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Deciphering the CIB Banyuls 09/10/2012

Resolving the CIB: II) statistical properties of sources responsible for CIB from observational and modeling point of view. Deciphering the CIB Banyuls 09/10/2012. Matthieu Béthermin CEA Saclay.

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Deciphering the CIB Banyuls 09/10/2012

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  1. Resolving the CIB:II) statistical properties of sources responsible for CIB from observational and modeling point of view Deciphering the CIB Banyuls 09/10/2012 Matthieu BétherminCEA Saclay

  2. Origins of the infrared output of the galaxies (e.g. star formation vs accretion, which star formation mode?)---> physics of galaxies Global evolution of the statisticalproperties of the infrared galaxies---> cosmology Whatmakes the CIB?

  3. SUMMARY Properties of resolved sources Observational point of view Origin of the CIB SED What information can you extract from the number counts Modeling point of view Principle of backward evolution models Properties of the sources responsible for CIB as predicted by empirical models

  4. OBSERVATIONAL POINT OF VIEW

  5. Redshift distribution of resolved sources Redshift distribution of resolved 24 microns sources in COSMOS (Le Floc’h+09)

  6. Redshift distribution of resolved sources Redshift distrbution of the sources detected by PACS at 100 (top) and 160 (bottom) microns (Berta+11) Redshift distrbution of the sources detected by SPIRE at 250 (blue), 350 (green) and 500 (red) microns (Béthermin+12b)

  7. BUILD-UP OF THE CIB at 24 MICRONS CIB build-up as a function of redshift at 24 microns(Le Floc’h+09) Contribution of the various redshift to the 24 microns counts (Le Floc’h+09)

  8. Redshift distribution of the CIB (LOWER LIMITS) Left: redshift distribution of the CIB from 24 microns and lower limits from Spitzer stacking and PACS (Jauzac+11). Right: lower limits from SPIRE stacking (Béthermin+12b).

  9. COUNTS PER Z SLICE BY STACKING AND CIB BUILD-UP IN THE SUB-MM DOMAIN Resolved SPIRE number counts (Béthermin+12b)

  10. Measured color per S24 and z slices. The scatter is estimated with a bootstrap method: From the mean color and scatter (assumed to be log-normal), we convert the 24 microns flux into SPIRE flux. Several realizations are used to estimate the uncertainties. Correction of completeness taking into account the flux cut at 24 microns. COUNTING SOURCES BELOW THE CONFUSION LIMIT BY stacking analysis Incompleteness due to the 24 microns flux cut cut for different scatter (Béthermin+12b).

  11. COUNTS PER Z SLICE BY STACKING AND CIB BUILD-UP IN THE SUB-MM DOMAIN Number counts built by stacking (Béthermin+12b) Cumulative contribution to the CIB as a function of the flux cut (Béthermin+12b)

  12. COUNTS PER Z SLICE BY STACKING AND CIB BUILD-UP IN THE SUB-MM DOMAIN Number counts per redshift slice built by stacking (Béthermin+12b) CIB build-up from counts per redshift slice(Béthermin+12b)

  13. Spectral energydiStribution of the CIB Empirical spectral energy distribution of the CIB (Béthermin+12b)

  14. MODELING POINT OF VIEW

  15. Whatcanwelearn FROM NUMBER COUNTS? The case of the bright-end where Euclidian approximation is valid The volume where you can detect A source with a luminosity densityLnu is The number of sources per luminosity density bin and brighter than a flux cut Snu is thus: So, the total number of sources brighter thaSnuin the sky is If you prefer differential number counts, just compute the derivative:

  16. Whatcanwelearn FROM NUMBER COUNTS? The case of the bright-end (Euclidian part) Euclidian level of the bright counts as a function of wavelength/frequency (Planck collaboration 2012)

  17. Whatcanwelearn FROM NUMBER COUNTS? Numbercountsat160 et 500 microns in various cases Complexevolution in luminosity and density Euclidianwithoutevolution ΛCDM, withevolution, flat spectrum Evolution of luminosity in (1+z)^2.5 ΛCDM, withoutevolution, realisticspectra Evolution of luminosity in (1+z)^3.5 Countsat 160 and 500 microns for variousevolutions

  18. Start from our local knowledge on the IR galaxies (Luminosity Function, SEDs...) Use an evolution of the luminosity function to reproduce the observations (and sometimes an evolution of the luminosity-temperature relation with z) Reproduce nicely the observations. BUT, give not physical interpretation. Based on halo model evolving from primordial fluctuations Use semi-analytical recipes to describe how the galaxies formed in the dark halos. Need Top-Heavy IMF to reproduce the sub-mm observations. Give a physical interpretation of the galaxy evolution. Modeling the EVOLUTION OF infraredgalaxies 2 approaches: Backwards evolution: Semi-analytical:

  19. PRINCIPLE OF THE BACKWARD EVOLUTION MODELS Type I AGN Type II AGNStarbursts Spiral Evolution of the luminosity function used by the model of Franceschini+10

  20. PRINCIPLE OF THE BACKWARD EVOLUTION MODELS Type I AGN Type II AGNStarbursts Spiral SED templates used in the model of Franceschini+10

  21. MANY PRE-HERSCHEL EMPIRICAL MODELS

  22. … whichfail to repoduce the some new observations Numbercountsat 500 microns (Oliver et al. 2010) => No model reproduce the countsatboth Herschel wavelengths.

  23. Building a «as simple as possible» model whichreproduce the new infrared observations → no AGN (low contribution), simple parametrization of IR galaxyevolution. MCMC minimisation to obtain the betterparameters (for a givenparametrization) and study the degeneracies. A NEW GENERATION OF MCMC MODELS (Bethermin+11, MaRSDEN+11)

  24. The luminosityfunction The transition between normal and starburst templates is driven by Infraredbolometricinfraredluminosityfunctionused by the model (Béthermin+11). We use the following parametrization of the IR LF:

  25. Evolution in density and in luminosity in: rL and rphi can change at 2 specific redshift zbreak1 (free parameter) and zbreak2 (fixed at z=2). We use the Lagache+04 templates to compute the flux observed by the different instruements. Evolution of the luminosity function Evolution in density Evolution in luminosity

  26. 2 populations: normal and starbursts. The normal templates do not evolve with LIR. The starburst tempapltes evolves with LIR. The Lagache et al. Infrared galaxy templates Spectral energy distribution of starburst galaxy templates for different infrared luminosity.

  27. Cosmologicalcontext SED libraries Local luminosityfunction (LF) Evolution of the LF Observables to fit INGREDIENT OF THE MODEL 13 free parameters

  28. We fit number counts at 24, 70, 160, 250, 350, 500 and 1100 microns +LFs+FIRAS CIB This fit is performed with a MCMC algorithm. MCMC fit of the observedcounts and LFs Chi2 = 177 for 113 degrees of freedom Extragalactic number counts at 250, 350 and 500 microns (Béthermin+11)

  29. Confidence region of the variousparameters of the model(Béthermin+11) Ajustement des comptages à 24, 70, 160, 250, 350, 500, et 1100 microns + qq LFs+ CIB FIRAS Ajustement réalisé par méthode MCMC. α Résultat: ajustement des comptages -5 σ -6 rΦ,mz L* -7 Φ* -8 rL,lz rL,lz 1, 2 et 3 sigma rΦ,lz 4 5 6 rL,mz zb,1 Evolution in density and luminosityatintermediateredshift rL,mz χ2 = 177 pour 113 degrés de liberté rΦ,mz rL,hz rΦ,hz Lpop Comptages extragalactique à 24, 160, 350, et 1100 microns (adapté de Béthermin et al. 2011) σpop rΦ,lz rΦ,lz Lpop rL,lz zb,1 rL,mz rΦ,mz rL,hz rΦ,hz σpop α σ L* Φ*

  30. Evolution of the characteristicluminosity and density Evolution of the characteristicdensities and luminosities (Béthermin+11)

  31. Strong increase of the infrared output from z=0 to z=1. z<0.5: dominated by normal galaxies. 0.5<z<1.5: dominated by LIRGs z>1.5: dominated by ULIRG. Evolution of the star formation rate Evolution of the infraredluminositydensity (and the star formation rate) and contribution of the differentluminoisty classes (Béthermin+11)

  32. COMPARISON WITH MARSDEN+11 MODEL Evolution in density and luminosity of the IR LF (Marsden+11) Evolution of the star formation rate density as a function of redshift (Marsden+11)

  33. LINKS between NUMBER COUNTS, CIB INTENSITY AND SMALL SCALE FLUCTUATIONS The intensity of the background can be computed with: The level of the Poisson fluctuation (in Jy^2/sr or an equivalent unit) can computed from: The Poisson level of the cross-power-spectrum between a band A and B is:

  34. LINKS between NUMBER COUNTS, CIB INTENSITY AND SMALL SCALE FLUCTUATIONS The intensity of the background can be computed with: The level of the Poisson fluctuation (in Jy^2/sr or an equivalent unit) can computed from: The Poisson level of the cross-power-spectrum between a band A and B is:

  35. Origins of the CIB SED of the CIB and contribution per redshift slice (up) and luminosity slice (down) (Béthermin+11)

  36. POISSON LEVEL OF THE FLUCTUATIONS: OBSERVATIONS VERSUS MODELS Level of Poisson fluctuations of the CIB as a function of the flux cut (Viero+12)

  37. Compute emissivities FOR MODELS OF CIB ANISOTROPIES Emissivity of IR galaxies as a function of redshift at various wavelength predicted from Béthermin+11 model (Pénin+12a)

  38. CONCLUSION • There are more and more constraints on the redshift distribution of the source responsible for the CIB. These constraints come from resolved sources below 160 microns and stacking at larger wavelength. • The number counts also provide strong constraints on the evolution of the IR galaxies. The various possible evolution can be explore through MCMC analyses. • The results shows that high redshift CIB is dominated by ULIRGs. The mean redshift of the CIB increase with wavelength.

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