The 2dF galaxyredshift survey
John Peacock
& the 2dFGRS team
Harvard, October 1999
Outline
Brief history
2dF Survey motivation & design
Survey data
Spectral classification
Results:
– Luminosity function
– Correlation function
Galaxy bias & future issues
History of galaxy clustering 1930s: Hubble lognormal cell counts 1940s/50s: Eyeball surveys (Shane & Wirtanen,
Zwicky, Abell…) 1970s: Correlation functions
mass= 0(1+) A(r) = < (x) (x+r) >
(1) Autocorrelation function
(2) Two-point correlations
r prob(pair) = <n>2 dV1 dV2 [1 + 2(r) ]dV1
dV2
A(r) = 2(r) ? - only if Poisson Clustering Hypothesis is true
Meaning of clustering
Neyman Scott & Shane (1953): random clump model
r (r < R) ”r
obs: r”= 2.4?
Modern view: gravitational instability of (C)DM
- sheets, pancakes, filaments, voids...
Las Campanas Redshift Survey~25000 z’s
CfA/SSRS z-survey
~15000 z’s
Redshift Surveys
The 2dF Galaxy Redshift Survey
Aim for LCRS X 10 = 250,000 z’s Increase sky coverage to get fully 3D sample
– Measure >100-Mpc power
– Test Gaussian nature of linear fluctuations
– Measure redshift-space distortions Increase sampling density
– Spatial distribution for different galaxy types
– Tests of theories for biased galaxy formation
2dFGRS Survey Team
Australian team members: Matthew Colless, Joss Bland-Hawthorn, Russell Cannon, Warrick Couch, Kathryn Deeley, Roberto De Propris, Karl Glazebrook, Carole Jackson, Ian Lewis, Bruce Peterson, Ian Price, Keith Taylor.
British team members: Steve Maddox, John Peacock, Shaun Cole, Chris Collins, Nicholas Cross, Gavin Dalton, Simon Driver, George Efstathiou, Richard Ellis, Carlos Frenk, Ofer Lahav, Stuart Lumsden, Stephen Moody, Peder Norberg, Shai Ronen, Mark Seabourne, Robert Smith, Will Sutherland, Helen Tadros.
2dFGRS parameters Galaxies: bJ 19.45 from revised APM
Total area on sky ~ 2000 º 250,000 galaxies in total, 93% sampling rate Mean redshift <z> ~ 0.1, almost all with z < 0.3
2dFGRS geometry
NGP
SGP
NGP 75x7.5 SGP 75x15 Random 100x2Ø ~70,000 ~140,000 ~40,000
~2000 sq.deg.250,000 galaxies
Strips+random fields ~ 1x108 h-3 Mpc3
Volume in strips ~ 3x107 h-3 Mpc3
Tiling strategy‘2dF’ = ‘two-degree field’ = 400 spectra
Efficient sky coverage, but variable completeness
High completeness through adaptive tiling: multiple coverage of high-density regions
Sampling: 2dF vs LCRS
2dFGRS (~93%)
LCRS (~25%)
Calibrating photometry
Recalibrated number counts
Old APMcounts
RecalibratedAPM counts
The 2dF site
Prime Focus
Th
e 2d
F f
acil
ity
2dF on the AAT
Configuring fibres
>12 arcsec spacing; 15 degree bend
<10 seconds to position each fibre
Data pipeline: real-time X-corr z’s
Exa
mp
le s
pec
tra
Survey status - August 1999
Observed:– 227/1093 fields– 58764 targets– 4037 repeats
Redshifts/IDs:– 53192 (91% complete)– 50180 galaxies– 2993 stars, 19 QSOs
Redshift yield
The median redshift yield is 93%.
10% of fields have a yield less than 80%.
30% of fields have a yield less than 90%.
After ADC s/w fix, good conditions routinely give yields >95%.
Reliability: of 1404 z’s in overlap with LCRS, only 8 disagree (99.4% agree).
Completeness
Redshift completeness is >90% for bJ<19 but drops to 80-85% at bJ=19.45.
Completeness is similar in NGP and SGP strips.
Completeness as a function of magnitude varies with the overall completeness of the field.
Selection function depends on (at least) overall completeness and magnitude.
Survey mask
NGP
SGP
Cutouts are bright stars and satellite
trails.
Selection mask
NGP
SGP
‘Bitten-cookie’ effect from missing overlap tiles.
0% 100%
0% 100%
Stellar contamination
Contamination by objects with
z~0.
SGP
NGP
Typical level of stellar
contamination is <5%.
0% 20%
0% 20%
Survey rate At least some data were
obtained on 61/99 of nights so far allocated to survey.
Over all nights with any data, the mean number of fields/night is 4.5.
Averaged over year, expect to get 7 fields for each completely clear night = 3000 z’s per night
Full survey requires about 100 clear dark nights, or all dark time for 1 year. In practice 2dFGRS uses about 1/3 AAT dark and will take 3 years
Cone diagram: all declinations
Cone diagram: 4-degree wedge
The big picture
2dFGRS
The 2dF galaxy + QSO redshift surveys
50180 galaxies
6824 QSOs
Redshift distributionMean redshift <z>=0.11;
almost all z<0.3.
N(z) still shows significant clustering.
(mean K-corrections)2 fit to
1/Vmax LF
Overall luminosity function
STY Schechter fit gives -1.2 (due to clustering? non-Schechter form?)
Small numbers at MB>-14.
Mean spectrum
PC1
PC2
PC3Early
Late
Early
Late
Spectral classification by PCA Apply Principal Component
analysis to spectra. PC1: emission lines correlate
with blue continuum. PC2: strength of emission
lines without continuum. PC3: strength of Balmer lines
w.r.t. other emission. Classify spectral types in
PC1-PC2 plane using sample of Kennicutt to set bounds.
Further work:– effect of spectro-photometric
errors;– self-classification algorithms;– calibration against spectral
models.
STY fit
1/Vmax LF
Early
Late
M*
All
LFs by spectral type
For 12,000 galaxies with PCA types, fit LFs by type.
1/Vmax LFs have less-steep faint ends than STY fits of Schechter functions.
From early to late types…
– M* gets fainter: -19.6 -18.9
gets steeper: -0.7 -1.7
Overall M* brighter than M* of any type; Schechter function not adequate fit.
Evidence for upturn at faint end of LF.
Overall STY Schechter fit
Sum of Schechter fits to each type
Early types (1,2)Late types (3,4,5)
Galaxy distribution by type
2D correlations
r
Model comparison - IFlattening depends on 0.6/b (gal = b mass)
infall
Fingers of God
Model comparison - II
Analyze into Legendre polynomials:
get from quadrupole-to-monopole ratio
-P2/P0 =
Linear
Damping
by fingers
of God
Projected correlations (r)
dxxrr )]([)( 2/122
APM w()
deprojection
works well to
r = 20 h-1 Mpc
(cosmic variance matters on larger scales)
The CDM clustering problemNon-monotonic scale-dependent bias
CDM CDM
Jenkins et al. 1998 ApJ 499, 20
b2 = g / m
Numerical galaxy
formation
Durham
Munich
Santa Cruz
Edinburgh
...
Antibias in LCDM
Benson et al.
astro-ph/9903343
Dark-matter haloes and bias
Moore et al:
= [ y3/2(1+y3/2) ]-1; y = r/rc
Correlations from smooth haloes
k
dk
kr
krksin)(2
PS++ mass function and NFW++ halo profile gives correct clustering
CDM
CDMLin
NLAPM
Halo occupations depend on mass
PS++ mass function wrong shape for cluster/group LF
Correct weighting of low-mass haloes predicts antibias
CDM
Summary 2dF survey status
– Over 50,000 redshifts (20% of survey)
– Expect 100,000 March 2000
– 250,000 March 2001 Preliminary results
– Luminosity functions by spectral type
– Correlations and redshift-space distortions Future issues
– Clustering on 100-Mpc scales
– Gaussian nature of density field
– Clustering by spectral type and luminosity
– Detailed tests of halo-based bias models
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