Extragalactic Astronomy with a deep NIR Large Area Survey - some thoughts about...
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some thoughts about...
Extragalactic Astronomy with
a deep NIR Large Area Survey
Vladimir Avila-Reese
Instituto de Astronomía, UNAM
The context
(only galaxies/ see other talks for QSO’s, clusters, lensing)
There are several competitive current and future
‘static’ NIR surveys with science drivers focused
on EG astronomy (UKIDSS www.ukidss.org/index.html ,VISTA
www.vista.ac.uk/index.html VIRMOS VDS www.oamp.fr/virmos/virmos_vvds.htm, etc.)
• NIR traces Ms, the galaxy stellar structure, hot dust, and
in combination with opt. bands, provide key information
about the stellar pop’s.
• High-z pop’s: e.g., already-in-place at z~1-3 L✴ E’s are revealed
in NIR surveys; SF-ing giant galaxies at z>4-5; growth of
structure and bias from z=3 to z=0 // but z is crucial!
What might be Sensitivity
the SASSIR z~0 z>0
strengths? -Low L, low SB pop’s -Sample completeness
(dIrr, BCD, dSph, LSB). down to low L’s &
SB’s (SMF up to z~4)
-Outer galaxy regions -Galaxy evolution
(structure, dust) (K~22 for a L✴ E at z=3)
Sky area (large statistics)
z~0 z>0
-Morphology (T, bars, -Clustering of different
rings, shells,...) & global pop’s at different z’s
structure of gal’s (SB
profiles, radii, B/D ratio, -Statistics of rare objects
CAS, lopsidness) -LSS studies: correlations
-Stellar scaling relations functions, BAO’s, voids &
-Environment corrtn’s superclusters (ISW)
Spectral range
z~0
-YJHK color-color traces z>0
- N I R c o l o r- c o l o r
SF activity & hot dust
diagram may select high-
-By combining with
z galaxy pop’s (gal. evol.).
opt. bands, full SP -Opt. bands important for
description, age-Z photometric z’s.
degeneracy broken
Sasir
The dashed line shows the Euclidian number
counts relation, which goes as 10-0.6K, i.e. the
position of a survey relative to the line is a relative
measure of the volume of space surveyed. This
Ultra Deep Survey?
illustrates, for example, that for surveys for brown
dwarfs 2MASS will detect many more than the
KPNO survey, and the LAS is an order of
magnitude bigger than 2MASS.
The local universe
NIR M/L ~ insensitive to o
Bell et al. 03 ApJS, 149, 249
galaxy or stellar type
NIR light ~ insensitive to
dust extinction
K-correction in K-band ~
insensitive to galaxy type
NIR traces well galaxy Ms &
stellar structure
BUT, NIR sky SB (K:14-15) >> but even in K-band, to estimate Ms, a color is needed!
outer SB of gal’s or even central
SB’s of low-L and LSB gal’s bar
‘ba
ryo
yon nic
ic g ’C
NIR bands are ideal for inferring ala
xie
DM
ha
s los
stellar (and eventually baryonic) stell
ar ga
laxie
galaxy properties and s
correlations, (i) to be compared
with models, and (ii) to
Baldry et al. 08, MNRAS
determine the ‘efficiency’ of
galaxy and star formationThe local universe
NIR M/L ~ insensitive to
o
Bell et al. 03 ApJS, 149, 249
galaxy or stellar type
NIR light ~ insensitive to
dust extinction
K-correction in K-band ~
insensitive to galaxy type
NIR traces well galaxy Ms &
stellar structure
BUT, NIR sky SB (K:14-15) >>
outer SB of gal’s or even central baryon and stellar fractions, a key constraint
SB’s of low-L and LSB gal’s to the galaxy formation models
bar
NIR bands are ideal for inferring
?
yon
ic g
stellar (and eventually baryonic) ala
xie
s
galaxy properties and
correlations, (i) to be compared
with models, and (ii) to
Baldry et al. 08, MNRAS
determine the ‘efficiency’ of
galaxy and star formationovered affect- from Fig. 2, it is assumed that any bias induced by this cut
Galaxy L and Ms functions
hat, for Pet- will be negligible.
der,
d when in- By estimating the area in this way, the assumption isK-band galaxies from UKIDSS LAS 5
2 A. J. Smith, J. Loveday & N. J. G. Cross
ntly brighter that all SDSS target galaxies would be detected in the LAS,
ture fluxes, the ellipticity and the seeing, all made available
icro-stepped,
1) Table 1. Sample sizesinofpart
if that the
K-bandWSA ofgalaxy
the sky
(theluminosity
pipeline has doesbeen
functions. surveyed.
not measure 2 DATA If this is not the
the half-light
this problem case, it will have two effects: (1) particular
radius). types used
All of the galaxies of galaxies
in this sample are drawn from the
) Given that will be underrepresented in the sample main galaxy (those samplewithin
of Data Release
the 5 of the Sloan Digital
effect of peculiar velocities:
et Sky Survey (SDSS; Adelman-McCarthy et al. 2007), from
,rs we have re-
Paper
SDSS2.4
Loveday (2000)
completenessNumber of galaxies in sample
Surface brightness limits but outside
345
thethe
which limitsopticalfor the LAS)
photometry and spectroscopic redshifts K r
-Petrosian K mag and r limits--> SB fainter than 20.4m/
in the UKIDSS Large Area Survey,
Table 2 shows
investigation
23 mag
the various
of surface
P
brightnesslimits
while leaving detailed
arcsec−2 , so we assume the limit in SDSS surface
on theand
completeness sample.
the very
spectroscopic redshifts
☐
Petrosian magnitudes brighter
(zConf > 0.8) and with de-reddened
effect than
of peculiar
r = 17.6velocities, which are not taken into account.
is 391 052.
brightness
faint-end of the luminosity function to future
adds no further incompleteness
work. (in principle) ofOfbuilding
to the
these,such
sample,
384a617 Note that this
are spectroscopically limitaswould
classified need to be relaxed in order to
galaxies.
1 INTRODUCTION
once the magnitudeThe advantages
limits in r and K and the surface census
bright-overed affect- from Fig. 2, it is assumed that any bias induced by this cut
Galaxy L and Ms functions
hat, for Pet- will be negligible.
der,
d when in- By estimating the area in this way, the assumption isK-band galaxies from UKIDSS LAS 5
2 A. J. Smith, J. Loveday & N. J. G. Cross
ntly brighter that all SDSS target galaxies would be detected in the LAS,
ture fluxes, the ellipticity and the seeing, all made available
icro-stepped,
1) Table 1. Sample sizesinofpart
if that the
K-bandWSA ofgalaxy
the sky
(theluminosity
pipeline has doesbeen
functions. surveyed.
not measure 2 DATA If this is not the
the half-light
this problem case, it will have two effects: (1) particular
radius). types used
All of the galaxies of galaxies
in this sample are drawn from the
) Given that will be underrepresented in the sample main galaxy (those samplewithin
of Data Release
the 5 of the Sloan Digital
effect of peculiar velocities:
et Sky Survey (SDSS; Adelman-McCarthy et al. 2007), from
,rs we have re-
Paper
SDSS2.4
Loveday (2000)
completenessNumber of galaxies in sample
Surface brightness limits but outside
345
thethe
which limitsopticalfor the LAS)
photometry and spectroscopic redshifts K µe,K - 21 mag arcsec−2
ing good agreement
The with previous results. Possible improvements a are discussed e ! targeted for spectroscopy in the SDSS
µthat
ce -fainter than K=16, deviates from the Euclidean slope
discussion about possible low-surface
SDSS brightness
main incomplete-
galaxy sample hasnumber limit of of
galaxies
could be implemented when extending this analysis LAS. galaxy sample. But firstµthe
to the full main e,r size of this sample must - 24.5 mag arcsec−2
effectness in 2MASS
of peculiar (Andreon24.5 2002),
velocities, magwhich which
arcsec are−2 would
not affect
taken
(Strauss etthe
intoal.low-
account.
2002). This limit is taken
e, -sky brightness in K + LAS depth--> r
-Petrosian K mag and r limits--> SB fainter than 20.4m/
in the UKIDSS Large Area Survey,
Table 2 shows
investigation
23 mag
the various
of surface
P
brightnesslimits
while leaving detailed
arcsec−2 , so we assume the limit in SDSS surface
on theand
completeness sample.
the very
spectroscopic redshifts
☐
Petrosian magnitudes brighter
(zConf > 0.8) and with de-reddened
effect than
of peculiar
r = 17.6velocities, which are not taken into account.
is 391 052.
brightness
faint-end of the luminosity function to future
adds no further incompleteness
work. (in principle) ofOfbuilding
to the
these,such
sample,
384a617 Note that this
are spectroscopically limitaswould
classified need to be relaxed in order to
galaxies.
1 INTRODUCTION
once the magnitudeThe advantages
limits in r and K and the surface census
bright-P = 0.18, and (3) making the LF 0.22 mag brighter in mag-
K-band galaxies from UKIDSS LAS 9
nitude, to convert from 0.1 r to r. Schechter function parame-
?
ters are M ∗ − 5 log h = −20.32 ± 0.04, α = −0.87 ± 0.05 and
φ∗ = (0.0216 ± 0.0010)h3 Mpc−3 .
red
K-band galaxies from UKIDSS LAS 13
Intrinsic or incompleteness? Detection of red-
Figure 19. K-band (left) and r-band LFs for red and blue galax-
f
Figure
Figure 12. K-band luminosity function for the whole sam-
12. K-band luminosity function for the whole sam- core low-Lthe
ies, showing gal’s is LF
total affected
as well. by the mag, r, and SB limits
e ple, with a compendium of published results from observations
a
e
ple, with a compendium
or semi-analytic
or semi-analytic
Schechter function
models.
models.
of Only
fit, Only
published
i.e., Mthe
results
the filled pointsfrom observations
are used in the
filled points are used in the
K − 5 log h < −20; the unfilled
faint Stellar mass function
- Schechter
points function
Figure are likelyBBD
17. fit,
to i.e.,from
suffer
for MK
red some− 5incompleteness
galaxies, h 2.35.
d pointsbrightness
likelyorto
red,
arebest-fitting low-luminosity
suffer from some galaxies. Schechter
incompleteness function pa- − ing off of the luminosity–surface brightness relation at high
The ∗
Cho" loniewski function, estimatedof low-surface
using M K
t rameters
brightness or are
red, − 5 log h = −23.17
Mlow-luminosity ± 0.04,Schechter
galaxies. α = −0.81function
± 0.04 andpa- luminosities, suggesting that this division reflects a property
?
5 log h < −20 and µe,abs
∗ = (0.0176 ± 0.0009)h
< 19, is shown by the red dotted
3 Mpc−3 .
f φ ∗ − 5 log hof=the −23.17 ± 0.04, of the underlying population. Moreover, the Cho"loniewski
rameters are M
contours. Parameters fit are M ∗ −α5 = log−0.81 ± 0.04mag,
h = −22.88 and
φ∗ =α(0.0176 ∗ = 0.0121h
= 0.17,±φ0.0009)h 3 Mpc −3 .−3
3 Mpc , µ∗e,abs = 17.09 mag arcsec−2 , function appears to fit the blue BBD much better than it fits
0.570 mag arcsec−2 the BBD for the whole sample. However, we caution that the
σµe,abs =
Equation (1) can be writtenand as β = −0.012.
lack of red-core galaxies with MK − 5 log h > −20 could be
“ r ”2
Equation (1) can be written a symptom of the incompleteness identified in Fig. 10, while
.asfunction. Only the filled points
P
µe " K + 2.5
Figure
log
20.
2π
Stellar
Figs. 17–19 show 2 mass
the K-band BBD and K- and
(15)are
r-band Figure 21. ofStellar
the lack suchmass function,
galaxies using
with various
µe,abs 19.5 mag arcsec−2
> mass-to-light rare
“ ”
?
LFs used in the Schechter
split by the SDSS rP rest-frame
2 function fit, i.e.,
u−r stellar mass greater than
−2 PSF colour. The space
ratios and the default kcorrect mass, which is derived from the
could be due to the low-surface brightness limit for de Vau-
µe " K +102.5 hlog M
For K=16 9.5 and
−2 µ = 19.5 . points are likely
2π" ;e the unfilled
mag arcsec , this to
corresponds (15)
to
suffer from some template fit to the input (ugriz) absolute magnitudes. Masses
density
a limit is Petrosianof2by
inestimated
incompleteness summing
radius of 4.0
low-surface the weights
arcsec,
brightness of galaxies
considerably
galaxies. Masses lesswith
calcu- couleursfrom
calculated profile galaxies.
the K-band kcorrect mass-to-light ratios have
− rthe
For uK=16
than >and
lated 62.35µe or
from
arcsecthe u − intrinsic
K-band
=limit
19.5 rmag
< 2.35
kcorrectto for
arcsec red
−2data; and
mass-to-light
the , −2this only blue
ratios galaxies
have
for surface
corresponds been
to The LFs
been increased show
by 0.1 dex. a sharp division, with red-core galax-
increased
respectively, by 0.1
with than dex.
jackknifeSchechter function parameters are found
brightness
a limit fainter
intoPetrosian
be log(M∗ hradius
2 /M ) = oferrors
20.38 mag
10.44 ±
estimated
4.0 arcsec
arcsec, doessubsequently.
the 6 arcsec
0.02, α considerably
= −1.02 ± 0.04 less
ies more abundant than blue-core galaxies by an order of
largeThe
radiusBBD for dominate.
limit "
red galaxies, excluding outliers, showsand no magnitude
masses derivedat high
from theluminosity
K-band M/L (and vice
ratios versa at
compared low lumi-
with
than the 6φ arcsec
∗ = (0.0112limit intrinsic
± 0.0007)h 3 Mpcto the
−3
data;
. Stellar onlybased
masses for surface
on other
evidence
Fig.
IMFs 9ofalso
a correlation
have shows between
the best-fitting
been reduced luminosity
Cho"
for comparison −2 lwith our and
oniewski fit tosurface
results, the
based nosity),
the masses and with
derived fromthethebright
opticalend of the
bands. The LF around
precise cause 0.8 mag
brightness fainter than 20.38 mag arcsec does the 6 arcsec• A NIR survey with both a very large area and high sensitivity (depth of
K~21)* will allow to reconstruct the local NIR bivariate L/SB function (i)
down to the dwarf galaxy pop and including LSB galaxies, (ii) with
enough statistics for determining accurately the LF bright end (rare gal’s)
and for (iii) allowing to separate the LF function by galaxy types, colors,
and environments (1200 nights for 3E4deg2 at J=20, K=18.4 in a 4m telescope;
UKIDSS-LAS will be for only 4E3deg2)
•Redshifts are necessary; for local galaxies
(zThe dwarf galaxy population (building blocks)
from Vaduvescu PhD thesis
•What is the abundance and the LF faint-end of different types of dwarf gal’s?
What is the minimum Ms of galaxies?
•How is the distribution of dwarfs in clusters, groups, filaments and voids?
•How is the stellar structure of dIrr’s, BCDs and dS’s?
NIR: mass, structure. Deep, LA surveys are necessary to explore
dwarfs in the local volume and in different environments.Some results from Vaduvescu thesis; Vaduvescu, Richer & McCall 06, AJ, 131
SPM observations. Careful photometric analysis. NIR SB profiles: sech law.
dE and dSph are probably old
fossils (or formed by tidal
destruction?)
What about dIrr, BCD, dS?
BCD are dIrr in bursting phase
and dE are fading dIrr?
Key constraints to the
kinematics! LCDM model (see
Valenzuela’s talk)Baryonic quantities, the ultimate goal
To fully understand galaxy
formation & evolution, we need
to constrain stars, gas, and dust
Synergy of NIR surveys Baryonic
with HI surveys --> the
real mass backbone of
Stellar
galaxiesDisk galaxy scaling relations 4.2. The stellar scaling relations
The main changes as passing from the baryo
stellar
Avila-Reese, Zavala, Firmani, Hernandez-Toledo, AJ, in scaling correlations
press; (Zavala, A-R,H-T,are the 03,
Firmani decrease
A&A) of
and intrinsic scatter in the Vm -M correlations.
2.6
B 2.6
Kters of the R-M and R-Vm correlations also
2.4 2.4 but the Very
significances reduced
of the number
differences are very
More interesting,of the‘useful’ galaxies
(weak) anticorrelation be
2.2 2.2 residuals of the baryonic Vm -Mbar and Rbar -M
2 2 The TF relations
relations tends to dissapear in the stellar case,
lated to other of our results, namely that the
1.8 sl=0.314 (2.77) 1.8 sl=0.261
disk surface
(3.67) •The bar TFR is steeper than the
density) is a third parameter in
σintr=0.063 σintr=0.049
onic TFR st one.
but not anymore in the stellar one.
1.6 1.6
10 differences
•Intrinsic
are
scatters: change from bar to st
9 10 11 9 11
and to K-bandto
related the gas (or stellar) m
cases
tion of galaxies, •Crucialshowing that the
for constraining modelsmass infa
histories vary systematically
16 among galaxies.
Avila-Reese et al.
variations consistent with galaxy models bas
0
2.6
St 2.6
Bar
2.4 2.4 ΛCDM framework?
Let us first discuss in more detail the chan
?
-0.2
2.2 2.2 slope of the Vm -M relation. If the stellar m
2 2 tion, fs = 1 − fg , depends on Ms as fs ∝ M
Mbar = Ms /fs ∝ -0.4 Ms 1−β . Therefore,
f
M from Vm s
1.8 sl=0.274 (3.40) 1.8 sl=0.306 (3.00) = s
σintr=0.045 one passes
σintr=0.051 to V m ∝ M s . In the left pan
α(1−β)M + M s g
1.6 1.6 7, fs vs Ms is plotted -0.6
for our galaxy sample.
9 10 11 9 10 11
with a high scatter, fs9 correlates 10 11 with
1.5 M 2 2.5rou
s
filled: HSB empty: LSB €
❍: red ∆: blue fs = 0.65(Ms /1010M" )0.13 ,
Fig. 7.— Stellar fraction fs vs Ms , Σs,0 , and (B − K). Solid and empty sy
galaxies are represented with circles, while blue galaxies with triangles. The solid
are from models by FA00.The radius-M (-L) relations
1 1
•Scattered and segregated by
SB, and less by color
0.5 0.5
•Slopes around 0.3, but for the
B band case, 0.44. ☛
0 0
sl=0.441 sl=0.285
σintr=0.19 σintr=0.20
9 10 11 9 10 11
A wide range in SB is
crucial for this relation.
Most of previous similar
1 1 samples did not include
LSB gal’s
0.5 0.5
Scaling relations are fossils of:
cosmological initial conditions
0
sl=0.310 0
sl=0.322
+ gal. evolution + SP evolution.
σintr=0.19 σintr=0.20
Observational constraints
9 10 11 9 10 11
(including early-types) are yet
filled: HSB empty: LSB
very limited. Even scatters are
❍: red ∆: blue highly informativeTrends among the residuals
✤In the bar case there is a (weak)
anti-correlation: sl=-0.15. The level
-0.5 baryonic of dependence of Vm on the disk
surface density decreases as SB
decreases (the halo becomes
dominant). Could MOND explain this?
✤The anti-corr’n disappears in the
st and L cases. Why? (A SF effect)
stellar
✤The B-band TFR residuals
increase as the gal’s are deviated
to the redder side (Kannappan+ 02).
For a given LK, the bluer the color,
K band the larger LB.
✤The bar TFR residuals are larger
for gal’s that end with higher st.
fractions (formed earlier and/or
had an efficient SF)
B band
The scaling rel’s change for luminous,
stellar, and baryonic quantities: clues to
models of gal. formation and cosmologyThe stellar structure of galaxies in the NIR
•NIR morphology is different to the optical ones (de Blok, Puerari,...):
morphological reclassification. B/D ratio and dust corrections
•NIR bar and bulge statistics (z~0 and z>0 and as a function of
environment): secular evolution of galaxies & dynamical history (Hernandez-Toledo+)
NIR •NIR CAS parameters &
•not floculent arms lopsideness statistics:
•a clear bar galaxy assembly history,
dark matter halo structure
and sub-structure, etc.
(Hernandez-Toledo+,
Valenzuela+)
•Outer stellar disks
structure -cutoff?, warps
•Color gradients: inside
out formation, secular mass
redistribution, dust gradient?
NGC 253
•LSB galaxy stellar
structureCB07 models
MNRAS, 384,930
Colours of SF-ing galaxies are poorly understood.
5800 SDSS/UKIDSS late-type local galaxies
-More strongly SF-ing galaxies have redder H-K color.
-The more dust attenuation, the redder H-K
-TP-AGB stars dominate the H & K bands following a
SF burst.
-TP-AGB stars are the main source of dust in nuclear
region of the galaxy
SFing
non-SFing
-Models: g-r vs Y-K could break divided by age divided by Z
the age-Z degeneracy.
-Data: marginally. Y-K is metal
sensitive (see also Galay+02)NIR photometry is very useful for understanding the
physics of interacting galaxies (several of their
underlaying properties are distorted in optical bands): a
deep and extensive NIR catalogue of these galaxies is
desirable
NIR colors as probes of interacting galaxies
(Geller et al. 06, AJ, 132, 2243)
interacting isolated control sample
Hot dust could be a new tracer of SF in
compact dust-enshrouded bursts. The
z=0 SFRD could be underestimatedThe z>0 universe
A large area survey of well-defined mass-tracing objects (e.g.,
galaxies in the NIR) in a given z-range is useful for several LSS and
structure formation problems.
--Baryonic Acoustic Oscillations (e.g. SDSS-III): dA at z=0.3, 0.6 & 2.5
~150 Mpc, z=0.3
Used to measure dark energy
propertiesImprint of superstructures in the CMBR due to
the ‘late-time’ Integrated Sach-Wolfe (ISW) effect
Accelerated expansion due to dark energy (z
depends on DE gravitational z--> secondary anysotropies in the CMBR:
cross-correlate with LSS at the z of the effect.
Rudnick+07ApJ, 671 The ISW signal peaks at l~20 and z=0.5: superstructures
of ~4deg or 100 Mpc/h
Granett+ 0805.3695 (LRG in SDSS)
1.4Ghz radio sources from NVSS
140 Mpc hole @ the
CMBR cold spot
Measurement of DE parameters
Test of cosmological modelsEvolution of the K-band LF (UKIDSS-UDS)
For high-z studies,
z determination is
demandatory
Cirasuolo + 08, 08043471
Downsizing:
bright/massive gal’s are
assembled at high z (1-3)
and then passively
evolve, while the
formation of less L gal’s is
progressively shifted to
lower z’sModels vs observations: a great challenge
et al. (2001) in Figure 1, we estimate that the effective sky 2001), there is evidence of clustering, particularly a dip around
coverage of the parent sample is 650 deg2, with an error of z p 0.04 and a sharp peak around z p 0.06. Therefore, the
Evolution of the galaxy pair fraction (merging rate)
∼5%. We ignore this error because it is much smaller than other fluctuations of the LF of paired galaxies around the smooth
errors. Given our pair selection criteria, both components of a Schechter function (e.g., the excess at MK p !22.75) are pos-
pair have the same Vmax determined by the Ks magnitude of the sibly1094due to this effect. RAWAT ET AL. Vol. 681
The stellar masses, corresponding to the absolute eterized magnitude by their redshift flag). So in cases in which the neighbor
bins of the LF, are also listed in Table 1. Following has Kochanek
Local pair fraction as a function
a VVDS redshift flag 2 (75% confidence) or worse, there is a
et al. (2001) and Cole et al. (2001), we first translate themuch greater risk of the pair being designated as having discor-
isophotal
dant redshifts. In addition to this, one also has to allow for the
Ks magnitude to the “total” Ks magnitude (dK s p 0.2 fact
of L or M in K-band (2MASS)
assume the conversion factor of Mstar /L K p 1.32 M, shift
mag), thenof the pairs using redshifts from the other two red-
that some
/L catalogs
whichcan also be erroneously counted as discordant (for
the ,same reason as above). Such pairs account for "15/45 discor-
is
Thefor a Salpeter
Astrophysical Journal,initial mass2008
681:1089Y1098, function
July 10 (Cole et al. 2001). The
dant redshift pairs in the z band. This can significantly swing the
Xu+04, ApJ 603
# 2008. The American Astronomical Society. All rights reserved. Printed in U.S.A.
differential pair fraction function (Table 1 and Fig. 2) isofcal-
number pairs with discordant redshifts. If we discard these
15 discordant cases and recalculate the contamination rate, we
culated using the Schechter functions of the paired get galaxies
60% # 14% as the contamination rate, which is in much bet-
and of 2MASS galaxies (Kochanek et al. 2001) interthe lumi-with the contamination rate of 42% # 6:3% that
agreement
we have obtained using our statistically estimated foreground/
nosity/mass rangeTOWARD coveredAbyROBUST the paired ESTIMATEgalaxyOF sample,
THE with
MERGER
background
RATE EVOLUTION
contamination.
the error estimated from the quadratic sum of the error USING NEAR-IR PHOTOMETRY
In a of the our contamination calculation is robust, and the
nutshell,
LF of paired galaxiesA. and Rawat, 1, 2
its deviation
Francois Hammer, 2
from Ajit contamination
the K. Kembhavi,1rate
Schechter andcompares
Hectorwell with2 the contamination rate
Flores
reported in literature,
Received 2007 June 19; accepted 2008 March 31
as well as with the subsample of our major
function. The last bin is not included because therepairs is where
onlyweahave spectroscopic redshifts for both members of
single galaxy in the bin, and therefore the value is toothe pair. Also, as a result of our eagerness to throw out prospec-
uncertain.
tive pairs as having discordant redshifts due to spurious redshift
ABSTRACT
Although error bars are substantial, some general trends canin some cases, we are going to end up with an es-
be identified
We use solid:
in Figure
K-band
a combination of deep, high angular resolution imaging
2. Unlike the LF ofthe2MASS
determination
data
galaxies,
timate of fromfraction
merger the CDFS
that is(HST/ACS GOODS
a bit too low, and thussurvey)
it should
the LFFig. 0:2 ! dashed:
and ground-based
of6.—Histogram
paired
z ! 1:2. galaxies
of We
z-band
near-IR
$ z has
(z select
host
Ks images
)/(1 þ za negative
galaxies
neigh solely
) for
host
to derive
the 65on slope
the
major basis
pairs
evolution
in
be of
the faint
of their
where
the
treated
J-bandend,
galaxy
as a major
lower merger
limit. rate in the redshift range
rest-frame absolute magnitude, which is a good
% redshift, 5.3. Source Blendin g and
/(1 þ z) 3:43#0:49
Photometric Completeness
suggesting
both tracer
that galaxies with
membersof the
have stellar mass.
a spectroscopic We
redshift. find
Note
!z/(1 þ z) % 0:006 as seen in the figure. Most
low stellar mass are less likely
steep
that only 20 pairs have $0:006
evolution with
other pairs have !z/(1 þ z) much
2:18#0:18
with the merger rate for optically
largerselected
than 0.006pairs
so that and /(1
they are þthe
out of z) frame. for pairs selected in the near-IR.
A major Ourbias result is unlikely
when studying close to pairs
be affected by may
of objects lumi-be
nosity evolution that is relatively modest when using rest-frame causedJ-band selection.
by the fact that sourcesTheare apparently
blended when more rapid
their evo-
separation
lution that we find in the visible TABLE 2 is likely caused by biases is comparable
relating to to the
incompletenessPSF. It particularly
and spatial affects ground-based
resolution affectingKs
00
Inthe
Figure 6 many objects
ground-based near-IR have !z/(1 þ
photometry, z) much larger than
underestimating images because
pair counts at higher the K s PSF ("0.5 ) is much larger
redshifts in the near-IR. The major than the HST
0.006 (so Paremeters
much of Schechter out ofatFunction Ks LF
of 6). 00
Fig. 2.—Ks-band LFs and stellar mass functions and differential pair fraction merger ratesowas
that most
$5.6oftimes
them are
higher the
z$frame
1:2inthan
Fig. at the opticalepoch.
current PSF ("0.1 ). This
Overall, 41% is illustrated
; (0:5 Gyr/!) in Figure
of all7,galaxies
where we
The members of such pairsof are Paired
treated as Galaxies
having ‘‘discordant red- have plotted the angular separation between the main galaxy
(right coordinates). The lines are Schechter functions of the LF of paired with MJ ! %19:5 have undergone a major merger in the last $8 Gyr, where ! is the merger timescale. Interestingly,
shifts’’ and are essentially foreground/background superpositions. and neighbors identified in the z filter against the z magnitude
we findplot,
no we
effect
canon the 5derived h major merger rate
(fdue/h3to
) theError
presence of thesegregated
large-scale structure at z ¼bins.
0:735 in the
galaxies (solid ), of the LF of 2MASS galaxies by Kochanek et al. (2001; From a this Error ∗ !derive
Mthen logthe Error
fraction log
of pairs that 0are of the neighbor, into three redshift A neighbor
CDFS.
actually foreground/background superpositions (i.e., the contami- here is identified as any galaxy within 5 h100 kpc % r % 20 h$1
$1
dotted ), and of the LF of 2MASS galaxies by Cole et al. (2001; dashed ). The 100
0.30
nation rate).0.56
This
Subject headingg !22.55
contamination rate is 0.25
found to be !3.46
"69%
s: galaxies: evolution — galaxies: formation # 0.13—
kpc of the primaryinteractions
galaxies: galaxy, regardless of its magnitude.
— galaxies: statisticsThe re-
shaded area presents the differential pair fractions and the errors. 13%. On first sight this might appear larger than the contamina- sultant list of 1085 neighbors includes major as well as minor
tion rate of 42% # 6:3% that we have obtained using our statisti- neighbors and constitutes the pool from which the major pairs
cally estimated foreground/background contamination (although are identified. In Figure 7 the open circles denote neighbors that
note the large error
1. bars since we are dealing with small number
INTRODUCTION have Ks magnitudes,
technique whereas the
of pair counting. green 2
Section crosses denote
lists the dataneigh-
sets we have
statistics here). However, we checked the spectra of the pairs bors that do not have Ks magnitude. As is shown in Figure 7,
used in this work and briefly explains the methodology that we
Galaxy
havingmergers are believed
discordant to be the It
redshifts ourselves. chief
turnsmechanism driv-
out that in many there are a large number ("43%) of such neighbors that do not
cases,evolution
the redshift determination can be quite poor indeed, espe- have employed in this paper for deriving the merger
have Ks -band magnitudes. This has the consequence of reduc- rate. Section 3
ing galaxy within the hierarchical framework. Although
cially details the sample selection criterion employed by us and the
mergers areinrare
the at
low-exposure
the current and low-resolution
epoch, VVDSframework
the hierarchical (as param- ing the pool of neighbors from which the major pairs are identified
possible biases in our sample. Section 4 explains the details of
predicts that the merger rate must have been higher at earlier
the photometry performed by us in the Ks filter. Section 5 explains
epochs. Despite its importance in understanding galaxy evolu-
in detail how we identify major pairs of galaxies, along with cor-
The merging rate history is an
tion, the quantification of the galaxy major merger rate and its
recting for possible contamination and incompleteness issues.
evolution with redshift is still an ill-constrained and hotly de-
bated issue. Patton et al. (1997) have derived a clear increase in Section 6 compares the differences in pairs identified in the vis-
ible and the near-IR. Section 7 deals with the calculation of the
the merger fraction with redshift until z $ 0:33 with a power-law
important constrain to models. index of 2:8 # 0:9. However, extension of this work to higher
redshifts has been riddled with controversy. Le Fevre et al. (2000)
reported steep evolution of the major merger rate until z $ 1:0,
major merger rate from our identified pairs and its evolution with
redshift. We conclude by discussing the implications of our re-
sults obtained in this paper in Section 8. We adopt a cosmology
High ang. resolution needed
with H0 ¼ 70 km s%1 Mpc%1, !M ¼ 0:3, and !" ¼ 0:7.
with a power-law index of 3:2 # 0:6 using pair-counting in the
optical band for identifying the merger candidates. Bundy et al.
2. THE DATA
(2004) reported a much more modest evolution of merger rate
using K 0 -band images for identifying major merger candidates. We have used version v1.0 of the reduced, calibrated images of
Lin et al. (2004) also reported very weak evolution in the merger the Chandra Deep FieldYSouth (CDFS) acquired with HST/ACS
rates using the DEEP2 redshift survey. Bell et al. (2006) reported as part of the GOODS survey (Giavalisco et al. 2004). The
a fairly rapid evolution in merger fraction of massive galaxies SExtractor ( Bertin & Arnouts 1996) based version r1.1 of theOn the evolution of clustering of 24-µm-selected galaxies
M. Magliocchetti,1,2,3! M. Cirasuolo,4 R. J. McLure,4 J. S. Dunlop,4
O. Almaini,5 S. Foucaud,5 G. De Zotti,3,6 C. Simpson7 and K. Sekiguchi8
1 INAF, Osservatorio Astronomico di Trieste, Via Tiepolo 11, 34100 Trieste, Italy
2 ESO, Karl-Schwarzschild-Str.2, D-85748 Garching, Germany
1134 M. Magliocchetti et al.
3 SISSA, Via Beirut 4, 34014 Trieste, Italy
1138 M. Magliocchetti et al.
intermedium z high z intermedium z
4 SUPA, Scottish Universities Physics Alliance, Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ
5 School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD
high z
6 INAF, Osservatorio Astronomico di Padova, Vicolo dell’Osservatorio 5, 35122 Padova, Italy
7 Astrophysics Research Institute, Liverpool John Moores University, Twelve Quays House, Egerton Wharf, Birkenhead CH41 1LD
8 National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588, Japan
Accepted 2007 October 16. Received 2007 October 9; in original form 2007 June 29
Figure 5. Angular correlation function w(θ) for the low-z (left-hand panel) and high-z (right-hand panel) samples. The solid (blue) curves represent the best
HON fits to the data obtained under the
A Bassumption
S T R A C T that the distribution of galaxies within their dark matter haloes mirrors that of the dark matter (chosen to
be described by a NFW profile, cf. Section 4), while
This paper the dashed
investigates the (green) curves
clustering are theofbest
properties fits obtained
a complete forof
sample a steeper galaxy profile, ρ ∝ r−3 . The long-short
1041 24-µm-selected
dashed (cyan) curves correspond to the best one-parameter 2
sources brighter than fits
F 24obtained by setting in equation (5) α = 0 and N 0 =the
µm= 400 µJy in the overlapping region between
1. Spitzer
The negative
Wide-w(θ ) data points in the χ
analysis of the low-z sample have been treated
Area as in Extragalactic
Infrared Section 3.1 (see text forand
(SWIRE) details).
UKIRT Infrared Deep Sky Survey (UKIDSS) Ultra
Deep Survey (UDS) surveys. With the help of photometric redshift determinations we have
Figure 3. Sky distribution of UDS-SWIRE, F 24 µm ! 400 µJy sources (small dots). The filled (red) circles in the left-hand concentrated
panel illustrate the 350 the two interval ranges z = [0.6–1.2] (low-z sample) and z ! 1.6 (high-z sam-
on objects
included in the redshift interval z = [0.6–1.2], while those in the right-hand panel represent the 210 sources with either z > 1.6 or no Figure
optical5.orAngular
near-IR correlation function w(θ) for the low-z (left-hand panel) and high-z (right-hand panel) samples. The solid (blue) curves represent the best
the data, as small-scale measurements ple) asof it isthefits
intwo-point
these regions correlation
were weassumption
expect the mid-infrared (IR) population tomatter
be dominated
identification.
function prefer smoother profiles by such intense
HON
as NFW
be described
to the data
dust-enshrouded
by a NFW
obtained
or ρ ∝ r activity −2.5
profile,
under the
cf. Section 4), while
that the
the
distribution of galaxies
. How-such as star formation and black hole accretion.
dashed (green) curves are
using
the best fits
halo
within their dark
obtained
ocupation
for a steeper
model
haloes mirrors that of the dark matter (chosen to
Inves-
galaxy profile, ρ ∝ r−3 . The long-short
dashed (cyan) curves correspond to the best one-parameter fits obtained by setting in equation (5) α = 0 and N 0 = 1. The negative w(θ ) data points in the χ 2
of galaxies undergoing intense star formation which we expect ever, (cf. atgeometry
very low redshifts
of UDS, and corresponds to tigations
it is reasonable
about The ofthethe
to expect
ofclustering
halfanalysis angular
maximum
of the low-z theof correlation
majority
BzK
sample been of
have galaxies
function produce an amplitude A ∼ 0.010 for the high-z
treated as in Section 3.1 (see text for details).
earlier in this section and also in Fig. 2) to dominate our sample. dark matterscale probed
haloes by thetosurvey.
be virialized sample
and
(Hartley and Aet
therefore 0.0055
∼ al., be in for the low-z
to prep.).
reasonably Galaxies one. The corresponding correlation lengths are r0 =
The low-z sample instead contains 350 sources. Their sky dis- Fig. 4 presents our results for the two15.9 low-z+2.9
(left-hand
and panel)+1.5
8.5−1.8 and Mpc,e.g. showing that the high-z population is more strongly clustered. Com-
tribution is represented by the filled (red) circles on the left-hand described high-z(at least beyond
(right-hand thewhile
panel) samples, veryTable
insmall
−3.4the
1the scales,
UDS
reports
data, the have
w(θ see
)
as small-scale been Bukert
selected
measurements of the totwo-point correlation
side of Fig. 3. The average redshift of the sample is found to1995) be values
by as a function profiles.
NFW-like of angular scale
Two inparisons
both cases.
options with
The are physical
error bars
instead models
possible forsuch the asformation
at < zNFW and evolution of large-scale structure reveal
lie in the
function redshift
prefer smoother rangeprofiles1.4 < or ρ ∝ r−2.5 . How-
of massive (M " 10 M# ) haloes,
13
!z" = 0.79, its median zmed = 0.84 and the comoving number den- show Poisson estimates for the points. Since thatthe thedistribution
high-z
ever, at verysources
is clus-
low redshifts are exclusively
it is reasonableassociated
to expect thewithmajority very
sity of these sources is n̄ G = (9.9 ± 1.0) × 10−5 Mpc−3 . Evensuch in high
tered,redshifts.
these estimatesThe first one
only provide a lower islimit
that
2.5 to andgalaxies
the can
uncertainties. still
be do trace
characterised the as
this case, the number density is in excellent agreement with underlying
comparable dark mattertoofthosehaloeswhich locally and
to be virialized hosttherefore
groups-to-clusters
be to reasonablyof galaxies and are very common
the However,distribution
it can be shown ofthatthe
overdark matter
the considered
withineither within
range
described
such (rare)(at their
angu-
star-forming haloes,
(sBzK) and
structures. Conversely, lower zsee
least beyond the very or
small scales, e.g. Bukert
galaxies are found to reside in smaller haloes
findings of Caputi et al. (2007) for their z ∼ 1 sources with ν Lν ! lar scales this estimate is close to those obtained from bootstrap
11.3 it is the dark matter itself which
resampling (e.g. Willumsen, Freudling (M doespassive not
1995) 12follow
by NFW-like
(pBzK)
10highMredshifts. NFW-like
profiles.
by the Twopro-
Daddi optionset are
al.instead possible at
10 L& , where ν Lν was calculated as indicated before. The most & Da Costa
min ∼
issue such
1997).
# ) In and The to be very
first one rareis thatingalaxies
such systems.
still do trace Onthethe other hand, mid-IR photometry
relevant properties for the high-z and low-z samples are summarized files. TheParticular
second option
attention was is instead
devoted to the that
shows (2004) ofgalaxies
that
close pairs.are
underlying criteria.
the low-z simply
In
and this more
redshift
of the dark matter within their haloes, andobjects and probe a similar mix-
high-z samples include similar
in Table 2. fact, the points on the top left-hand corners of both w(θ)distribution
esti-
radiallymatesconcentrated than scales
correspond to angular the dominant
turerange
close toof isdark
theitactive the
5.4-arcsec matter
it isdark
galactic
the matter
reso- counterpart.
itself which
nucleus
passive (AGN) does not
galaxies andfollow NFW-like pro-
star-forming
that galaxies. While recent studies have
files. The second option is instead that galaxies are simply more
Whatever the favourite choice, onedetermined
lution of the 24-µm Spitzer channel and thing
therefore is
could
areradially
foundclear;
be
toonbe
affected
a concentrated
strong subhalo
evolution
thethanmore
scales,
of the
the dominant
24-µm
highly luminosity function between z ∼ 2 and 0, they
dark matter counterpart.
3 C L U S T E R I N G P R O P E RT I E S by source confusion. However, since optical and near-IR images for
24-µm-selected
these sources havegalaxies at redshifts
a much better cannot
resolution clustered.
(∼0.8 !
zWhatever
provide 0.6the
arcsec), weare
Thecan more
information
favouriteclustering strongly
on
choice, the
one physical
of
thingaisset nature of such
ofon subhalo
clear; an evolution. Our clustering results
scales,
radiallyuseconcentrated
this information and than their
consider instead
low-redshift
as ‘good’ indicate thatofbe
all thosecounterparts.
pairs24-µm-selected made thisdirectly
galaxies is due
at Such tolinked
redshifts the ! 0.6 are of
a zpresence moredifferent
stronglypopulations of objects inhabiting
3.1 The angular correlation function galaxies
galaxies which are identified in the Subaru/UDSradially
can
images, concentrated
while we than their low-redshift
tocounterparts. Such ato be exclusively associated with
strong regard
concentration is indicative different structures, as active systems halos at z # 1.5 are found
The angular two-point correlation function w(θ) gives the excess as potentially spurious those madeof ofthea strong
galaxiesmass
strong without interaction
ofsuch the
concentration dark between
matter
is indicative of a strong interaction between
probability, with respect to a random Poisson distribution, of finding
galaxiesoptical/near-IR
which reside in the
counterparts. Forproximitylow-mass
the low-z sample, of galaxies,
the
there
galaxies arehalo
11 pairs
which whileinvery
centres,
reside theand massive
we of sources
proximity appearandtowehave concluded their active phase
the halo centres,
two sources in the solid angles δ$1 , δ$2 separated by an angle ◦ in which they reside; in the case of
with distances between 0.001◦ and 0.0031
expect foundsuchto abe strong before
. Of this epoch.
these,
expect onlysuch a Finally,
one was we noteto that
strong interaction the small-scale
eventually drive a substantial clustering data seem to require steep
θ. In practice, w(θ ) is obtained by comparing the actual source closer thaninteraction
5.4 arcsec and bothto theeventually
IRAC −3 pBzKs
and R-band
number
drive
the
pho- dark
of mergers.
aIt substantial
matternothalos
is possibly agalaxies
random coincidence thathaloes. This is suggestive of close
distribution with a catalogue of randomly distributed objects subject (ρ ∝ r ) profiles for the distribution of within their Figure 6. Average number of galaxies $N% per dark matter halo of specified
number of
tometry mergers.
indicate thatIt weisarepossibly
dealing with not
have a
two distinct random
bright masssources.
in coincidence
10
24-µm-selected excess sources ofat that
10 13 solar
intermediate-to-high redshifts are
to the same mask constraints as the real data. We chose to use the encounters
close (i.e. again with distances between 0.0011 and ◦ and/or mergers
0.0031 associated
◦
) pairs which could stronglyFigure favour6. both
Average AGN andMstar
number
mass formation
of galaxies
(expressed in M&$N% activity.
perThedark
units). solid matter
(red) line halo of specified
represents the case for
estimator (Hamilton 1993) bright 24-µm-selected
are instead found in the sources at Of
high-z sample. intermediate-to-high
masses.
these, only one is at a dis- redshifts are
in general to very intense star-forming systems; the ex- the high-z sample, while the dashed (green) line is for the low-z sample.
cess of proximity between such galaxies wouldmass M (expressed in M units). The solid (red) line represents the case for
DD RR in general tance associated
below 5.4 arcsec. toUnfortunately,
very intense Key
the two words:
sources of galaxies:
star-forming this pair systems; evolution the
eventually
–ex-galaxies: statistics – cosmology:&observations – cosmol-
lead to
w(θ ) = 4 − 1, (1) are unidentified both in the optical and in the near-IR
gas-rich mergers which could easily trigger enhanced
bands, and so the high-z sample, while the dashed (green) line is for the low-z sample.
star formation
(DR)2 cess of proximity between such galaxies ogy: theory would
activity – like
large-scale
eventually
the ones observed. structure
leadIn to of Universe
passing, we note – that
infrared:
evidencegeneral. the lowest possible masses where the sources start appearing), and
the pair has to be considered as spurious.
high-zfor an upturn (although less significative than ours) on scales r " we note that since $N% is a quantity which is averaged all over the
where DD, RR and DR are the number of data–data, random– gas-rich mergers
The angularwhich could
correlation easily
function for the trigger
h
enhanced
sample
0.2 −1
Mpc
was then
has
star
also
formation
been recently reported by Gilli et al. (2007) for
random and data–random pairs separated by a distance θ. computed by both including and excluding the possibly spurious dark matter haloes more massive than Mmin , in the most extreme
activitypair.
The two considered UDS-SWIRE samples have an estimated 5σ
likeThethe ones (θobserved.
small-scale In passing,
∼ 0.0015◦ ) results are their we
by thenote
shownsample z ∼ that
oftwo evidencesources inthe
1, 24-µm-selected lowestfields.
the GOODS possiblecase
masses where
our results imply the sources
that more start
than one appearing),
in two and
of all the structures
flux completeness F for an upturn
" 400 µJy. Furthermore, since the whole horizontal (although less significative
dashes in the right-hand than
The
panel of Fig. 4. The bestours)
filled average
circle onnumber
scales rfrom
" the
of galaxies $N%canonical hierarchical
as a function of halo merging scenario,
with masses M ∼ 10that
13 proved to
M& host a high-z, F 24 µm # 400 µJy galaxy.NIR color selection of high-z gal. populations
Colour information is also vital for discriminating between objects, and for the
determination of photometric redshifts, particularly using the 4000Å break as
it moves through the I, J, & H bands over the range 1Concluding remarks • Many EG problems could be solved with a deep and LA NIR survey • Synergy with SMM/Opt/X-ray deep surveys will be crucial for z determination and selection of high-z objects. • Synergy with HI surveys will allow to get baryonic quantities (the dream of modelers) • Follow-up (spectra, opt. bands, etc.) of discovered high-z galaxies.
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