Prsentation PowerPoint

Deciphering the CIBBanyuls08/10/2012Resolving the CIB:I) Methods to identify the sources responsible for the CIB Matthieu BtherminCEA Saclay

The extragalactic background light (EBL)SED of the extragalactic background light (from Dole & Bthermin, in prep.)

2Measurements of the cosmic infrared background (CIB) levelAbsolute measurements: need an absolute photometry and an accurate removing of the foregrounds.Upper limits:derived from the absorptions of TeV photons from the blazars by the COB/CIB.Lower limits:from the number counts and statistical analyses (stacking, P(D)).

Measurements of the cosmic infrared background (from Bthermin+11, CRF proceeding)

Direct countsStackingTotal extrapolated contribution3SUMMARYABSOLUTE MESUREMENTS OF THE CIB

UPPER LIMITS FROM OPACITY OF THE UNIVERSE TO TEV PHOTONS

LOWER LIMITS FROM DEEP SURVEY (AND SOME TECHNICAL STUFFS ABOUT SOURCE EXTRACTION AND COUNTS)

MORE STRINGENT LOWER LIMITS BY STACKING ANALYSIS

GO DEEPER WITH P(D) ANALYSISABSOLUTE MEASUREMENTSABSOLUTE MEASUREMENTS OF THE CIB: The challenge of FOREGROUND SUBTRACTION

ABSOLUTE MEASUREMENTS OF THE CIB: The challenge of FOREGROUND SUBTRACTION

Spectral energy distribution of the background light (Matsuura+11).MODELS OF ZODIACAL EMISSION

Earth SunEarth SunEarth SunEarth SunModel of zodiacal emission in the solar system (Kelsall+98)MODELS OF ZODIACAL EMISSION

Model of zodiacal emission in the solar system (Kelsall+98)

ABSOLUTE MEASUREMENTS OF THE CIB: The challenge of FOREGROUND SUBTRACTION

SUBTRACTION OF THE GALACTIC CIRRUS EMISSIONS

Correlation between HI column density and intensity at 100 microns in IRAS data (Lagache+00)SUBTRACTION OF THE GALACTIC CIRRUS EMISSIONS

Decomposition of the HI emissivity into 3 components (Penin+12b, see also Miville-Deschnes+05)SUBTRACTION OF THE GALACTIC CIRRUS EMISSIONS

LocalIntermediate velocity cloudHigh velocity cloudSpatial distribution of HI clouds in ELAIS-N1 field (Pnin+12)

From Miville-Deschnes+05SUBTRACTION OF THE GALACTIC CIRRUS EMISSIONS

100 microns IRAS map around ELAIS-N1: all component (left), model of cirrus (center), cirrus removed (right) (Pnin+12)

UPPER LIMITS FROM HIGH ENERGY PHOTONSPHOTON-PHOTON SCATTERING

TeV photon from blazarIR EBL photone-e+Cross section of the photon-photon interaction:Minimal energy of the IR photon for interaction: 2 (mec2)2/E = 0.5 MeV2 /E

or IR (microns) 0.6 E (TeV)Details and references in e.g. Bthermin+11ABSORPTION OF BLAZAR TEV PHOTONS BY THE EBL

Spectral energy distribution of the extragalactic background light (Dole+06)100 TeV10 TeV1 TeV100 GeVAbsorption of TEV PHOTONS ALONG A LINE OF SIGHT

From Hess collaborationEFFECT ON BLAZAR SPECTRUMS

Observed and intrinsic TeV spectrum of a distant blazar (Aharaonian+06)IntrinsicObservedCompilation of blazar spectra (Kneise&Dole 10)UPPER LIMITS ON EBL SED

From Meyer+12LOWER LIMITS FROM DEEP SURVEYSResolving the CIB

Spitzer 24 microns22Resolving the CIB

Spitzer 24 microns

Galaxy number counts at 24 microns (Bthermin+10a)23Resolving the CIB

Spitzer 24 microns

Cumulative contribution of the IR galaxies to the CIB as a function of the flux cut (Bthermin+10a)

24SOURCE EXTRACTION: IN A VERY SIMPLIFIED CASELets discuss this (over-?)simplified case:The PSF is a Dirac (i.e. the flux of a source lies only in one pixel).The source density is small (i.e. less than one source per pixel).Constant Gaussian instrumental noise.

The PDF of the signal (Smes) in pixel hosting a source with a flux Si is:The probability to detect a source for a threshold Sd is:The mean flux of the detected sources with an initial flux Si is:SOURCE EXTRACTION IN A VERY SIMPLIFIED CASE

Completeness for a 5sigma thresholdFlux boosting (5 sigma threshold)

The probability to detect a source for a threshold Sd is:The mean flux of the detected sources with an initial flux Si is:Smes SdSmes SiEMPIRICAL ESTIMATION OF COMPLETENESS AND FLUX BOOSTING IN A COMPLEXE CASE

Principle of source injection (from Morgan Cousin)Step 1: inject few artificial sources in the real mapStep 2: Rerun the extraction toolStep 3: compute the completeness from the fraction of recovered sources (and the flux boosting from their mean flux).Resolving the CIB: THE PROBLEM OF THE CONFUSION

Spitzer 24 micronsCIB 80% rsolved (Bthermin+10a)28

Spitzer 160 micronsCIB 15% rsolved (Bthermin+10a)Resolving the CIB: THE PROBLEM OF THE CONFUSION29

Herschel 160 micronsCIB 70% rsolved (Berta+10)Resolving the CIB: THE PROBLEM OF THE CONFUSION30

Herschel 500 micronsCIB 6% rsolved (Oliver+10)Resolving the CIB: THE PROBLEM OF THE CONFUSION31CONFUSION LIMIT2 regimesSource density limitedFluctuation limited

In general, when source density reaches 20 beams/sourcesFluctuation due to faint sources:

CONFUSION NOISE AND CONFUSION LIMIT

1- confusion noise (top) and confusion limit (bottom) as a function of wavelength for various diameters of telescopes (Bthermin+11) Using the 24 micron observations as a prior

24 microns Spitzer250 microns Herschel34

24 microns Spitzer250 microns HerschelUsing the 24 micron observations as a prior35

24 microns Spitzer250 microns HerschelUsing the 24 micron observations as a prior36

24 microns Spitzer250 microns Herschel

Principle of the PSF-fitting photometry using a prior on positions.

Model fitted to the dataUsing the 24 micron observations as a priorThis task can be performed with several codes: DAOPHOT, Starfinder, GALFIT, FASTPHOT37MORE STRINGENT LOWER LIMIT BY STACKING

24 microns Spitzer250 microns HerschelUsing the 24 micron observations as a prior39

24 microns Spitzer250 microns HerschelUsing the 24 micron observations as a prior40Using the 24 micron observations as a prior

24 microns Spitzer250 microns Herschel

41STACKING: THE MOVIEDirected by Herv Dole

LOWER LIMIT OF THE CIB BY STACKING

Spectral energy distribution of the CIB (Dole+06)LOWER LIMIT OF THE CIB BY STACKINGSpectral energy distribution of the CIB (Dole+06)

Lower limits to the CIB in the sub-mm derived by stacking in the BLAST data (Marsden+09)LOWER LIMIT OF THE CIB BY STACKINGCounting the faint infrared sources by stackingExtragalactic number counts at 160 microns measured with Spitzer (Bthermin+10a)

COUNTS AT 160 MICRONS

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COUNTS AT 160 MICRONSstackingExtragalactic number counts at 160 microns measured with Spitzer (Bthermin+10a)Counting the faint infrared sources by stacking

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Cumulative contribution of the 160 microns sources to the CIB (Bthermin+10a)CONTRIBUTION OF THE UNRESOLVED SOURCES TO THE CIB48Biases due to the clusteringThe clustering of the 24 microns sources biases the stacking results. This bias can be >20% with Spitzer at 160 microns and with BLAST

Effect of the clustering on the stacking(from Bavouzet's thesis)Simulation including the Simulation with clustering49Correlation function and stacking

- Results of a stacking with IAS method (see Nicolas Bavouzet thesis or the annexe B of Bthermin et al. 2010b)

Biases due to clusteringAuto-correlation of the stacked populationCross-correlation with other populations

Radial profile of the results of a SPIRE stacking (Bthermin+12b)50How the clustering biases the stacking results?

Estimated on the stacking measurements due to the clustering of the sources(from Bavouzet's thesis)

Measured bias caused by clustering with SPIRE (Bthermin+12b)51Estimation of the CLUSTERING biaSMethod 1:Convolve the 24microns map by the SPIRE beam. Stack the 24 microns catalog and compare with the flux of the individual sources (PROBLEM: do not take into account the dependence of the colors and the clustering with the redshift).Method 2:You make a first stacking to estimate the color (and scatter?) of you populations. You build a simulation using the position of the real sources and the color of them. You compare the input flux and output flux to estimate the bias (PROBLEM: do not take into account the contribution of the sources not seen at 24 microns)

52Estimation of the CLUSTERING biasesMethod 3:You build a simulation from models (PROBLEM: Can we realy trust the clustering in the models?)Method 4: fit directly a clustering and a source component on stacked images.

53KURCZYNSKI & GAWIWER 2010 methodWhen you do PSF-fitting you fit this model to the map:

This method allow to estimate the fluxes (Sk) of the sources.If you assume that the flux of all a population is the same, you can estimate the flux of this population correcting the contamination due to the geometry of the sources. It is the principle of KG method.

54Bias due to the incompleteness of the input catalog

Stacking of 2uJy