The HerMES SPIRE Submillimeter Luminosity FunctionThe HerMES SPIRE Submillimeter Luminosity FunctionMattia Vaccari & Lucia Marchetti & Alberto Franceschini (University of Padova)Mattia Vaccari & Lucia Marchetti & Alberto Franceschini (University of Padova)

Isaac Roseboom (University of Sussex) & the HerMES Consortium - http://hermes.sussex.ac.ukIsaac Roseboom (University of Sussex) & the HerMES Consortium - http://hermes.sussex.ac.uk

The HerMES SPIRE Submillimeter Luminosity FunctionThe HerMES SPIRE Submillimeter Luminosity FunctionMattia Vaccari & Lucia Marchetti & Alberto Franceschini (University of Padova)Mattia Vaccari & Lucia Marchetti & Alberto Franceschini (University of Padova)

Isaac Roseboom (University of Sussex) & the HerMES Consortium - http://hermes.sussex.ac.ukIsaac Roseboom (University of Sussex) & the HerMES Consortium - http://hermes.sussex.ac.ukMattia VaccariMattia Vaccari

mattia@mattiavaccari.netmattia@mattiavaccari.netwww.mattiavaccari.netwww.mattiavaccari.net

Mattia VaccariMattia Vaccarimattia@mattiavaccari.netmattia@mattiavaccari.net

www.mattiavaccari.netwww.mattiavaccari.netA) SummaryA) Summary

We present the first measurement of the We present the first measurement of the Submillimeter Local Luminosity FunctionSubmillimeter Local Luminosity Function based based

on on HerMESHerMES data. data. Herschel SPIREHerschel SPIRE observations are combined with Spitzer, 2MASS & SDSS observations are combined with Spitzer, 2MASS & SDSS

datasets in the SWIRE Lockman Hole datasets in the SWIRE Lockman Hole (LH) (LH) and Spitzer Extragalactic First Look Survey and Spitzer Extragalactic First Look Survey

(XFLS) (XFLS) fields (totaling fields (totaling 14.7 deg14.7 deg22) to optimally detect and identify Herschel sources. ) to optimally detect and identify Herschel sources. We We

compute the 250, 350, 500 µm as well as the IR bolometric (8-1000 µm) local (0<z<0.2) compute the 250, 350, 500 µm as well as the IR bolometric (8-1000 µm) local (0<z<0.2)

luminosity functionluminosity function and thus derive local benchmarks for models of the formation and and thus derive local benchmarks for models of the formation and

evolution of submillimeter galaxies at a very early stage of the Herschel mission.evolution of submillimeter galaxies at a very early stage of the Herschel mission.

A) SummaryA) SummaryWe present the first measurement of the We present the first measurement of the Submillimeter Local Luminosity FunctionSubmillimeter Local Luminosity Function based based

on on HerMESHerMES data. data. Herschel SPIREHerschel SPIRE observations are combined with Spitzer, 2MASS & SDSS observations are combined with Spitzer, 2MASS & SDSS

datasets in the SWIRE Lockman Hole datasets in the SWIRE Lockman Hole (LH) (LH) and Spitzer Extragalactic First Look Survey and Spitzer Extragalactic First Look Survey

(XFLS) (XFLS) fields (totaling fields (totaling 14.7 deg14.7 deg22) to optimally detect and identify Herschel sources. ) to optimally detect and identify Herschel sources. We We

compute the 250, 350, 500 µm as well as the IR bolometric (8-1000 µm) local (0<z<0.2) compute the 250, 350, 500 µm as well as the IR bolometric (8-1000 µm) local (0<z<0.2)

luminosity functionluminosity function and thus derive local benchmarks for models of the formation and and thus derive local benchmarks for models of the formation and

evolution of submillimeter galaxies at a very early stage of the Herschel mission.evolution of submillimeter galaxies at a very early stage of the Herschel mission.

B) HerMES SPIRE Source Extraction and Cross-IdentificationB) HerMES SPIRE Source Extraction and Cross-Identification

(Roseboom et al., MNRAS, in preparation)(Roseboom et al., MNRAS, in preparation) At the depth of our SDP imaging there are ~1-10 beams/src, significantly below the At the depth of our SDP imaging there are ~1-10 beams/src, significantly below the traditional confusion limit of 30 beams/src (see Figure 1). Thus we need to take account of traditional confusion limit of 30 beams/src (see Figure 1). Thus we need to take account of source blending in performing source photometry and cross-identificationsource blending in performing source photometry and cross-identification We achieve this by making use of the strong correspondence between 24 μm imaging We achieve this by making use of the strong correspondence between 24 μm imaging from Spitzer and the SPIRE bands. The SPIRE fluxes of 24 μm sources are estimated using from Spitzer and the SPIRE bands. The SPIRE fluxes of 24 μm sources are estimated using a linear inversion method which finds the best fit set of fluxes considering the 24 μm a linear inversion method which finds the best fit set of fluxes considering the 24 μm positions and the SPIRE maps (see mat). Similar methods have been used previously on positions and the SPIRE maps (see mat). Similar methods have been used previously on Spitzer and BLAST data (Magnelli et al. 2009, Bethermin et al. 2010, Chapin et al. 2010)Spitzer and BLAST data (Magnelli et al. 2009, Bethermin et al. 2010, Chapin et al. 2010) Testing on simulations (see Figures 2/3 & 4) shows that our method is both reliable and Testing on simulations (see Figures 2/3 & 4) shows that our method is both reliable and returns high completeness for even the faintest SPIRE sourcesreturns high completeness for even the faintest SPIRE sources While our method requires 24 μm detections, we estimate that in our deepest fields we While our method requires 24 μm detections, we estimate that in our deepest fields we are missing at most 15% of the faint SPIRE population with extreme Sare missing at most 15% of the faint SPIRE population with extreme S250250/S/S2424 flux ratios flux ratios For local (0<z<0.2) sources we estimate to be complete down to the adopted flux limitsFor local (0<z<0.2) sources we estimate to be complete down to the adopted flux limits

B) HerMES SPIRE Source Extraction and Cross-IdentificationB) HerMES SPIRE Source Extraction and Cross-Identification

(Roseboom et al., MNRAS, in preparation)(Roseboom et al., MNRAS, in preparation) At the depth of our SDP imaging there are ~1-10 beams/src, significantly below the At the depth of our SDP imaging there are ~1-10 beams/src, significantly below the traditional confusion limit of 30 beams/src (see Figure 1). Thus we need to take account of traditional confusion limit of 30 beams/src (see Figure 1). Thus we need to take account of source blending in performing source photometry and cross-identificationsource blending in performing source photometry and cross-identification We achieve this by making use of the strong correspondence between 24 μm imaging We achieve this by making use of the strong correspondence between 24 μm imaging from Spitzer and the SPIRE bands. The SPIRE fluxes of 24 μm sources are estimated using from Spitzer and the SPIRE bands. The SPIRE fluxes of 24 μm sources are estimated using a linear inversion method which finds the best fit set of fluxes considering the 24 μm a linear inversion method which finds the best fit set of fluxes considering the 24 μm positions and the SPIRE maps (see mat). Similar methods have been used previously on positions and the SPIRE maps (see mat). Similar methods have been used previously on Spitzer and BLAST data (Magnelli et al. 2009, Bethermin et al. 2010, Chapin et al. 2010)Spitzer and BLAST data (Magnelli et al. 2009, Bethermin et al. 2010, Chapin et al. 2010) Testing on simulations (see Figures 2/3 & 4) shows that our method is both reliable and Testing on simulations (see Figures 2/3 & 4) shows that our method is both reliable and returns high completeness for even the faintest SPIRE sourcesreturns high completeness for even the faintest SPIRE sources While our method requires 24 μm detections, we estimate that in our deepest fields we While our method requires 24 μm detections, we estimate that in our deepest fields we are missing at most 15% of the faint SPIRE population with extreme Sare missing at most 15% of the faint SPIRE population with extreme S250250/S/S2424 flux ratios flux ratios For local (0<z<0.2) sources we estimate to be complete down to the adopted flux limitsFor local (0<z<0.2) sources we estimate to be complete down to the adopted flux limits

HerMES

~70 deg2

C) Optical/NIR Counterparts & SED FittingC) Optical/NIR Counterparts & SED Fitting

HerMES/Spitzer Large-Area SDP FieldsHerMES/Spitzer Large-Area SDP Fields

LHLH & & XFLSXFLS were used in this work were used in this work

NameNameAreaArea

(deg(deg2)2)

SSlimlim

(mJy)(mJy)

0<z<0.2 Sources0<z<0.2 Sources

Total (Spec/Phot)Total (Spec/Phot)

LHLH ~ 10~ 10 4040 478 (369/109)478 (369/109)

XFLSXFLS ~ 5~ 5 3030 275 (222/53)275 (222/53)

Source #s are for the 250 μm sampleSource #s are for the 250 μm sample

Flux limits are the same at 350 & 500 μm Flux limits are the same at 350 & 500 μm

D) SPIRE 250, 350, 500 µm & IR Bolometric (8-1000 µm) LLFD) SPIRE 250, 350, 500 µm & IR Bolometric (8-1000 µm) LLF

The accurate 24 μm positions used for Herschel source extraction allows us to reliably The accurate 24 μm positions used for Herschel source extraction allows us to reliably determine the SDSS and 2MASS counterparts of all our 0<z<0.2 sources.determine the SDSS and 2MASS counterparts of all our 0<z<0.2 sources.

SDSS, NED and SWIRE follow-up spectroscopic redshifts are used along with SDSS SDSS, NED and SWIRE follow-up spectroscopic redshifts are used along with SDSS photometric redshifts to obtain a complete redshift information.photometric redshifts to obtain a complete redshift information.

Archival multi-Archival multi-wavelength spectrophotometrywavelength spectrophotometry (including IRAC and MIPS) then allows us (including IRAC and MIPS) then allows us to determine accurate photometric redshifts and IR luminosities for all 0<z<0.2 sources.to determine accurate photometric redshifts and IR luminosities for all 0<z<0.2 sources.

E) Conclusions and future work E) Conclusions and future work We provide We provide useful local (0<z<0.2) benchmarks for submillimeter galaxy formation and useful local (0<z<0.2) benchmarks for submillimeter galaxy formation and

evolution studiesevolution studies at a very early stage of the Herschel mission and thus pave the way for at a very early stage of the Herschel mission and thus pave the way for

wider-area data soon to be provided by wider-area data soon to be provided by Herschel surveys such as HerMES and H-ATLASHerschel surveys such as HerMES and H-ATLAS Using 24 Using 24 μm positions and combining linear inversion and model selection techniques positions and combining linear inversion and model selection techniques

we reliably detect Herschel sources and identify them in multi-wavelength imageswe reliably detect Herschel sources and identify them in multi-wavelength images We find a slightly more abundant local submillimeter population than predicted by most We find a slightly more abundant local submillimeter population than predicted by most

models in recent literature and an IR bolometric (8-1000models in recent literature and an IR bolometric (8-1000 μm μm) LLD of 1.3 10) LLD of 1.3 1088 L L at z~0.1 at z~0.1 The continuation of the Herschel mission will yield larger samples and improved SED The continuation of the Herschel mission will yield larger samples and improved SED

templates, providing templates, providing better IR bolometric luminosity estimates and stronger constraints better IR bolometric luminosity estimates and stronger constraints

on models on models for galaxy evolution and dust emission from the local to the distant Universefor galaxy evolution and dust emission from the local to the distant Universe

E) Conclusions and future work E) Conclusions and future work We provide We provide useful local (0<z<0.2) benchmarks for submillimeter galaxy formation and useful local (0<z<0.2) benchmarks for submillimeter galaxy formation and

evolution studiesevolution studies at a very early stage of the Herschel mission and thus pave the way for at a very early stage of the Herschel mission and thus pave the way for

wider-area data soon to be provided by wider-area data soon to be provided by Herschel surveys such as HerMES and H-ATLASHerschel surveys such as HerMES and H-ATLAS Using 24 Using 24 μm positions and combining linear inversion and model selection techniques positions and combining linear inversion and model selection techniques

we reliably detect Herschel sources and identify them in multi-wavelength imageswe reliably detect Herschel sources and identify them in multi-wavelength images We find a slightly more abundant local submillimeter population than predicted by most We find a slightly more abundant local submillimeter population than predicted by most

models in recent literature and an IR bolometric (8-1000models in recent literature and an IR bolometric (8-1000 μm μm) LLD of 1.3 10) LLD of 1.3 1088 L L at z~0.1 at z~0.1 The continuation of the Herschel mission will yield larger samples and improved SED The continuation of the Herschel mission will yield larger samples and improved SED

templates, providing templates, providing better IR bolometric luminosity estimates and stronger constraints better IR bolometric luminosity estimates and stronger constraints

on models on models for galaxy evolution and dust emission from the local to the distant Universefor galaxy evolution and dust emission from the local to the distant Universe

We evaluate the Monochromatic & IR Bolometric LLFs using the 1/VWe evaluate the Monochromatic & IR Bolometric LLFs using the 1/Vmaxmax estimator estimator

We compare our estimates with models and measurements from recent literatureWe compare our estimates with models and measurements from recent literature

(Poisson) errors are estimated in each field and a weighted mean is then computed(Poisson) errors are estimated in each field and a weighted mean is then computed

A&A Herschel Special Issue

A&A Herschel Special Issue A&A Herschel Special Issue

A&A Herschel Special Issue

Figures 2/3. Simulations used for XID: GOODS-N 250 μmFigures 2/3. Simulations used for XID: GOODS-N 250 μmsimulated map (left) & real map (right)simulated map (left) & real map (right)

Figures 2/3. Simulations used for XID: GOODS-N 250 μmFigures 2/3. Simulations used for XID: GOODS-N 250 μmsimulated map (left) & real map (right)simulated map (left) & real map (right)

Testing was performed on two simulated datasets by taking the mock catalogs of Testing was performed on two simulated datasets by taking the mock catalogs of Fernandez-Conde et al. (2008) and producing maps which match the observed Fernandez-Conde et al. (2008) and producing maps which match the observed properties (i.e. noise, PRF) of our GOODS-N (deep) and LH (shallow) dataproperties (i.e. noise, PRF) of our GOODS-N (deep) and LH (shallow) data Comparisons are performed for the shallow data between our XID method and two Comparisons are performed for the shallow data between our XID method and two existing techniques; the ubiquitous p-statistic coupled with Sussextractor derived existing techniques; the ubiquitous p-statistic coupled with Sussextractor derived source catalogues, and a simpler map-based approach based on Bethermin et al. (2010)source catalogues, and a simpler map-based approach based on Bethermin et al. (2010) At 250 μm the HerMES XID method is seen to clearly outperform the othersAt 250 μm the HerMES XID method is seen to clearly outperform the others At the longer wavelengths the advantage currently offered by our method is limitedAt the longer wavelengths the advantage currently offered by our method is limited

Testing was performed on two simulated datasets by taking the mock catalogs of Testing was performed on two simulated datasets by taking the mock catalogs of Fernandez-Conde et al. (2008) and producing maps which match the observed Fernandez-Conde et al. (2008) and producing maps which match the observed properties (i.e. noise, PRF) of our GOODS-N (deep) and LH (shallow) dataproperties (i.e. noise, PRF) of our GOODS-N (deep) and LH (shallow) data Comparisons are performed for the shallow data between our XID method and two Comparisons are performed for the shallow data between our XID method and two existing techniques; the ubiquitous p-statistic coupled with Sussextractor derived existing techniques; the ubiquitous p-statistic coupled with Sussextractor derived source catalogues, and a simpler map-based approach based on Bethermin et al. (2010)source catalogues, and a simpler map-based approach based on Bethermin et al. (2010) At 250 μm the HerMES XID method is seen to clearly outperform the othersAt 250 μm the HerMES XID method is seen to clearly outperform the others At the longer wavelengths the advantage currently offered by our method is limitedAt the longer wavelengths the advantage currently offered by our method is limited

ΦΦ250,350,500250,350,500 plots : black solid line is total model and color lines are different populations plots : black solid line is total model and color lines are different populations

of Franceschini et al. (2010), dashed black line is model of Xu et al. (2001), dot-dot-dot-of Franceschini et al. (2010), dashed black line is model of Xu et al. (2001), dot-dot-dot-dashed black line is model of Negrello et al. (2007)dashed black line is model of Negrello et al. (2007)

ΦΦIRIR plot : dashed, plot : dashed, dot-dashed, dot-dot-dot-dashed and dotted black lines indicate predictions by Xu et al. (2001), Lagache et al. (2004), Negrello et al. (2007) and Valiante et al. (2009), dashed red line is modified Schechter (double exponential) best fit dashed red line is modified Schechter (double exponential) best fit

http://hermes.sussex.ac.ukhttp://hermes.sussex.ac.uk

Empty DiamondsEmpty DiamondsSanders et al. 2003Sanders et al. 2003