309 – Testing Λ & GR"

A collaborative effort …"

The CMASS galaxy sample"

Standard  colour  selec.on  criteria  

Also  include  star-­‐galaxy  separa.on  criteria  

Extends  SDSS-­‐II  LRG  cuts  to   cover  both  blue  and  red   massive  galaxies  at  higher   redshi@s  

SDSS-II LRGs"

Galaxy distribution: not like an N-body simulation!"

Needs care, but doesn’t change numerical requirements

Catalog creation"

Anderson et al. 2012; Ross et al. 2012"

need a “random” catalog to

Redshift failures & close pairs"

•  Spectra where we failed to get an accurate redshift are spatially

correlated"

•  Close pairs obviously correlated with

density"

•  Correct both by upweighting the

nearest target with good classification "

Target density fluctuations"

•  Target density correlates with stellar density and brightness"

•  Corrected by weighting"

•  See Ross et al. for more details"

Reconstruction of linear positions"

Measuring a distance"

•  Fit the observed acoustic feature using some way to parametrize over nuisance broad-band features (different approaches for P(k) and ξ(r))" •  Use a fiducial model to compare against

observed features in spherically averaged statistics. Departures quantified by dilation scale α:"

" "P(k/α) ξ(αr)"

•  The dilation scale α depends on cosmology through:"

" "D_V /r_s = α(D_V /r_s)_fid " " "D_V = [cz(1 + z)2_d

A2 H-1]1/3 "

Reconstruction on CMASS mocks"

Reconstruction on CMASS"

Reconstruction: error on α"

Correla.on  func.on  

Power  spectrum  

BAO fitting, likelihood calculation"

Analysis steps requiring significant computation" •  Data analysis"

–  raw data reduction, spectral extraction"

–  spectral fitting, redshift extraction"

•  Catalog & mask creation" •  Reconstruction"

–  calculation"

•  Correlation function calculation"

–  N_gal2 _{operation, some algorithms N}

gallog(Ngal)"

•  Power-spectrum calculation"

–  N_gridlog(N_grid), N_grid ~ 2048,4096"

•  BAO & 2-pt statistics fitting and cosmological

likelihood calculation" ~2 0 0 C PU h o u rs "

Mock catalogues"

•  Mocks needed to calculate covariances, and test analysis methods"

•  Mock calculation would ideally be bases on N-body simulations" •  Too time-consuming so use approximate methods (e.g. based

on 2nd _{order fields)"}

•  For BOSS DR9, 600 mocks created by populating 2LPT field using the CMASS HOD (galaxy—mass relation)"

Analysis steps requiring significant computation"

•  Mock catalog creation"

–  each takes ~200 CPU/hours"

•  Mock catalog analysis"

–  each takes ~200 CPU/hours (same

as data)"

•  Multiply by 600 gives significant computing request"

BOSS CMASS clustering measurements"

Key BAO measurements"

•  ξ(r)  and  P(k)  based  es.ma.ons  are  appropriate  and  

unbiased,  but  they  include  the  noise  from  small  scales  and   shot  noise  differently  

•  We  average  the  two  results,  and  compute  the  error  bar  

using  the  observed  sca2er  of  the  average  value  in  the  

mocks.  This  shows  no  significant  departure  from  a  Gaussian  

CMASS results"

Extra information from additional measurements"

•  Including the quadrupole allows us to measure H and d_A separately (or include an additional

measurement of F) " –  F = (1+z) d_A(z)H(z)/c "

–  F called the Alcock-Paczynski parameter "

•  Measure the growth rate from the peculiar velocities through redshift-space distortions"

–  fσ₈(z=0.57)"

–  amplitude of velocity field"

•  See a wide variety of physics from the full shape of the clustering statistic (as a function of scale)"

The ESA Euclid Mission"

Space-based Vis and NIR observations of galaxies" " VIS Imaging" NIR Photometry" NIR Spectroscopy" NIR Imaging" Tomographic shear"

machine" Redshift machine"

Dark Matter and Galaxy !

PowerSpectra-meters!

Explorer of gravity and expansion"

Astronomical data base for " Legacy science"

SDSS-II LRG clustering" SDSS LRGs at z~0.35" " Total effective volume" V_eff = 0.26 Gpc3_h-3_" " ~100,000 galaxies"

BOSS CMASS DR9 galaxy clustering" BOSS CMASS galaxies at z~0.57" " Total effective volume" V_eff = 0.77 Gpc3_h-3_" " ~300,000 galaxies" Anderson et al."

Predicted Euclid galaxy clustering"

Redshift slice"

0.9 < z < 1.1"

"

Total effective

volume (of Euclid)"

V_eff = 19.7 Gpc3_h-3_"

"

~52,000,000

ΛCDM models with curvature" flat wCDM models"

Union supernovae" WMAP 5year"

SDSS-II BAO Constraint on r_s(z_d)/D_V(0.2) & r_s(z_d)/D_V(0.35) "

Percival et al. 2009; arXiv:0907.1660"

ΛCDM models with curvature" flat wCDM models"

Union supernovae" WMAP 5year"

SDSS-II BAO Constraint on r_s(z_d)/D_V(0.2) & r_s(z_d)/D_V(0.35) "

Conclusions"

•  Science extraction from surveys requires significant

computational effort"

•  Recent BOSS analysis required ~106 CPU hours"

–  Anderson et al. (alphabetical) arXiv:1203.6565 " –  Reid et al. arXiv:1203.6641 "

–  Sanchez et al. arXiv:1203.6616 " –  Ross et al. arXiv:1203.6499 " –  Manera et al. arXiv:1203.6609 " –  Tojeiro et al. arXiv:1203.6565" –  Samushia et al arXiv:1206.5309"

•  Spread between a number of groups and computers"

•  Significant future resources needed as surveys increase in

size (100x jump in next 10 years, with requirement going as