2012
DOI: 10.1111/j.1365-2966.2012.21065.x
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Foreground removal usingfastica: a showcase of LOFAR-EoR

Abstract: We introduce a new implementation of the fastica algorithm on simulated Low Frequency Array Epoch of Reionization data with the aim of accurately removing the foregrounds and extracting the 21‐cm reionization signal. We find that the method successfully removes the foregrounds with an average fitting error of 0.5 per cent and that the 2D and 3D power spectra are recovered across the frequency range. We find that for scales above several point spread function scales, the 21‐cm variance is successfully recovered… Show more

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Cited by 189 publications
(188 citation statements)
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“…Thus, the EoR signal can be extracted by fitting out the smooth component of the foregrounds along the frequency direction. This can be achieved by using polynomials (e.g., Santos et al 2005;Wang et al 2006;McQuinn et al 2006;Bowman et al 2006;Jelić et al 2008, and references therein), or more advanced non-parametric methods (Harker et al 2009a;Chapman et al 2012Chapman et al , 2013). However, one should be careful in using polynomials.…”
Section: Removalmentioning
confidence: 99%
See 1 more Smart Citation
“…Thus, the EoR signal can be extracted by fitting out the smooth component of the foregrounds along the frequency direction. This can be achieved by using polynomials (e.g., Santos et al 2005;Wang et al 2006;McQuinn et al 2006;Bowman et al 2006;Jelić et al 2008, and references therein), or more advanced non-parametric methods (Harker et al 2009a;Chapman et al 2012Chapman et al , 2013). However, one should be careful in using polynomials.…”
Section: Removalmentioning
confidence: 99%
“…If the order of the polynomial is set too large, the EoR signal could be fitted out. Hence, in principle it is better to fit the foregrounds non-parametrically -allowing the data to determine their shape -rather than selecting some functional form in advance and then fitting its parameters (Harker et al 2009a;Chapman et al 2012). In addition, fitting directly to the visibilities rather than the image cubes might be another avenue to remove foregrounds.…”
Section: Removalmentioning
confidence: 99%
“…In a recent paper, Chapman et al (2014) have compared different frequency window functions to conclude that the extended Blackman-Nuttall window is the best choice for recovering the HI power spectrum. For the present work we have used the Blackman-Nuttall window as given by eq.…”
Section: Frequency Window Functionmentioning
confidence: 99%
“…The foregrounds are smooth along frequency in total intensity and might show fluctuations in polarized intensity. Therefore, the EoR signal can be extracted from the foreground emission by fitting out the smooth component of the foregrounds along frequency, as shown for the LOFAR case by Jelić et al (2008);Harker et al (2009);Chapman et al (2012Chapman et al ( , 2013.…”
Section: Foreground Emission In the Lofar-eor Experimentsmentioning
confidence: 99%