2-Day IDAPP meeting INAF-IASF Bologna Student: Pietro Procopio Dr. Carlo Burigana University of Ferrara Dr. Nazzareno Mandolesi Internal tutor: External tutor: CMBR Spectrum - Foreground Analysis - Component Separation First Year Activities External co-tutor Dr. Jacques Delabrouille

Brief summary CMBR and spectral distortions: a precise numerical code CMBR and foregrounds A new release of the IRAS map: IRIS and angular power spectrum analysis Conclusion and prospectives      Component Separation: the stage in Paris

Cosmic Microwave Background Radiation Anisotropies Angular power spectrum Polarization P 2 = Q 2 + U 2 Example: Scattering Thomson of radiation with quadrupole anisotropy generates linear polarization Spectrum Photon distribution function

CMBR SPECTRUM T 0 = ± °K (Mather et al. 1999) Redshift Dimensioneless frequency Has the CMBR a black body spectrum?

Spectral distortions In the primordial universe some processes can lead the matter-radiation fluid out of the thermal equilibrium ( energy dissipation because of density fluctuations,Physical processes out of the equilibrium, radiative decay of particles, energy release related to the first stages of structures formation, free-free distortions) The photon distribution function isn’t a Planckian one The Kompaneets equation in cosmological contest provides the best tool to compute the evolution of the photon distribution function, but a numerical code is needed! KYPRIX An extremely precise fortran based code, able to simulate the effects of the primordial physical processes that can affect the thermodynamic equilibrium of the CMBR

KYPRIX How does it work? Subroutine for boundary cond. in point A D03PCF Discretization of the Kompaneets Increasing time y Subroutine for boundary cond. in point B FUNCTION For specific phys. quant. Cosmic exp Output files  (,t) Integral quan. Input parameters a)cosmological par. b)integration par. MAIN PROGRAM Initialization of the solution vector U Subroutine PDEDEF Discretization in the x axis Computation of the rates of the physical processes

KYPRIX’ update(s) update related to the NAG libraries* sensitivity e efficiency increased** introduction of the cosmological constant** 2006 CPU platform transfer (still in progress) activity update related to the relative abundances of H and He introduction of the ionization fraction of e - ‘90 first KYPRIX release by Carlo Burigana * Updating a numerical code for the solution of the Kompaneets equation in cosmological context, P.Procopio and C.Burigana, INAF-IASF Bologna, Internal Report, 419; **Accuracy and performance of a numerical code for the solution of hte Kompaneets equation in cosmological context, P.Procopio and C.Burigana, INAF-IASF Bologna, Internal Report, 420;

Cosmological applications BIG BANG z today z term z BE z ric z Superposition of black bodies where Primordial distortions Late distortions Related (mainly) to the reionization history of the universe Free-free distortions Bose-Einstein like spectrum with µ function of X Cosmological application of a numerical code for the solution of the Kompaneets equation, P.Procopio and C.Burigana, INAF-IASF Bologna, Internal Report, 421;

Cosmological application Distortions dued to reionization of the universe at low redshifts Ω m = 1 Ω  = 0 Ω m = 0.29 Ω  = 0.73 One of the rapresentative cases

Reionization Nowday, the most precise measurements related to the parameters of the standard model (of the universe) are those realized by the NASA satellite WMAP optical depth of the universe  =0.09±0.03 (3-years WMAP data) Effects of a reionization are visible in all the properties of the CMBR: --- Temperature anisotropies suppression at high multipoles* --- gain of power in T-E cross-correlation PS and in the E and B modes mainly at low and middle multipoles --- raising of free-free and compotonization like distortions in the spectrum Given that, we need a performing tool able to simulate the stages of evolution of the reionization as better as possible not only for effects related to the anisotropies, but also for what concern the CMBR spectrum *Planck-LFI scientific goals: implications for the reionization history L.Popa, C.Burigana, N.Mandolesi,…,P.Procopio,et. al., Publ. By New Astronomy

CMBR and Foregrounds 2 main classes Galactic foregrounds Synchrotron emission Dust emission Free-free emission + anomalus component + dark matter annihilation + diffuse emission with origin in the solar system (ZLE) + discrete components From radio to IR Extragalactic foregrounds AGNRadio sources - Flat and steep spectrum Far-IR galaxies Dust emission (primordial galaxies) From radio to far-IR SZ effect

The dust emission Diffuse morphology in our Galaxy  Detection and characteristic frequency ranges  H  region - Survey IR and far-IR Dust emission dominates at  70 GHz, both in temperature and polarization 2 components model  d≈nm emission at  6-60  m d≥0.1  m emission at >100  m Thermal emission  Typical spectrum is a modified BB: I(,T d )≈  B(,T d ) ≈  +2 in RJ regime with  ≈1; FIRAS,WMAP  ≈2

The Infrared Astronomical Satellite (IRAS) Impact on many areas of modern astrophysics It revealed the ubiquity of infrared cirrus that are a spectacular manifestation of the interstellar medium complexity but also an important foreground for observational cosmology With the forthcoming Planck* satellite there is a need for all-sky complementary data sets with arcminute resolution that can bring informations on specific foreground emissions that contaminate the CMB radiation With its ~4' resolution it matches perfectly the high-frequency bands of Planck* * The Low Frequency Instrument on board the Planck satellite: characteristics and performance L.Valenziano, M.Sandri, G.Morgante,…..,P. Procopio, et. al., Publ. By New Astronomy * The Planck LFI RCA Flight Model test campaign L.Terenzi, F.Villa, A.Mennella,…,P.Procopio,et. al., Publ. By New Astronomy

The IRIS maps It is a new generation of IRAS images It benefits from a better zodiacal light subtraction, from a calibration and zero level compatible with DIRBE, and from a better destriping Main features of the IRIS data

Tests The aim of the analisys is to get a better knowledge of the statistical properties of this component of the foregrounds that affect the measurement of the cosmic signal About the first release of the IRIS maps… Not in galactic coordinates Covering the 98% of the sky, extended to 100% using DIRBE data set at frequencies of interest Loss of power when rotating from equatorial coord. to galactic (not related to the map itself) Residuals of ZLE after its subtraction (still present)

Tests Tools: IDL + HEALPix fortran & IDL facilities + anafast Galactic cut at different |b| (with 2 different method) “Galactic keep” at different |b| Separeted APS for north and south emisphere, each of Them at different |b| WMAP Galactic masks Comparison with between the 100  m map and the Schlegel map Maps: in Galactic coord. Nside = 1024 resolution  4’ MJy/sr We started with computing the angular power spectrum of the map in several cases of Galactic cut

Some APS Angular power spectrum of the 100µm map with a Galactic cut equal to |b|=5° Same as above, But with a cut |b|=60° B cut 30 C l of the map with cut At |b|=60°

After the tests The target is to reach a good knowledge of the statistical properties of this component of the galactic foreground. Knowing correlation function, behaviour of the angular power spectrum of different patches of the sky is useful in understanding how to model (maybe a bit better) the dust emission properties across the sky, i.e. his behaviour with respect the galactic latitude. Then, performing local analysis one can find out cleaner zones of the sky, where the contamination of this component is less prominent, with clear advantages for observational sessions.

Component Separation Signals and images contain contributions from several components or sources. Component separation consist in separating the emission of interest from all the other components present in the data set The most popular CS model in CMB analysis is the linear mixture: all components are assumed to have an emission which can be decomposed as the product of a spatial template indipendent of the frequency of observation and of a spectral emission law which does not depend on the pixel.

The Spectral Matching method Multi Detector Multi Component Analysis Blind separation and SMICA Our analysis Our data set The aim is that to recover the CIB from a set of infrared maps, to separate and recognize the Galactic dust emission, to fix problems related to residual in ZLE subtraction. Possibly to realize a better destriping of IRAS maps. IRIS maps (12, 25, 60, 100 micron) IRAS maps (by which the IRIS maps were derived) DIRBE (only the channels with these fequencies)

Preliminary analysis Starting using SMICA Comparison of the zero level between IRAS maps and DIRBE maps Checking for holes in the maps Finding out relevant differencies between maps of different frequency 4 frequencies + 2 (then 3) different map sets = 8 (12) maps Sources detection and subtraction Finding the right masking map for all the maps Repixelization of te DIRBE data set …

Conclusions Spectral distortions are not simple to detect, the signal is very low and to get the sensitivity needed it is required a fine calibration with a reference BB and great control of systematic. A study about observational experiment from the Moon is in progress: no atmosphere = great results from ground based experiments. With KYPRIX and other codes like CMBfast we have a complete set of instruments to probe the primordial universe in a theoretical way. Identifying and mapping the emission of all the astrophysical processes that a Planck like satellite will detect is one of the most important step in the exploitation of CMB data analysis. We are going into the era of high precision cosmology, so we have to know in the best possible way how to deal with contamination generated by our own Galaxy. The work on component separation is about T, but new cosmology is also pointing to the polarization signal of the CMBR: we’ll stay tuned!