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Deciphering the CIB Banyuls 08/10/2012 RESOLVING THE CIB: I) METHODS TO IDENTIFY THE SOURCES RESPONSIBLE FOR THE CIB Matthieu Bthermin CEA Saclay

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THE EXTRAGALACTIC BACKGROUND LIGHT (EBL) SED of the extragalactic background light (from Dole & Bthermin, in prep.)

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MEASUREMENTS OF THE COSMIC INFRARED BACKGROUND (CIB) LEVEL Absolute 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 countsStacking Total extrapolated contribution

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SUMMARY ABSOLUTE 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) ANALYSIS

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ABSOLUTE MEASUREMENTS

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ABSOLUTE MEASUREMENTS OF THE CIB: THE CHALLENGE OF FOREGROUND SUBTRACTION

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Spectral energy distribution of the background light (Matsuura+11).

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

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

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ABSOLUTE MEASUREMENTS OF THE CIB: THE CHALLENGE OF FOREGROUND SUBTRACTION

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

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

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SUBTRACTION OF THE GALACTIC CIRRUS EMISSIONS Local Intermediate velocity cloud High velocity cloud Spatial distribution of HI clouds in ELAIS-N1 field (Pnin+12) From Miville-Deschnes+05

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

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UPPER LIMITS FROM HIGH ENERGY PHOTONS

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PHOTON-PHOTON SCATTERING TeV photon from blazar IR EBL photon e- e+ Cross section of the photon-photon interaction: Minimal energy of the IR photon for interaction: 2 (m e c 2 ) 2 /E = 0.5 MeV 2 /E or IR (microns) 0.6 E (TeV) Details and references in e.g. Bthermin+11

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ABSORPTION OF BLAZAR TEV PHOTONS BY THE EBL Spectral energy distribution of the extragalactic background light (Dole+06) 100 TeV 10 TeV 1 TeV 100 GeV

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ABSORPTION OF TEV PHOTONS ALONG A LINE OF SIGHT From Hess collaboration

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EFFECT ON BLAZAR SPECTRUMS Observed and intrinsic TeV spectrum of a distant blazar (Aharaonian+06) Intrinsic Observed Compilation of blazar spectra (Kneise&Dole 10)

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UPPER LIMITS ON EBL SED From Meyer+12

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LOWER LIMITS FROM DEEP SURVEYS

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RESOLVING THE CIB Spitzer 24 microns

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RESOLVING THE CIB Spitzer 24 microns Galaxy number counts at 24 microns (Bthermin+10a)

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RESOLVING THE CIB Spitzer 24 microns Cumulative contribution of the IR galaxies to the CIB as a function of the flux cut (Bthermin+10a)

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SOURCE EXTRACTION: IN A VERY SIMPLIFIED CASE Lets 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:

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SOURCE EXTRACTION IN A VERY SIMPLIFIED CASE Completeness for a 5sigma threshold Flux 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 Sd Smes Si

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EMPIRICAL 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 map Step 2: Rerun the extraction tool Step 3: compute the completeness from the fraction of recovered sources (and the flux boosting from their mean flux).

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RESOLVING THE CIB: THE PROBLEM OF THE CONFUSION Spitzer 24 microns CIB 80% rsolved (Bthermin+10a)

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Spitzer 160 microns CIB 15% rsolved (Bthermin+10a) RESOLVING THE CIB: THE PROBLEM OF THE CONFUSION

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Herschel 160 microns CIB 70% rsolved (Berta+10) RESOLVING THE CIB: THE PROBLEM OF THE CONFUSION

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Herschel 500 microns CIB 6% rsolved (Oliver+10) RESOLVING THE CIB: THE PROBLEM OF THE CONFUSION

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CONFUSION LIMIT 2 regimes Source density limited Fluctuation limited In general, when source density reaches 20 beams/sources Fluctuation due to faint sources:

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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)

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USING THE 24 MICRON OBSERVATIONS AS A PRIOR 24 microns Spitzer250 microns Herschel

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24 microns Spitzer250 microns Herschel USING THE 24 MICRON OBSERVATIONS AS A PRIOR

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24 microns Spitzer250 microns Herschel USING THE 24 MICRON OBSERVATIONS AS A PRIOR

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24 microns Spitzer250 microns Herschel Principle of the PSF-fitting photometry using a prior on positions. Model fitted to the data USING THE 24 MICRON OBSERVATIONS AS A PRIOR This task can be performed with several codes: DAOPHOT, Starfinder, GALFIT, FASTPHOT

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MORE STRINGENT LOWER LIMIT BY STACKING

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24 microns Spitzer250 microns Herschel USING THE 24 MICRON OBSERVATIONS AS A PRIOR

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24 microns Spitzer250 microns Herschel USING THE 24 MICRON OBSERVATIONS AS A PRIOR

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24 microns Spitzer250 microns Herschel

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STACKING: THE MOVIE Directed by Herv Dole

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

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

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Lower limits to the CIB in the sub-mm derived by stacking in the BLAST data (Marsden+09) LOWER LIMIT OF THE CIB BY STACKING

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COUNTING THE FAINT INFRARED SOURCES BY STACKING Extragalactic number counts at 160 microns measured with Spitzer (Bthermin+10a) COUNTS AT 160 MICRONS

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stacking Extragalactic 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 CIB

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BIASES DUE TO THE CLUSTERING The 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 clustering

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CORRELATION 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 clustering Auto-correlation of the stacked population Cross-correlation with other populations Radial profile of the results of a SPIRE stacking (Bthermin+12b)

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HOW 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)

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ESTIMATION OF THE CLUSTERING BIAS Method 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)

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ESTIMATION OF THE CLUSTERING BIASES Method 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.

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KURCZYNSKI & GAWIWER 2010 METHOD When 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.

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BIAS DUE TO THE INCOMPLETENESS OF THE INPUT CATALOG Stacking of 2uJy