Mattia VaccariSKA South Africa Fellow

University of the Western Cape

Lucia Marchetti - Open UniversityAlberto Franceschini - University of Padova

HerMES Consortium (Coordinated by Jamie Bock & Seb Oliver)

The Obscured Cosmic Star Formation HistoryFrom Spitzer/Herschel’s Era to Euclid/SKA’s

• Determine dust attenuation corrections for Continuum- & Line-based Indicators

• Reconcile Star Formation Rates with Stellar Masses (and IMFs and SP Models)

• Assess AGN contamination levels on SFR (and SM) estimates 2

Cosmic Star Formation History

Hopkins & Beacom 2006Multi-Wavelength CSFH

Dust Correction

Bouwens & Illingworth 2006SFRD from FUV rest-frame

• The emergence of a “Concordance View” on the Cosmic Star Formation History depends on consistently being able to:

Herschel/HerMES Science Motivation

z=0z=

1

z=4

Herschel Extragalactic Imaging Surveys- High-sensitivity (albeit with moderate resolution)- Use PACS & SPIRE at 100-500 µm- Observe the SED peak of IR galaxies at 1<z<4- Detect Large and Uniform Samples of (U)LIRGs- Derive IR “Bolometric” (8-1000 µm) Luminosity and use it as a Star Formation Rate Indicator

Questions to be addressed by Herschel- What is the history of Far-IR galaxies?- How do they assemble and evolve over time?- Where have luminous FIR systems gone today?- How do FIR galaxies relate to dark matter?- What is the role of dust in star formation?- What is the connection between dusty star formation and AGNs?PA

CS

PAC

SSP

IRE

SPIR

ESP

IRE

Angular resolution

Survey speed

3

Herschel is a recently completed ESA cornerstone mission (2009-2013)• large (3.5 m) aperture, low emissivity (~5%), passively cooled (70-90 K)• cryogenically cooled focal plane science instruments with > 3 yr lifetime (2009-2013)

http://hermes.sussex.ac.uk

6.5'

7.5'

GOODS-N - D. Elbaz

The Confusion Challenge

4

5

IRAS dust mapSchlegel+ 1998

HerMES fields

6

Spitzer Proprietary Catalogs (SWIRE, Bootes, XFLS)IRAC (ch1 or ch2) selectedMIPS 24/70/160 always available

GALEX NUV & FUV always available

SDSS available in the North (Astro/Photo Calibration)

Miscellaneous Optical Imaging (SWIRE, INTWFS, NDWFS, CFHTLS…)

2MASS J,H,Ks always available (Spitzer Astro Calibration)

UKIDSS J, K available in XMM/LH/EN1

VIKING & IBIS available in XMM & Bootes respectively

VISTA/VIDEO will cover 12 deg2 within ES1/XMM/CDFS in ZYJHK

Spec-Z available @ NED & Recent Literature

Photo-Z available from SDSS @ Low-Z as well as from SWIRE @ High-Z (Rowan-Robinson+ 2013, using an early version of the data fusion)

A Multi-Wavelength Catalog for HerMES scienceThe Spitzer Multi-Wavelength ‘Data Fusion’

} INFRARED

UV}OPTICAL}

OPTICAL}NIR}

NIR}

NIR}} NIR

- Base on an homogeneous source re-extraction on IRAC and MIPS maps (IRAC1 or IRAC2 selection)

- COSMOS and other deep fields ‘data fusion’ carried out in collaboration with other consortia

- Catalog-level Aperture Matching and SED fitting χ2 minimization (Rowan-Robinson+ 2013)

- Image-level aperture matching and/or multi-band source extraction will be required for the optimal exploitation of deep IRAC, VISTA and VST data in equatorial/southern fields 7

A Multi-Wavelength Catalog for HerMES scienceThe Spitzer Multi-Wavelength ‘Data Fusion’

TOT : ~ 3 million of sources

SWIRE

http://www.mattiavaccari.net/df/65 deg2 σ ~ 1 µJy in IRAC12

Measuring Galaxy Evolution

The evolution of the Galaxy Luminosity Function with redshift can beinterpreted as a combination of luminosity and density evolution

(Chris Pearson)

REDSHIFT

•  LUMINOSITY EVOLUTION�(Galaxies in the past were brighter than today)

•  DENSITY EVOLUTION (Galaxies in the past were more numerous than today)

8

Depends on 4(+) parameters

-14

-12

-10

-8

-6

-4

-2

6 7 8 9 10 11 12 13 14

(Differential) Luminosity Function(Differential) Luminosity Function

lg(!

) {M

pc-3

dex-1

}

lg(L/LO)

!!"*!

#!L*!

L<L*(power law)! L>L*(exponential)!

! =d"dL

= ! *LL *# $

% &

1'(

exp '12) 2 lg

2 (1 + L / L*)# $

% &

! - Faint end slope

L* - Characteristic luminosity!

"* - Number density normalization

# - Gaussian width

LUMINOSITY FUNCTION Galaxy number density as a function of their luminosity

The Galaxy Luminosity Function

Luminosity and density evolution can be seen as variations of L* and ϕ*

(Chris Pearson)

9

10

Empty Circlesthis work

vs Local Estimates

Empty TrianglesMarleau+ 2007

Empty SquaresShupe+ 1998

Empty PentagonsRodighiero+ 2010

AsterisksBabbedge+ 2006

Spitzer Data Fusion LLF @ 24 μm

11

Empty Circlesthis work

vs Local Estimates:

Empty SquaresPatel+ 2013 (MIPS)

Dashed LinesModel predictionsby Fontanot+ 2012

Dot-Dashed & Dashed LinesSerjeant & Harrison 2005

with two different functional forms

Spitzer Data Fusion LLF @ 70 μm

12

Empty Circlesthis work

vs Local Estimates

Empty TrianglesTakeuchi+ 2006 (ISO)

Dot-Dashed & Dashed LinesSerjeant & Harrison 2005

with two different functional forms

Empty SquaresPatel+ 2013 (MIPS)

Dashed LinesModel predictionsby Fontanot+ 2012

Spitzer Data Fusion LLF @ 160 μm

The multi-wavelength approachto Herschel source characterization

13

SPIRE 250 µm R-band optical

Roseboom et al. 2010

24 µm sources

250 µm beam

GOODS-N Images

SPIRE fluxes are estimated using a combination of linear inversion and model selection techniques and fitting the map with the smallest number of point-like

sources at the positions of MIPS 24 micron sources justified by the data.When deep 24 micron imaging is available the method will miss a small fraction

of the 250 micron population characterized by extreme 250/24 flux ratios.

The FIR/SMM Local Luminosity FunctionMarchetti+ in prep

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Redshift distributionNED+SDSS+BOSS SpeczSDSS Photometry & Photz

Magnitude distribution in redshift bins

SDSS r-band magnitude limit

5 HerMES wide fields with 7-band Spitzer DataHomogeneous re-extraction of Spitzer DataLH + XFLS + Bootes + EN1 + XMMTotal Area ~ 38 deg2 - 250 μm flux > 30 mJy

~ 5k sources up to z < 0.5

All SDSS0.4 < z < 0.60.2 < z < 0.40.0 < z < 0.2

15.0

15.5

16.0

16.5

17.0

17.5

18.0

18.5

19.0

19.5

20.0

20.5

21.0

21.5

22.0

4.04.0 5.0 6.0 7.0 8.0 9.0 1e021e02

S250 [mJy]

mag

_r [A

B]

The Evolution of the FIR/SMM Luminosity FunctionVaccari+ in prep

15

Redshift Distribution : SPIRE vs PACS

zCOSMOS SpeczUltraVista Photz

250 µm flux > 10 mJy10k sources up to z~5

SubaruCFHT

13

SPIRE (HerMES)PACS (PEP)

SPIRE (HerMES)PACS (PEP)

Marchetti+ in prep

SED Fitting & LF Estimation

SED fitting is carried out using empirical templates and a fixed redshift to evaluate

the panchromatic k-correction and thus monochromatic luminosities as well as the

IR Bolometric Luminosity (SFR)

Using Le Phare (Arnouts+ 1999 & Ilbert+ 2006)with Polletta+ 2007 & Gruppioni+ 2010 templates

We use the 1/Vmax non parametric LF Estimator (Schmidt 1968), fit

modified Schechter functions (Saunders+ 1990) and probe

luminosity and density evolution through the changes in L* and ϕ*

Depends on 4(+) parameters

-14

-12

-10

-8

-6

-4

-2

6 7 8 9 10 11 12 13 14

(Differential) Luminosity Function(Differential) Luminosity Function

lg( !

) {M

pc-3

dex-1

}

lg(L/LO)

!!"*!

#!L*!

L<L*(power law)! L>L*(exponential)!

! =d"dL

= ! *LL *# $

% &

1'(

exp '12) 2 lg

2 (1 + L / L*)# $

% &

! - Faint end slope

L* - Characteristic luminosity!

"* - Number density normalization

# - Gaussian width

LUMINOSITY FUNCTION Galaxy number density as a function of their luminosity

The SPIRE Local Luminosity Function

The Obscured Local Luminosity Density

Marchetti+ in prep

FUV

18

The Energy Output of the Local Universe

Marchetti+ in prep (after Driver+ 2012)

The Infrared Local Luminosity Densityfrom Spitzer/Herschel matched surveys

19

250 μm Luminosity Function

We agree with 0 < Z < 2 HerMES and H-ATLAS

previous work, pushing it to higher-z and lower-L

respectively

Dust treatment in current SAMs still inadequate to

describe evolution of SMM galaxies with redshift

Vaccari+ in prep (HerMES)Lapi+ 2011 (H-ATLAS)Eales+ 2010 (HerMES)

Fontanot+ 2012

The Evolution of the 0<Z<5 Sub-Millimeter Luminosity Function

20

90 μm Luminosity Function

PACS is slightly more sensitive at the faint end

(less affected by confusion) while possibly suffering

from some incompleteness and/or poor k-corrections at

the highest redshifts

Vaccari+ in prep (SPIRE)Gruppioni+ 2013 (PACS)

The Evolution of the 0<Z<5 Far-Infrared Luminosity Function

21

The Evolution of the 0<Z<5 Infrared Bolometric Luminosity Function

Vaccari+ in prep (SPIRE)Gruppioni+ 2013 (PACS)

Fontanot+ 2012

Infrared Bolometric Luminosity Function

Excellent agreement throughout between PACS

and SPIRE estimates

SPIRE is likely more complete/sensitive to the

highest redshift population(where we can only sample a small luminosity range)

22

luminosity evolution

Parametrizing Evolution

L* and ϕ* vs z (250 micron)

density evolution

Vaccari+ in prep Vaccari+ in prep

L* and ϕ* vs z (bolometric)

23

The Evolution of the 0<Z<5 Infrared Bolometric Luminosity Function

IR Bolometric Luminosity Function

24

Herschel provides the first reliable assessment of the IR bolometric luminosity density up to z ~ 5 based on FIR/SMM flux-limited samples of about 10k+ sources.

Our results are lower than previous Spitzer/MIPS estimates close to the peak of the Cosmic Star

Formation Rate Density, where Herschel shows a relatively fast decrease of galaxy activity beyond z > 2

IR Bolometric Luminosity& SFR Density Estimates

IR Bolometric Luminosity

Vaccari+ in prep (SPIRE)

Gruppioni+ 2013 (PACS)

Rodighiero+ 2010 (MIPS)

Perez-Gonzalez+ 2005 (MIPS)

IR vs UV (dust-uncorrected) SFRD

VVDS FUV LFs : Cucciati+ 2012SDF LBGs : Shimasaku+ 2005

Hopkins & Beacom 2006Behroozi+ 2013

Vaccari+ in prep

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What About Stellar Mass Assembly?

Burgarella+ 2013 adopted the FUV LFs by Cucciati+ 2012 and FIR LFs by Gruppioni+ 2013 to (re)derive the Unobscured and Obscured SFRD respectively and the related uncertainties

Making some reasonable assumptions about Star Formation Rate Density at very early times, our analysis yields a

Stellar Mass Density broadly in agreement with the latest observations

Where do we stand in the Radio?

• The 1.4 GHz Continuum is a powerful SFR tracer (unaffected by dust absorption)

• Current deepest wide (~deg2-scale) 1.4 GHz surveys reach 10/20 μJy rms

• Star Forming Galaxies (rather than AGNs) only dominate fainter than 100 μJy26

Padovani+ 2010

Padovani+ 2010

SFG LF Evolution

• MeerKAT/ASKAP will provide better resolution & SFR-sensitivity than SPIRE• MIGHTEE/EMU survey will sample the radio luminosity function deep & wide• FIR/Radio correlation probed up to high-z as a function of ‘any’ parameter• Redshift & Physical Properties will be provided by Optical/NIR ancillary data• LSST & Euclid Deep & Wide will be very well-matched to the SKA instead

What’s Next? The SKA Pathfinders!

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The star-forming galaxy luminosity function with MeerKAT/MIGHTEE + ASKAP/EMU

28(Isabella Prandoni)Needs ID-ing & Redshift Info & Physical Properties!

MeerKAT/MIGHTEE ASKAP/EMU

What’s Next? Deep & Wide Opt/NIR Surveys!

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McAlpine+ 2013(Bondi+ 2003)

DES/VST & VISTA & Spitzer Warm will provide Photometric Redshifts and

Stellar Masses up to z~5 over ~10+ deg2

==> full exploitation of existing radio surveys as well as of SKA pathfinders

VIDEO - Y/J/Ks in XMM3Jarvis+ 2013

3’ X 3’

Conclusions

✓ Herschel observations provide us with a complete characterization of the FIR/SMM spectral energy distributions for high- (and low-) redshift galaxies, which is key to the source bolometric emission and thus star formation rate

✓ The luminosity function shows a strong evolution in both luminosity (positive) and density (negative) over the full 0 < Z < 5 redshift range, which appears at strong variance with the predictions of most commonly adopted SAMs

✓ The Obscured and Unobscured SFR density estimates derived from Far-UV and Far-IR Luminosity Functions yield a picture of Cosmic Star Formation History broadly in agreement with observed Stellar Mass Assembly History

✓ LSST, Euclid & SKA (and before them DES/VST/VISTA & SKA pathfinders) will better investigate the obscured CSFH as a function of redshift and environment thanks to their combination of areal coverage and sensitivity, but the homogeneous exploitation of ancillary data will be key to their success

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