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Matched Filter Search for Ionized Bubbles in 21-cm Maps Kanan K. Datta Dept. of Astronomy Stockholm University Oskar Klein Centre

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Collaborators Somnath Bharadwaj Tirthankar Roy Choudhury Suman Majumdar

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21 cm observations of the reionization : Major Approaches 1)Global evolution of average redshifted 21 cm differential brightness temperature with redshift. (Ravi Subramanians talk) 2)The rms, skewness measurement as a function of redshift. (Garrelt Mellemas talk) 3)Measuring HI power spectrum. (Abhik Ghosh, Somnath Bharadwaj, Stuart Wyithes talk) 4)Cross Correlation (Brigs, T. Guha Sarkars talk) 5) Detecting Individual Ionized Bubbles

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HI

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Can we detect individual ionized bubbles in 21-cm observations?

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Motivation for Individual Bubble detection Direct probe of reionization. Interpretation is easier. IGM properties (HI fraction surrounding the HII regions) Source properties (age, photon emission rate ) This will compliment the study through power spectrum measurements

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A Visibility based method Direct measured quantity is Visibility Noise in the image is correlated, where as in visibility it is uncorrelated. Advantages over the image base method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator A Visibility based method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator Total Observed visibility A Visibility based method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator Filter A Visibility based method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator Summation over all baselines and frequency channels A Visibility based method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator Analytically the mean also can be calculated using A Visibility based method

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To optimally combine the signal from an ionized bubble of radius R_b at redshift z_c we introduce an estimator Analytically the mean also can be calculated using A Visibility based method Baseline Distribution function

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Simulating Signal Dark Matter map

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Assume HI traces Dark matter with bias 1 HI map Simulating Signal

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Assume HI traces Dark matter with bias 1 We put spherical ionized bubbles by hand with one at the centre. Simulating Signal

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Assume HI traces Dark matter with bias 1 We put spherical ionized bubbles by hand with one at the centre. Simulating Signal

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Assume HI traces Dark matter with bias 1 We put spherical ionized bubbles by hand with one at the centre. Simulating Signal

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Simulate dark matter distribution at redshift 6 Grid size=2 Mpc, Box size=256 Mpc (GMRT), 512 Mpc (MWA) Assume HI traces Dark matter with bias 1 We put spherical ionized bubbles by hand with one at the centre. Simulating Signal

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SB PR1 PR2 Simulated maps

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Simulating visibilities

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Effect of the HI fluctuations

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Baseline distribution

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Matched Filter The signal to noise ratio (SNR) is maximum if we use the filter exactly matched with the signal from the bubble that we are trying to detect ie.,

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Matched Filter The signal to noise ratio (SNR) is maximum if we use the filter exactly matched with the signal from the bubble that we are trying to detect ie., The filter subtracts out any frequency independent component from the frequency range the frequency range To remove the foreground contribution we modify the filter as,

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Results Restriction on bubble detection: Detection of bubbles of radius >8 Mpc for GMRT is possible. HI fluctuations will affect Small bubble detection (

ERLR that redshift range 7-9.2 and 8.8-10.8 We find that redshift range 7-9.2 and 8.8-10.8 are the most appropriate for the GMRT and the MWA respectively. A 3 sigma detection is possible with the GMRT for bubbles > 50 Mpc or >30 Mpc for 1000 hrs of integration time for ER or LR models. The same figure is >40 Mpc and >30 Mpc for the MWA. Optimal Redshift Datta, Bharadwaj, Choudhury, MNRAS, 2009

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Conclusions We developed a technique for detecting individual ionized bubbles in 21-cm maps. The technique maximizes the SNR and subtracts out foregrounds. A 3 sigma detection is possible with instruments like GMRT, LOFAR, MWA for bubbles > 50 Mpc or >30 Mpc for ~1000 hrs of integration time for ER or LR models. Bubble size can be determined which will give crucial information about reionizing source properties Blind search for bubbles is, in principle possible. Detailed study with simulated signal, foregrounds, noise etc needs to be done.

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Thank You