Obesity in the Universe: How Did Early Type Galaxies Become so Fat?

Richard Ellis & Drew Newman (Caltech)

CIFAR April 6th 2012

Bimodal Galaxy Distribution

Bell et al. 2003

Star formingBlue

Late typeYoung

PassiveRed

Early typeOld

• Hubble Sequence - morphology shows dynamically distinct populations

Gas content/integrated colors - different ages and star formation histories

Color-magnitude Relation at z~2

Kriek et al 2009 Ap J 705, L71

Photometric and dynamical studies of early-type galaxies over 0<z<1 confirm that the most massive examples formed the bulk of their stars prior to z~2

And, sure enough, red and dead galaxies were eventually found at z~2

Logically these would seem to be the precursors of most of today’s massive early-types (although continued formation is also possible)

Modest Increase in Mass Density of Red Galaxies

Log Fractional Contribution to Total Stellar Mass 0.4<z<1.4

Bundy et al Ap J 651, 120 (2006)

Spectroscopically-complete surveys of galaxies with IR-based stellar masses show only a modest increase (30%) in the abundance of M>1011M red galaxies over 0.4<z<1.4 (5 Gyr) at the expense of truncated SF in blue galaxies

Rising Reds Declining Blues

The big surprise: z~2 early-types are SMALL!

SDSS

2 < z < 3

HST sizes of a representative sample of z~2-3 red galaxies with M >1011 M: re~0.9 kpc

2-5 times smaller than comparably massive z~0 ellipticals!

Growth in size but not mass?

half-light radius

van Dokkum et al (2008)

Earlier claims by:

Daddi et al (2005), Trujillo et al (2006)

The `Red Nuggets’ Problem

Initial skepticism at observational claims: result depends on combination of photometrically-determined masses and HST sizes of distant galaxies

• Perhaps mass overestimated e.g. “bottom light” IMF, AGB stars • Perhaps size underestimated due to surface brightness effects• Dynamical data to confirm masses• Improved HST data over 0<z<2• How much growth occurred in self-consistent samples?• Separating growth of long-lived populations vs new arrivals• What does it all mean?!

How Big Should a Massive Galaxy Be? Ask a Theorist

Wuyts et al 2010 Ap J 722, 1666

Size Depends: I – On Gas Fraction of Initial Merger

local spheroids

z~2 red galaxies

Wuyts et al 2010 Ap J 722, 1666

increasing dissipational gas fraction fgas

Equal mass merger SPH simulations using GADGET-2 with gas cooling, multi-phase ISM and SN/AGN feedback (Springel, Hernquist et al)Remnant is smaller for suitably-scaled z~3 disks with high gas fractions

fgas

re ~ exp( -fgas/0.3)

Size Depends: II – On Epoch of Merger

Since gas fraction fgas declines with time, later merger products are larger

NB: In principle this could account for expansion in size from z~2 to 0 but such a simple explanation is ruled out by low rate of major merging and absence of significant decline in abundance of fixed mass spheroids for z<1

Hopkins et al 2010 MN 401, 1099

Keck LRIS-R: IAB<23.5; 12-16 hr exposures, 1.1 < z < 1.60

Newman et al 2010 Ap J 707, L103

Size evolution at fixed dynamical mass

Standard test conducted in literature:

size ~ (1+z)-x

Unlikely evolutionary path

For M>1011 M

x = 0.70 ± 0.11(40% by z=1)

• Only massive early-types are significantly growing in size• z > 2 objects appear ultra-compact implying very fast growth??

Size evolution at fixed velocity dispersion

More physically meaningful

Mergers should increase size but not velocity dispersion

Exploits unique dynamical data

Tests “progenitor bias”(cut in Mdyn restricts in σ, R so could give false evolutionary trend)

For σ > 225 km s-1

x = 0.69 ± 0.21

Growth ×1.7-2.7 since z~2

Treu et al DEIMOS

Newman et al LRIS-R

Cappellari stack

van Dokkum z=2.2

Matched SDSS=LRIS

Growth KeckSDSS

Size growth for 1011 M galaxy of × 3.5 ± 0.3 over 0.4 < z < 2.5But scatter (1σ region) is significant (and valuable information)Growth rate consistent with that found in limited dynamical data and, again, particularly rapid in 2 Gyr period from 1.5<z<2.5

Size Growth Rate in CANDELS data

Newman et al (2012) Ap J 746, 162

How Did Early Galaxies Enlarge?

Improved observational data (dynamical masses, HST images) confirms size growth is real!

What, physically, could lead to this growth in size?

• Major mergers

• Minor mergers

• Mass loss/adiabatic expansion (implausible as inactive systems)

Size Growth During Dissipationless Merging

Naab et al 2009 Ap J 699, L108

(see also Khochfar & Silk 2006 Ap J 648, L21; Khochfar & Silk 2009 MNRAS 397, 506)

From virial theorem, total energy

Consider merger such that

and define

Assuming conservation ofenergy (e.g. parabolic orbits,Binney & Tremaine 2008)

Major merger : no change in v, M and R double, d log R / d log M = 1

Lots of minor mergers find d log R / d log M = 2

SPH simulations of minor mergers indicate d log R / d log M ~ 1.3 – 1.6

Measuring the Minor Merger Rate in CANDELS Data

WFC3/IR data is sufficiently deep (H<26.5) that we can secure photometric redshifts for secondaries 1/10th as massive for 404 quiescent primaries with log MP/M < 10.7 over 0.4 < z < 2

Search area 10 < R < 30 h-1 kpcδz < 0.1 (for z < 1) and δz < 0.2 (for 1 < z < 2)Mass ratio μ = MS/MP > 0.1

Caution: such photo-z associations could still lead to an over-estimate of pairs that will ultimately merge given environs in which red galaxies lie

Satellite photo z precision

μ*=0.3

μ*=0.5

μ*=0.2

μ*=0.1 μ*=0.1

Measuring the Minor Merger Rate in CANDELS DataFind fpair = 0.16 ± 0.03 over full z range

Majority of secondaries are also red

μ (mass ratio) distribution quite flat as expected from SAMs

Newman et al (2012) Ap J 746, 162

Can Minor Merging Explain Size Growth: I?

Assuming:

1.Merger timescale

τe ~ 1-2 Gyr

(Patton+, Lotz+, Kitzbichler+)

2. Bound fraction of projected pairs Cmg (=f3D)~0.5

3. Size growth per mass increase

dlogR / dlogM ~1.6(Nipoti+)

Size growth over 0.4<z<1 is broadly consistent with that expected from observer minor merger fraction IF merger timescale is fastSize growth over 1<z<2 is inconsistent with observed minor merger fraction for any reasonable choice of parameters

Accounting for New Arrivals

Simple model is naïve as it assumes all sources enlarge in lockstep from z~2 progenitors.

In reality population comprises old galaxies which formed at z~2 and perhaps expand via mergers

AND

Newly arrived quiescent systems whose size reflects their epoch of formation

Comoving no. density of log M>10.7 quiescents

Rapid size growth at high z may be associated with increase in no. density over 1.5<z<2.5

Evolution in Size Distribution FunctionKey to distinguishing growth of pre-existing sources and the arrival of new sources is the cumulative

distribution of mass-normalized radius γ

In addition to matching the evolution in mean size growth and number density of quiescent galaxies, a satisfactory model must also account for the rate of depletion of the most compact systems from high redshift to low redshift.

Cumulative Distribution Function (CDF) is fit by a skew-normal distribution at various redshifts

A Two Phase Growth ModelConsider CDF at z~2 and z~1:

Mergers add mass and lead to enlargement.

For “intra sample mergers”, the number also declines.

Plausible model will shift some fraction P of the most compact z~2 sources to lie within the z~1 CDF with the remainder (1-P) as `new arrivals’

Defines Δlog γmin

The test is thus whether the observed rate of minor mergers can deplete this fraction of the most compact sources in the observed CDFs

Can Minor Merging Explain Growth: II ?

Conclusion unchanged: 0.4<z<1 size evolution is readily explained by observed rate of minor mergers, but rapid growth over 1<z<2.5 is harder to understand

Newman et al (2012) Ap J 746, 162

Summary

• Present-day massive early type galaxies formed most of their stars by z~2

• Evolving stellar mass functions place some limits on the continued appearance of massive early types: most are not genuine `new arrivals’ but represent some combination of dry mergers and truncated star formation in massive blue galaxies

• The compact nature of early types at z~2.5 is confirmed by CANDELS data; we observe a × 3.5 growth in mean size over 0.4<z<2.5 for quiescent systems with masses > 1010.7 M.

• Dynamical data has been key in verifying the relevant masses, at least to z~1.6; the `red nugget puzzle’ is unlikely to be due to observational errors/mis-interpretations

• Minor mergers are so far the only plausible mechanism for the size growth. Modeling suggests the observed merger rate can explain the growth observed since z~1 but explaining the rapid growth observed over 1.5<z<2.5 remains a challenge

Cosmology with the Subaru Prime Focus Spectrograph

http://sumire.ipmu.jp/en/2652

HyperSuprimeCam – being commissioned now!

Subaru Prime Focus Spectrograph (PFS) Team

Prime Focus Unit includes Wide Field Corrector (WFC) and Fiber Positioner.

Spectrograph room located above Naysmith platform

Fiber connector mounted on top end structure

Fiber Cable routed around elevation axis and brings light to the Spectrographs

PFS Concept is Caltech/JPL WFMOS design

Design study based on Subaru-provided

details, several visits to Subaru,

interaction with HSC team

Key requirements: survey speed and

positioner reliability

PFS Positioner

Optical Bench with Positioner Units

Positioner Unit - Cobra

Cobra system tested at JPL in partnership with New Scale TechnologiesDesigned to achieve 5μm accuracy in < 8 iterations (40 sec) 2400 positioners 8mm apart in hexagonal pattern to enable field tiling

A&G Fiber Guides

Positioner Element – “Cobra”

• 7.7mm diameter, theta-phi system positioning within 9.5mm patrol area to 5μm precision.

• Optical fibers mounted in “fiber arm” which attaches to upper postioner axis:

• Fiber runs through the center of the positioner

First axis of rotation

Second axis of rotation

Patrol RegionTop View

Fiber Tip

Theta stage

Phi stage

Fiber arm

Triple-arm Spectrograph (one of 4)

Unique feature of Jim Gunn design is continuous coverage from 370nm to 1.3μm with matched spectral resolutions (R~2500-4000) for effective simultaneous exposures

Detectors: Hamamatsu red-sensivity CCDs and expected Teledyne HgCdTe 4RG arrays

PFS Cosmology: Key Science Goals

(Takada, Hirata, Kneib)• Measure the cosmological distances, DA(z) and

H(z), to 3% accuracy in each of 6 redshift bins over 0.8<z<2.4 via the BAO experiment

• Use the BAO distance constraints to reconstruct the dark energy densities in each redshift bin

• Use the BAO distance constraints to constrain

the curvature parameter ΩK to 0.3% accuracy

• Measure the redshift-space distortion (RSD) effect to reconstruct the growth rate in each redshift bin to 6% accuracy

PFS Cosmology Survey

• The total volume: ~9 (Gpc/h)3 ~ 2 × BOSS survey

• Assumed galaxy bias (poorly known): b=0.9+0.4z• PFS survey will have ngP(k)~a few@k=0.1Mpc/h in

each of 6 redshift bins

Redshift

Vsurvey

(h-3 Gpc3)# of

galaxies (per FoV)

ng

(10-4 h3 Mpc-3)

bias ngP(k)@k=0.1hMpc-1

0.8<z<1.0

0.79 358 6.0 1.26 2.23

1.0<z<1.2

0.96 420 5.8 1.34 2.10

1.2<z<1.4

1.09 640 7.8 1.42 2.64

1.4<z<1.6

1.19 491 5.5 1.5 1.78

1.6<z<2.0

2.58 598 3.1 1.62 0.95

2.0<z<2.4

2.71 539 2.7 1.78 0.76

• Assume 100 clear nights to meet the scientific goals → the area of PFS survey

Expected BAO constraints

• The PFS cosmology survey enables a 3% accuracy of measuring DA(z) and H(z) in each of 6 redshift bins, over 0.8<z<2.4

• This accuracy is comparable with BOSS, but extending to higher redshift range

• Also very efficient given competitive situation– BOSS (2.5m): 5 yrs– PFS (8.2m): 100

nights

BOSS PFS-Red PFS-NIR

DE constraints• The BAO geometrical constraints achieved

significantly constrain the DE parameters

• For a (w0, wa)-DE model, H(z) and DA(z) are given as

Survey Ωde wconst wa FoM ΩK

Planck+BOSS 0.0061

0.076

1.2 11 0.0071

Planck+BOSS+PFS

0.0051

0.059

0.36 47 0.0030• PFS can significantly improve the DE constraints

over BOSS• PFS can achieve a 0.3% accuracy of the curvature → a

fundamental discovery • A wider redshift coverage as well as more

independent z-bins are powerful aspects in improving the overall constraints (which the CMB alone cannot)

DE reconstruction• The wide-z coverage of PFS+BOSS enables a

reconstruction of DE densities as a function of redshift → can constrain a broader range of DE models

• PFS can significantly improve the accuracy of the reconstruction due to the increased z-bins

• 7% accuracy of Ωde(z) in each of

z-bins

• PFS+SDSS+Planck allows a detection of dark energy up to z~2, for a Λ-type model

But is PFS competitive with BigBOSS?• Survey

parameters taken from BigBOSS proposal

• 500 vs. 100 nights

• 14,000 vs. 1,420 deg2

• Naively, a factor (10)1/2 difference

• BigBOSS better than PFS at z<1.2 (but note target selection a big issue for BigBOSS)

• PFS comparable with BigBOSS for 1.2<z<1.6 but PFS can uniquely target1.6<z<2.4

• PFS more likely to complete its survey before Euclid

BigBOSS (4m) vs. PFS (8.2m)

BigBOSS

Redshift-Space Distortion (RSD)

• The redshift-space distortion can probe the growth rate

• It gives a complementary probe of DE and can test gravity on cosmological scales

• The PFS can reconstruct the growth rate in each of redshift bins, to a 7% accuracy

Peacock et al (2dF team, 01)