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Thesis Defense Talk

Tuhin Ghosh (IUCAA)Tuhin Ghosh (IUCAA)

under the supervision ofunder the supervision of

Prof. Tarun Souradeep (IUCAA)Prof. Tarun Souradeep (IUCAA) 5th of March, 2012

Galactic and Cosmological Signalsin the Microwave BackgroundAnisotropy and Polarization

Courtesy: Planck

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List of Publications

1. Tuhin Ghosh, Anthony John Banday, Tess Jaffe, Clive Dickinson, Rod Davies, Richard Davis and Krzysztof Gorski Foreground Analysis Using Cross-Correlations of External Templates on WMAP7 accepted in MNRAS, astro-ph/1112.0509

2. Tuhin Ghosh, Jacques Delabrouille, Mathieu Ramazeilles, Jean Francois Cardoso and Tarun Souradeep Foreground maps in Wilkinson Microwave Anisotropy Probe frequency bands Monthly Notices of the Royal Astronomical Society, 412, 883, 2011.

3. Tuhin Ghosh, Rajib Saha, Pankaj Jain and Tarun Souradeep Model Independent Foreground Power Spectrum Estimation using WMAP 5-year Data Phys. Rev. D 79, 123011, 2009.

4. Tuhin Ghosh, Amir Hajian and Tarun Souradeep, Unveiling Hidden Patterns in CMB Anisotropy Maps Phys. Rev. D 75, 083007, 2007.

5. Tuhin Ghosh, Anthony John Banday, Tess Jaffe, Clive Dickinson, Rod Davies, Richard Davis and Krzysztof Gorski Effect of ILC subtraction on Template Based Foreground Analysis (in preparation).

6. Tuhin Ghosh, Jean Francois Cardoso, Simon Prunet and Tarun Souradeep, Statistics of Foregrounds in Spherical Needlet Basis (in preparation).

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Outline of the Thesis

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Main Highlights of the Thesis

Spectral characterisation of foregrounds

- Evidence of spinning dust emission in the WMAP 7 yr data - The derived mean electron temperature is of the order ~ 6000-8000 K (considerably higher than WMAP results which is between 4000-5000 K) - The WIM spinning dust emission has a peak intensity between 40-50 GHz. - Compared the DDD and Finkbeiner Halpha template and explained the artifacts in the templates and how it biases the spectral properties of foregrounds Statistical properties of foregrounds

- The marginals and the conditional distribution between two needlet scales follows a ``Student's t- distribution'' Foreground Power Spectrum Estimation

- The model specific MEM method used by WMAP Team overestimates the foreground power close to Galactic Plane and underestimates the foreground power at high latitudes relative to our model independent method

Morphology of the foregrounds

- We provide a WMAP derived foreground maps by using popular technique called Wiener filtering and subtracting the needlet ILC map. We made the foreground maps available in public domain.

CMB power spectrum estimation

- We developed a method to estimate CMB power spectrum employing the clever strategy to remove the source of bias in existing ILC method

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Wilkinson Microwave Anisotropy Probe (WMAP)

The Wilkinson Microwave Anisotropy Probe (WMAP) was a NASA Explorer mission that launched June 2001 to make fundamental measurements of cosmology -- the study of the properties of our universe as a whole.

WMAP had been stunningly successful, producing our new Standard Model of Cosmology.

WMAP measures the microwave sky at five frequency bands ranging from 23 GHz to 94 GHz with highest angular beam resolution of 13 arcminute.

WMAP Satellite (2001-2010)

Jarosik et al., ApJS, 192, 2011

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WMAP 5 Frequency Maps23 GHz 33 GHz

41 GHz 61 GHz

94 GHz

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Temperature Dependence of Foreground Emissions

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High Frequency Foregrounds (Planck Frequencies)

Cosmic Infrared Background

Infrared Point Sources

CO lines

Molecular H2 gas

Zodical Light

WMAP Haze

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Planck Collaboration Early Results

Planck Collaboration, A & A, 536, A20

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Spectral Characterization of Foregrounds

WMAP observations: 20-100 GHz

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Spectral Characterization of Foregrounds

WMAP observations: 20-100 GHz

1633 Regions of Interest EBV Mask

Cross-Correlation Analysis

The cross-correlation measure, , between a data vector, d and a template vector t can be measured by minimizing,

where MSN is the covariance matrix including both signal and noise for the template-corrected data vector.

T i(p)= Tc(p)+X

j

SijTfj (p)+ T i

N (p)

Tuhin Ghosh et al., MNRAS accepted, astro-ph/1112.0509

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Synchrotron Emission

Model SI: Power law emisitivity in terms brightness temperature over the WMAP frequencies.

Model SII: Single power law emissivity is assumed to extend from 408 MHz.

Model SIII: The emissivity is assumed to follow a power law model from 408 MHz until K-band and then to exhibit spectral curvature.

Tuhin Ghosh et al., MNRAS accepted, astro-ph/1112.0509

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Free-free Emission

Model FI: Power-law model emissivity with a fixed spectral index (-2.15).

Model FII: Power-law model emissivity with variable spectral index.

Model FIII: Combination of free-free emission and a spinning dust model for a typical warm ionised medium (WIM).

Dobler and Finkbeiner, ApJ, 680, 2008 Tuhin Ghosh et al., MNRAS accepted,

astro-ph/1112.0509

Free-free amplitude at 23 GHz is proportional to mean electron temperature

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Dust Emission

Model DI: The dust coefficients are fitted with a combination of thermal dust and power law dust-correlated AME.

Model DII: The dust coefficients are fitted with a combination of thermal dust and two spinning dust components consisting of Cold Neutral Medium (CNM) and Warm Neutral Medium (WNM).

Tuhin Ghosh et al., MNRAS accepted, astro-ph/1112.0509

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Summary Slide

Early 2003

2011

Synchrotron

Free-freeDust

Tuhin Ghosh et al., MNRAS accepted, astro-ph/1112.0509

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Large Errorbar (Correlated CMB Signal)

Tuhin Ghosh et al., PRD, 123011, 2009

CMB

Foreground Power Spectrum(outside the Galactic plane)

33 GHz

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Tegmark & Efstathiou 96, Tegmark 2003, Saha et al. 2005, 2008

Internal Linear Combination (ILC)

Harmonic space: (l,m) : Spherical harmonic coefficients

Pixel space: (\theta,\phi) : Temperature in real space

Needlet space: (j,k) : Needlet coefficients at given scale j at pixel k

For each frequency channel, i :

Linear combinations of maps of different frequency channels, i.

CMB anisotropy is achromatic :

(Such that CMB signal is untouched in the final map )

Determine weights such that it minimizes

the total power

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Three basis functions are commonly used in CMB analysis:

Pixel Space: foreground and noise are uncorrelated in pixel space but signal correlated. Harmonic Space: signal is uncorrelated but foregrounds are correlated. Needlet Space: Localized both in harmonic as well as pixel space. Advantage for non-stationary signal analysis like foregrounds.

[1]Pietrobon et al. 2008, astro-ph/0809.0010[2]Marinucci et al. 2007, astro-ph/0707.0844

Needlet Basis

Pixel Space Harmonic SpaceNeedlet Space

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Foreground Map at WMAP Frequency Bands

Tuhin Ghosh et al., MNRAS 412,883,2011

Total Map

Needlet ILC Map

Total - Needlet ILC Map Foreground Map

23 GHz

33 GHz

Identification of point sources

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Optimal Approach in case of ILC subtraction

ILC Estimate of the CMB signal

The composite frequency spectrum get distorted by ILC subtraction. The distortion is a constant factor in terms on thermodynamic temperature which can be easily taken into account. Due to the ILC subtraction, the correlated CMB get replaced by the correlated noise coming from ILC subtraction.

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Optimal Approach (Continued ...)

In classical approach, one frequency map is fitted with N template maps.

Synchrotron coefficients are:

In optimal approach, M frequency map is directly fitted with N template maps.

Synchrotron model parameters: Non-linear Fitting

In case of ILC subtraction,

Synchrotron model parameters:

Noise covariance matrix

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Effect of ILC Subtraction (Simulations)

Input Amplitudes:

Dust : 9.0 uK/uKFree-free: 9.0 uK/RSynchrotron: 5.0 uK/K

Recovered Amplitude:

1) CMB included analysis

Dust: 8.98+/-1.02 uK/uKFree-free: 8.99+/-0.52 uK/RSynchrotron: 5.09+/-2.61 uK/K

2) CMB excluded analysis

Dust: 9.00+/-0.03 uK/uKFree-free: 9.00+/-0.57 uK/RSynchrotron: 5.00+/-0.07 uK/K

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Main Results of Optimal Approach after CMB Subtraction

1. The average spectral index of synchrotron emission over K- to W-band is -2.92. The spectral indices varies over the sky which ranges between -2.75 to -3.3.

2. The regions analysed close to the Galactic plane are consistent with electron temperature between 5500 to 9000 K. The derived electron temperature of 7000 K from radio recombination line studies of extended HII regions in the vicinity of solar neighborhood (Alves et al. 2011, Banday et al. 2003).

3. More than 9 regions shows a significant detection of WIM spinning dust emission (dominated from regions close to Galactic Plane).

4. We studied the impact of dust extinction using the optimal approach. If we assume the electron temperature to be ~7000 K, the constraint on dust absorption correction is f_d < 0.3.

5. The dust emission is fitted well with a combination of well understood thermal dust emission and the combination of two spinning dust model arising from warm neutral medium and cold neutral medium.

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Statistical Characterization of CMB Foregrounds

Saha, ApJ, 739, 2011

1. Study the non-Gaussianity coming from local patches due to residual foregrounds.

2. Denoising the foreground template.

3. Incorporated the statistics in Component Separation Method.

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Statistical Characterization of Gaussian Map in Needlet space

P(X)

P(Y,X)

Coarser Scale Finer Scale

X : Parent Scale Coefficients

Y : Child Scale Coefficients

P(X) : Distribution of Parent scale

P(Y) : Distribution of Child scale

P(Y|X) : Conditional distribution

P(Y,X) : Joint Distribution

P(Y|X)

Tuhin Ghosh, J.-F. Cardoso, S. Prunet, T. Souradeep

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P(Y,X)

P(Y|X)

P(X)

SFD 100 micron map

Statistical Characterization of Foreground Map in Needlet space

Tuhin Ghosh, J.-F. Cardoso, S. Prunet, T. Souradeep

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Conclusions

1. We developed a “optimal approach” to extract the foreground parameters directly from the given multifrequency maps. The method is unbiased and is a powerful toolto study the spectral characteristics of foregrounds.

2. We found the evidence of spinning dust emission in WMAP7 yr data.

2. We report the marginal distribution and conditional distribution of needlet coefficients follows the ''Student's t-distribution” in case of foregrounds.

3. We present a blind CMB power spectrum estimation method called Direct Angular Power Spectrum (DAPSE) based on minimal assumptions using a clever strategy to remove the source of bias exists in standard ILC method in harmonic space.

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Future Directions

Planck Surveyor mission of European Space Agency (ESA) (2009 – present)

Planck produce high resolution full sky maps of temperature and polarisation anisotropy.

Currently working as a Planck HFI associate.

Applying all the techniques used in my thesis to quantifythe foregrounds from Planck.

Planck Collaboration produces more than 28 papers just on CMB foregrounds in early 2011.

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For each frequency channel, i :

Linear combinations of maps of different frequency channels, i.

CMB anisotropy is achromatic :

(Such that CMB signal is untouched in the final map )

Determine weights such that it minimizes

the total power

Internal Linear Combination (ILC)

Bias Issues in ILC method

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DAPSE : Redressing the bias issues in IPSE(Direct Angular Power Spectrum Estimation)

Bias arises when foreground & noisedominate over common angular scales-- weights are influenced by noise(Analytic study: Saha et al. PRD 08)

Cross Power Spectra:

Chiang et al., ApJ, 738, 2011

Linearly combine the cross-power spectrum With suitable weights in such a way that the variance of cross-power spectrum get minimized and weights sums to unity

White Noise Cross Power Spectrum

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DAPSE (continued ...)

TT Power Spectrum TE Power Spectrum

EE Power Spectrum

Tuhin Ghosh, S. Prunet, T. Souradeep