2009
DOI: 10.1088/1475-7516/2009/07/011
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Reconstruction of the primordial power spectrum using temperature and polarisation data from multiple experiments

Abstract: We develop a method to reconstruct the primordial power spectrum, P (k), using both temperature and polarisation data from the joint analysis of a number of Cosmic Microwave Background (CMB) observations. The method is an extension of the Richardson-Lucy algorithm, first applied in this context by Shafieloo & Souradeep [1]. We show how the inclusion of polarisation measurements can decrease the uncertainty in the reconstructed power spectrum. In particular, the polarisation data can constrain oscillations in t… Show more

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Cited by 82 publications
(72 citation statements)
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“…There is no fundamental limit to how densely P R (k) can be sampled though; the number of samples in k can even exceed the number of data points (e.g., the C s) if one is willing to forgo the possibility of an analysis based on exploring the likelihood/posterior and treat the issue as a deconvolution problem (i.e., an inversion of Equation 128) instead. Deconvolution techniques have been applied by several groups to CMB temperature data [492][493][494][495][496][497], CMB temperature+polarisation data [498][499][500] and combinations of CMB data with large scale structure data [501]. In order to get rid of spurious high-frequency spikes that are likely to occur for noisy data when the primordial spectrum is oversampled, these methods typically involve a smoothing procedure.…”
Section: Bottom-up: Reconstruction Of the Primordial Power Spectrummentioning
confidence: 99%
“…There is no fundamental limit to how densely P R (k) can be sampled though; the number of samples in k can even exceed the number of data points (e.g., the C s) if one is willing to forgo the possibility of an analysis based on exploring the likelihood/posterior and treat the issue as a deconvolution problem (i.e., an inversion of Equation 128) instead. Deconvolution techniques have been applied by several groups to CMB temperature data [492][493][494][495][496][497], CMB temperature+polarisation data [498][499][500] and combinations of CMB data with large scale structure data [501]. In order to get rid of spurious high-frequency spikes that are likely to occur for noisy data when the primordial spectrum is oversampled, these methods typically involve a smoothing procedure.…”
Section: Bottom-up: Reconstruction Of the Primordial Power Spectrummentioning
confidence: 99%
“…However, there is no independent evidence for this form of the primordial power, and as the observed anisotropies arise as a convolution of the assumed primordial spectrum with the transfer function of the assumed cosmological model, it is clear that we cannot determine one without making assumptions about the other. (In fact, there are indications that the primordial spectrum is not scale-free, even when a ÃCDM cosmology is assumed [74][75][76][77][78][79][80][81][82][83]. )…”
Section: Primordial Power Spectramentioning
confidence: 99%
“…These include the "cosmic inversion" method [9][10][11][12][13], regularization methods like truncated singular value decomposition [14] and Richardson-Lucy iteration [3,15,16], and maximum entropy deconvolution [17]. Recently the authors of [18] carried out a reconstruction of the PPS employing Tikhonov regularization using multiple data sets and detected several features in the PPS at a 2σ level of significance (also compare [3]).…”
Section: Introductionmentioning
confidence: 99%