The scale of the problem: Recovering images of reionization with generalized morphological component analysis

Emma Chapman, Filipe B. Abdalla, J. Bobin, J. L. Starck, Geraint Harker, Vibor Jelić, Panagiotis Labropoulos, Michiel A. Brentjens, Saleem Zaroubi, A. G. de Bruyn, L. V.E. Koopmans

פרסום מחקרי: פרסום בכתב עתמאמרביקורת עמיתים


The accurate and precise removal of 21-cm foregrounds from Epoch of Reionization (EoR) redshifted 21-cm emission data is essential if we are to gain insight into an unexplored cosmological era.We apply a non-parametric technique, Generalized Morphological Component Analysis (GMCA), to simulated Low Frequency Array (LOFAR)-EoR data and show that it has the ability to clean the foregrounds with high accuracy. We recover the 21-cm 1D, 2D and 3D power spectra with high accuracy across an impressive range of frequencies and scales. We show that GMCA preserves the 21-cm phase information, especially when the smallestspatial scale data is discarded. While it has been shown that LOFAR-EoR image recovery istheoretically possible using image smoothing, we add thatwavelet decomposition is an efficientway of recovering 21-cm signal maps to the same or greater order of accuracy with more flexibility. By comparing the GMCA output residual maps (equal to the noise, 21-cm signal and any foreground fitting errors) with the 21-cm maps at one frequency and discarding the smaller wavelet scale information, we find a correlation coefficient of 0.689, compared to 0.588 for the equivalently smoothed image. Considering only the pixels in a central patch covering 50 per cent of the total map area, these coefficients improve to 0.905 and 0.605, respectively, and we conclude that wavelet decomposition is a significantly more powerful method to denoise reconstructed 21-cm maps than smoothing.

שפה מקוריתאנגלית
עמודים (מ-עד)165-176
מספר עמודים12
כתב עתMonthly Notices of the Royal Astronomical Society
מספר גיליון1
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 11 פבר׳ 2013
פורסם באופן חיצוניכן

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