Changeset 3977 in Sophya
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trunk/Cosmo/RadioBeam/sensfgnd21cm.tex
r3976 r3977 100 100 } 101 101 102 \date{Received December 15, 2010; accepted xxxx, 2011}102 \date{Received June 15, 2011; accepted xxxx, 2011} 103 103 104 104 % \abstract{}{}{}{}{} … … 111 111 cm emission. Such a 3D matter distribution map can be used to test the Cosmological model and to constrain the Dark Energy 112 112 properties or its equation of state. A novel approach, called intensity mapping can be used to map the \HI distribution, 113 using radio interferometers with large instanteneous field of view and waveband }113 using radio interferometers with large instanteneous field of view and waveband.} 114 114 % aims heading (mandatory) 115 { In this paper, we study the sensitivity of different radio interferometer configuration for the observation of large scale structures116 115 { In this paper, we study the sensitivity of different radio interferometer configurations, or multi-beam 116 instruments for the observation of large scale structures and BAO oscillations in 21 cm and we discuss the problem of foreground removal. } 117 117 % methods heading (mandatory) 118 118 { For each configuration, we determine instrument response by computing the (u,v) plane (Fourier angular frequency plane) … … 124 124 LSS power spectrum, after separation of 21cm-LSS signal from the foregrounds. } 125 125 % conclusions heading (optional), leave it empty if necessary 126 { We show that a n interferometer with few hundred elements and a surface coverage of126 { We show that a radio instrument with few hundred simultaneous beamns and a surface coverage of 127 127 $\lesssim 10000 \mathrm{m^2}$ will be able to detect BAO signal at redshift z $\sim 1$ } 128 128 … … 422 422 We have set the electromagnetic (EM) phase origin at the center of the coordinate frame and 423 423 the EM wave vector is related to the wavelength $\lambda$ through the usual 424 $ | \vec{k}_{EM} | = 2 \pi / \lambda $. The receiver beam or antenna lobe $L(\vec{\Theta} )$424 $ | \vec{k}_{EM} | = 2 \pi / \lambda $. The receiver beam or antenna lobe $L(\vec{\Theta},\lambda)$ 425 425 corresponds to the receiver intensity response: 426 426 \begin{equation} 427 L(\vec{\Theta}) = B(\vec{\Theta},\lambda) \, B^*(\vec{\Theta},\lambda)427 L(\vec{\Theta}), \lambda = B(\vec{\Theta},\lambda) \, B^*(\vec{\Theta},\lambda) 428 428 \end{equation} 429 429 The visibility signal between two receivers corresponds to the time averaged correlation between … … 441 441 the common receivers axis, the visibilty would be written as the 2D Fourier transform 442 442 of the product of the sky intensity and the receiver beam, for the angular frequency 443 $2 \pi( \frac{\Delta x}{\lambda} , \frac{\Delta x}{\lambda} )$:443 \mbox{$(u,v)_{12} = 2 \pi( \frac{\Delta x}{\lambda} , \frac{\Delta x}{\lambda} )$}: 444 444 \begin{equation} 445 445 \vis(\lambda) \simeq \iint d\alpha d\beta \, \, I(\alpha, \beta) \, L(\alpha, \beta) … … 478 478 Several beam can be formed using different combination of the correlation from different 479 479 antenna pairs. 480 481 An instrument can thus be characterized by its $(u,v)$ plane coverage or response 482 ${\cal R}(u,v,\lambda)$. For a single dish with a single receiver in the focal plane, 483 the instrument response is simply the Fourier transform of the beam. 484 For a single dish with multiple receivers, either as a Focal Plane Array (FPA) or 485 a multi horn system, each beam (b) will have its own response 486 ${\cal R}_b(u,v,\lambda)$. 487 For an interferometer, we can compute a raw instrument response 488 ${\cal R}_{raw}(u,v,\lambda)$ which corresponds to $(u,v)$ plane coverage by all 489 receiver pairs with uniform weighting. 490 Obviously, different weighting schemes can be used, changing 491 the effective beam shape and thus the response ${\cal R}_{w}(u,v,\lambda)$ 492 and the noise behaviour. 480 493 481 494 \begin{figure} … … 587 600 588 601 \begin{figure} 589 \vspace*{- 10mm}602 \vspace*{-25mm} 590 603 \centering 591 604 \mbox{ 592 605 \hspace*{-10mm} 593 \includegraphics[width=0.6 \textwidth]{Figs/pnkmaxfz.pdf}606 \includegraphics[width=0.65\textwidth]{Figs/pnkmaxfz.pdf} 594 607 } 595 \vspace*{- 35mm}608 \vspace*{-40mm} 596 609 \caption{Minimal noise level for a 100 beam instrument as a function of redshift (top). 597 610 Maximum $k$ value for a 100 meter diameter primary antenna (bottom) } … … 602 615 \subsection{Instrument configurations and noise power spectrum} 603 616 604 We have numerically computed the instrument response in the (u,v) plane for several605 instrument configurations, at redshift $z=1$. 617 We have numerically computed the instrument response ${\cal R}(u,v,\lambda)$ 618 with uniform weights in the $(u,v)$ plane for several instrument configurations: 606 619 \begin{itemize} 607 620 \item[{\bf a} :] A packed array of $n=121 \, D_{dish}=5 \mathrm{m}$ dishes, arranged in … … 678 691 \bigwedge_{[\pm 2 \pi D^{ill}_y / \lambda ]} (v ) 679 692 \end{equation} 680 Figure \ref{figuvcovabcd} for the four configurations with $\sim 100$ receivers per 693 Figure \ref{figuvcovabcd} shows the instrument response ${\cal R}(u,v,\lambda)$ 694 for the four configurations (a,b,c,d) with $\sim 100$ receivers per 681 695 polarisation. The resulting projected noise spectral power density is shown in figure 682 696 \ref{figpnoisea2g}. The increase of $P_{noise}(k)$ at low $k^{comov} \lesssim 0.02$ 683 697 is due to the fact that we have ignored all auto-correlation measurements. 684 It can be seen that an instrument with $100 $ beams and $\Tsys = 50 \mathrm{K}$698 It can be seen that an instrument with $100-200$ beams and $\Tsys = 50 \mathrm{K}$ 685 699 should have enough sensitivity to map LSS in 21 cm at redshift z=1. 686 700 … … 716 730 Reaching the required sensitivities is not the only difficulty of observing the large 717 731 scale structures in 21 cm. Indeed, the synchrotron emission of the 718 Milky Way and the extra galactic radio sources isa thousand time brighter than the732 Milky Way and the extra galactic radio sources are a thousand time brighter than the 719 733 emission of the neutral hydrogen distributed in the universe. Extracting the LSS signal 720 734 using Intensity Mapping, without identifying the \HI point sources is the main challenge … … 723 737 emissions can be used to separate the faint LSS signal from the Galactic and radio source 724 738 emissions. However, any real radio instrument has a beam shape which changes with 725 frequency whichsignificantly increases the difficulty and complexity of this component separation739 frequency: this instrumental effect significantly increases the difficulty and complexity of this component separation 726 740 technique. The effect of frequency dependent beam shape is often referred to as {\em 727 741 mode mixing} \citep{morales.09}. … … 730 744 the simple models we have used for computing the sky radio emissions in the GHz frequency 731 745 range. We present also a simple component separation method to extract the LSS signal and 732 its performance. We show in particular the effect of the instrument response and possible733 way of getting around this difficulty. The results presented in this section concern the746 its performance. We show in particular the effect of the instrument response on the recovered 747 power spectrum, and possible way of getting around this difficulty. The results presented in this section concern the 734 748 total sky emission and the LSS 21 cm signal extraction in the $z \sim 0.6$ redshift range, 735 749 corresponding to the central frequency $\nu \sim 884$ MHz. 736 750 737 751 \subsection{ Synchrotron and radio sources } 738 We have modeled the radio in the form of three dimensional maps (data cubes) of sky temperature752 We have modeled the radio sky in the form of three dimensional maps (data cubes) of sky temperature 739 753 brightness $T(\alpha, \delta, \nu)$ as a function of two equatorial angular coordinates $(\alpha, \delta)$ 740 754 and the frequency $\nu$. Unless otherwise specified, the results presented here are based on simulations of … … 760 774 Frequency & 500 kHz ($d z \sim 10^{-3}$) & 256 \\ 761 775 \hline 762 \end{tabular} \\ 776 \end{tabular} \\[1mm] 763 777 Cube size : $ 90 \, \mathrm{deg.} \times 30 \, \mathrm{deg.} \times 128 \, \mathrm{MHz}$ \\ 764 778 $ 1800 \times 600 \times 256 \simeq 123 \, 10^6$ cells … … 775 789 776 790 We have thus also created a simple sky model using the Haslam Galactic synchrotron map 777 at 408 Mhz \citep{haslam. 08} and the NRAO VLA Sky Survey (NVSS) 1.4 GHz radio source791 at 408 Mhz \citep{haslam.82} and the NRAO VLA Sky Survey (NVSS) 1.4 GHz radio source 778 792 catalog \cite{nvss.98}. The sky temperature cube in this model (Model-II/Haslam+NVSS) 779 793 has been computed through the following steps: 780 794 781 795 \begin{enumerate} 782 \item The Galactic synchrotron emission is modeled as a sum of two power law.783 We assign a power law index $\beta = -2.8 \pm 0.15$ to each sky direction.796 \item The Galactic synchrotron emission is modeled power law with spatially 797 varying spectral index. We assign a power law index $\beta = -2.8 \pm 0.15$ to each sky direction. 784 798 $\beta$ has a gaussian distribution centered at -2.8 and with standard 785 799 deviation $\sigma_\beta = 0.15$. … … 790 804 \item A two dimensional $T_{nvss}(\alpha,\delta)$sky brightness temperature at 1.4 GHz is computed 791 805 by projecting the radio sources in the NVSS catalog to a grid with the same angular resolution as 792 the sky cubes is computed. The source brightness in Jansky is converted to temperature taking the793 pixel angular size into account ($ \sim 21 \mathrm{mK / mJansky}$ at 1.4 G hz and $3' \times 3'$ pixels).794 A s epctral index $\beta_{src} \in [-1.5,-2]$ is also assigned to each sky direction for the radio source806 the sky cubes. The source brightness in Jansky is converted to temperature taking the 807 pixel angular size into account ($ \sim 21 \mathrm{mK / mJansky}$ at 1.4 GHz and $3' \times 3'$ pixels). 808 A spectral index $\beta_{src} \in [-1.5,-2]$ is also assigned to each sky direction for the radio source 795 809 map; we have taken $\beta_{src}$ as a flat random number in the range $[-1.5,-2]$, and the 796 810 contribution of the radiosources to the sky temperature is computed as follow: … … 806 820 \footnote{SimLSS : {\tt http://www.sophya.org/SimLSS} }. 807 821 {\color{red}: CMV, please add few line description of SimLSS}. 808 We have generated the mass fluctuations $\delta \rho/ rho$ at $z=0.6$, in cells of size822 We have generated the mass fluctuations $\delta \rho/\rho$ at $z=0.6$, in cells of size 809 823 $1.9 \times 1.9 \times 2.8 \, \mathrm{Mpc^3}$, which correspond approximately to the 810 824 sky cube angular and frequency resolution defined above. The mass fluctuations has been 811 converted into temperature through a factor $0.13 mK$, corresponding to a hydrogen812 fraction $0.008 x(1+0.6)$. The total sky brightness temperature is then computed as the sum825 converted into temperature through a factor $0.13 \mathrm{mK}$, corresponding to a hydrogen 826 fraction $0.008 \times (1+0.6)$. The total sky brightness temperature is then computed as the sum 813 827 of foregrounds and the LSS 21 cm emission: 814 828 $$ T_{sky} = T_{sync}+T_{radsrc}+T_{lss} \hspace{5mm} OR \hspace{5mm} … … 840 854 \end{table} 841 855 842 we have computed the power spectrum onthe 21cm-LSS sky temperature cube, as well843 as onthe radio foreground temperature cubes computed using our two foreground856 we have computed the power spectrum for the 21cm-LSS sky temperature cube, as well 857 as for the radio foreground temperature cubes computed using our two foreground 844 858 models. We have also computed the power spectrum on sky brightness temperature 845 859 cubes, as measured by a perfect instrument having a 25 arcmin gaussian beam. 846 The resulting computed power spectr umare shown on figure \ref{pkgsmlss}.860 The resulting computed power spectra are shown on figure \ref{pkgsmlss}. 847 861 The GSM model has more large scale power compared to our simple model, while 848 862 it lacks power at higher spatial frequencies. The mode mixing due to … … 853 867 compared to the mK LSS signal. 854 868 869 It should also be noted that in section 3, we presented the different instrument 870 configuration noise level after {\em correcting or deconvolving} the instrument response. The LSS 871 power spectrum is recovered unaffected in this case, while the noise power spectrum 872 increases at high k values (small scales). In practice, clean deconvolution is difficult to 873 implement for real data and the power spectra presented in this section are NOT corrected 874 for the instrumental response. 875 855 876 \begin{figure} 856 877 \centering 878 \vspace*{-10mm} 857 879 \mbox{ 858 \hspace*{- 10mm}859 \includegraphics[width=0. 5\textwidth]{Figs/comptempgsm.pdf}880 \hspace*{-20mm} 881 \includegraphics[width=0.6\textwidth]{Figs/comptempgsm.pdf} 860 882 } 883 \vspace*{-10mm} 861 884 \caption{Comparison of GSM (black) Model-II (red) sky cube temperature distribution. 862 885 The Model-II (Haslam+NVSS), … … 869 892 \mbox{ 870 893 \hspace*{-10mm} 871 \includegraphics[width= \textwidth]{Figs/compmapgsm.pdf}894 \includegraphics[width=0.9\textwidth]{Figs/compmapgsm.pdf} 872 895 } 873 896 \caption{Comparison of GSM map (top) and Model-II sky map at 884 MHz (bottom). … … 883 906 \includegraphics[width=0.7\textwidth]{Figs/pk_gsm_lss.pdf} 884 907 } 885 \vspace*{- 30mm}908 \vspace*{-40mm} 886 909 \caption{Comparison of the 21cm LSS power spectrum (red, orange) with the radio foreground power spectrum. 887 910 The radio sky power spectrum is shown for the GSM (Model-I) sky model (dark blue), as well as for our simple … … 893 916 894 917 895 \subsection{ LSS signal extraction } 896 % {\color{red} \large \it CMV + Reza + J.M. Martin } \\[1mm] 897 Description of the component separation method and the results 898 \begin{itemize} 899 \item Component separation method, based on instrument response correction and frequency 900 smoothness / power law 901 \item Foreground power spectrum 902 \item Performance of component separation : comparison of frequency slices of recovered LSS 903 and foreground maps, source catalogs 904 \item Performance in statistical sense (power spectrum) : comparison of recovered P(k)-LSS 905 and true P(k), residual noise/systematic effect power spectrum 906 \end{itemize} 907 918 \subsection{ Instrument response and LSS signal extraction } 919 920 The observed data cube is obtained from the sky brightness temperature 3D map 921 $T_{sky}(\alpha, \delta, \nu)$ by applying the frequency dependent instrument response 922 ${\cal R}(u,v,\lambda)$. 923 As a simplification, we have considered that the instrument response is independent 924 of the sky direction. 925 For each frequency $\nu_k$ or wavelength $\lambda_k=c/\nu_k$ : 926 \begin{enumerate} 927 \item Apply a 2D Fourier transform to compute sky angular Fourier amplitudes 928 $$ T_{sky}(\alpha, \delta, \lambda_k) \rightarrow \mathrm{2D-FFT} \rightarrow {\cal T}_{sky}(u, v, \lambda_k)$$ 929 \item Apply instrument response in the angular wave mode plane 930 $$ {\cal T}_{sky}(u, v, \lambda_k) \longrightarrow {\cal T}_{sky}(u, v, \lambda_k) \times {\cal R}(u,v,\lambda) $$ 931 \item Apply inverse 2D Fourier transform to compute the measured sky brightness temperature map, 932 without instrumental (electronic/$\Tsys$) white noise: 933 $$ {\cal T}_{sky}(u, v, \lambda_k) \times {\cal R}(u,v,\lambda) 934 \rightarrow \mathrm{Inv-2D-FFT} \rightarrow T_{mes1}(\alpha, \delta, \lambda_k) $$ 935 \item Add white noise (gaussian fluctuations) to obtain the measured sky brightness temperature 936 $T_{mes}(\alpha, \delta, \nu_k)$. We have also considered that the system temperature and thus the 937 additive white noise level was independent of the frequency or wavelength. 938 \end{enumerate} 939 The LSS signal extraction depends indeed on the white noise level. 940 The results shown here correspond to the (a) instrument configuration, a packed array of 941 $11 \times 11 = 121$ 5 meter diameter dishes, with a white noise level corresponding 942 to $\sigma_{noise} = 0.25 \mathrm{mK}$ per $3 \times 3 \mathrm{arcmin^2} \times 500 kHz$ 943 cell. 944 945 Our simple component separation procedure is described below: 946 \begin{enumerate} 947 \item The measured sky brightness temperature is first corrected for the frequency dependent 948 beam effects through a convolution by a virtual, frequency independent beam. We assume 949 that we have a perfect knowledge of the intrinsic instrument response. 950 $$ T_{mes}(\alpha, \delta, \nu) \longrightarrow T_{mes}^{bcor}(\alpha,\delta,\nu) $$ 951 The virtual target instrument has a beam width larger to the worst real instrument beam, 952 i.e at the lowest observed frequency. 953 \item For each sky direction $(\alpha, \delta)$, a power law $T = T_0 \left( \frac{\nu}{\nu_0} \right)^b$ 954 is fitted to the beam-corrected brightness temperature. $b$ is the power law index and $10^a$ 955 is the brightness temperature at the reference frequency $\nu_0$: 956 \begin{eqnarray*} 957 P1 & : & \log10 ( T_{mes}^{bcor}(\nu) ) = a + b \log10 ( \nu / \nu_0 ) \\ 958 P2 & : & \log10 ( T_{mes}^{bcor}(\nu) ) = a + b \log10 ( \nu / \nu_0 ) + c \log10 ( \nu/\nu_0 ) ^2 959 \end{eqnarray*} 960 \item The difference between the beam-corrected sky temperature and the fitted power law 961 $(T_0(\alpha, \delta), b(\alpha, \delta))$ is our extracted 21 cm LSS signal. 962 \end{enumerate} 963 964 Figure \ref{extlsspk} shows the performance of this procedure at a redshift $\sim 0.6$, 965 for the two radio sky models used here: GSM/Model-I and Haslam+NVSS/Model-II. The 966 21 cm LSS power spectrum, as seen by a perfect instrument with a gaussian frequency independent 967 beam is shown in orange (solid line), and the extracted power spectrum, after beam correction 968 and foreground separation with second order polynomial fit (P2) is shown in red (circle markers). 969 We have also represented the obtained power spectrum without applying the beam correction (step 1 above), 970 or with the first order polynomial fit (P1). 971 972 It can be seen that a precise knowledge of the instrument beam and the beam correction 973 is a key ingredient for recovering the 21 cm LSS power spectrum. It is also worthwhile to 974 note that while it is enough to correct the beam to the lowest resolution instrument beam 975 ($\sim 30'$ or $D \sim 50$ meter @ 820 MHz) for the GSM model, a stronger beam correction 976 has to be applied (($\sim 36'$ or $D \sim 40$ meter @ 820 MHz) for the Model-II to reduce 977 significantly the ripples from bright radio sources. The effect of mode mixing is reduced for 978 an instrument with smooth (gaussian) beam, compared to the instrument response 979 ${\cal R}(u,v,\lambda)$ used here. 980 981 Figure \ref{extlssratio} shows the overall {\em transfer function} for 21 cm LSS power 982 spectrum measurement. We have shown (solid line, orange) the ratio of measured LSS power spectrum 983 by a perfect instrument $P_{perf-obs}(k)$, with a gaussian beam of $\sim$ 36 arcmin, respectively $\sim$ 30 arcmin, 984 in the absence of any foregrounds or instrument noise, to the original 21 cm power spectrum $P_{21cm}(k)$. 985 The ratio of the recovered LSS power spectrum $P_{ext}(k)$ to $P_{perf-obs}(k)$ is shown in red, and the 986 ratio of the recovered spectrum to $P_{21cm}(k)$ is shown in black (thin line). 987 988 \begin{figure*} 989 \centering 990 \vspace*{-20mm} 991 \mbox{ 992 \hspace*{-20mm} 993 \includegraphics[width=1.1\textwidth]{Figs/extlsspk.pdf} 994 } 995 \vspace*{-30mm} 996 \caption{Power spectrum of the 21cm LSS temperature fluctuations, separated from the 997 continuum radio emissions at $z \sim 0.6$. 998 Left: GSM/Model-I , right: Haslam+NVSS/Model-II. } 999 \label{extlsspk} 1000 \end{figure*} 1001 1002 1003 \begin{figure*} 1004 \centering 1005 \vspace*{-20mm} 1006 \mbox{ 1007 \hspace*{-20mm} 1008 \includegraphics[width=1.1\textwidth]{Figs/extlssratio.pdf} 1009 } 1010 \vspace*{-30mm} 1011 \caption{Power spectrum of the 21cm LSS temperature fluctuations, separated from the 1012 continuum radio emissions at $z \sim 0.6$. 1013 Left: GSM/Model-I , right: Haslam+NVSS/Model-II. } 1014 \label{extlssratio} 1015 \end{figure*} 908 1016 909 1017 \section{ BAO scale determination and constrain on dark energy parameters} … … 911 1019 We compute reconstructed LSS-P(k) (after component separation) at different z's 912 1020 and determine BAO scale as a function of redshifts. 913 We can this a large number of time ( ~ 100 \ldots 1000 ) to have the reconstructed P(k) 914 with {\it realistic } errors. We can then determine the error on the reconstructed DE 915 parameters 1021 Method: 1022 \begin{itemize} 1023 \item Compute/guess the overall transfer function for several redshifts (0.5 , 1.0 1.5 2.0 2.5 ) \\ 1024 \item Compute / guess the instrument noise level for the same redshit values 1025 \item Compute the observed P(k) and extract $k_{BAO}$ , and the corresponding error 1026 \item Compute the DETF ellipse with different priors 1027 \end{itemize} 1028 916 1029 917 1030 \section{Conclusions}
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