اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدBayesian semi-blind component separation for foreground removal in interferometric 21-cm observations
106
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We present in this paper a new Bayesian semi-blind approach for foreground removal in observations of the 21-cm signal with interferometers. The technique, which we call HIEMICA (HI Expectation-Maximization Independent Component Analysis), is an extension of the Independent Component Analysis (ICA) technique developed for two-dimensional (2D) CMB maps to three-dimensional (3D) 21-cm cosmological signals measured by interferometers. This technique provides a fully Bayesian inference of power spectra and maps and separates the foregrounds from signal based on the diversity of their power spectra. Only relying on the statistical independence of the components, this approach can jointly estimate the 3D power spectrum of the 21-cm signal and, the 2D angular power spectrum and the frequency dependence of each foreground component, without any prior assumptions about foregrounds. This approach has been tested extensively by applying it to mock data from interferometric 21-cm intensity mapping observations under idealized assumptions of instrumental effects. We also discuss the impact when the noise properties are not known completely. As a first step toward solving the 21 cm power spectrum analysis problem we compare the semi-blind HIEMICA technique with the commonly used Principal Component Analysis (PCA). Under the same idealized circumstances the proposed technique provides significantly improved recovery of the power spectrum. This technique can be applied straightforwardly to all 21-cm interferometric observations, including epoch of reionization measurements, and can be extended to single-dish observations as well.
قيم البحث
اقرأ أيضاً
The Internal Linear Combination (ILC) component separation method has been extensively used to extract a single component, the CMB, from the WMAP multifrequency data. We generalise the ILC approach for separating other millimetre astrophysical emissi
ons. We construct in particular a multidimensional ILC filter, which can be used, for instance, to estimate the diffuse emission of a complex component originating from multiple correlated emissions, such as the total emission of the Galactic interstellar medium. The performance of such generalised ILC methods, implemented on a needlet frame, is tested on simulations of Planck mission observations, for which we successfully reconstruct a low noise estimate of emission from astrophysical foregrounds with vanishing CMB and SZ contamination.
Contamination from instrumental effects interacting with bright astrophysical sources is the primary impediment to measuring Epoch of Reionization and BAO 21 cm power spectra---an effect called mode-mixing. In this paper we identify four fundamental
power spectrum shapes produced by mode-mixing that will affect all upcoming observations. We are able, for the first time, to explain the wedge-like structure seen in advanced simulations and to forecast the shape of an EoR window that is mostly free of contamination. Understanding the origins of these contaminations also enables us to identify calibration and foreground subtraction errors below the imaging limit, providing a powerful new tool for precision observations.
Subtraction of astrophysical foreground contamination from dirty sky maps produced by simulated measurements of the Murchison Widefield Array (MWA) has been performed by fitting a 3rd-order polynomial along the spectral dimension of each pixel in the
data cubes. The simulations are the first to include the unavoidable instrumental effects of the frequency-dependent primary antenna beams and synthesized array beams. They recover the one-dimensional spherically-binned input redshifted 21 cm power spectrum to within approximately 1% over the scales probed most sensitively by the MWA (0.01 < k < 1 Mpc^-1) and demonstrate that realistic instrumental effects will not mask the EoR signal. We find that the weighting function used to produce the dirty sky maps from the gridded visibility measurements is important to the success of the technique. Uniform weighting of the visibility measurements produces the best results, whereas natural weighting significantly worsens the foreground subtraction by coupling structure in the density of the visibility measurements to spectral structure in the dirty sky map data cube. The extremely dense uv-coverage of the MWA was found to be advantageous for this technique and produced very good results on scales corresponding to |u| < 500 wavelengths in the uv-plane without any selective editing of the uv-coverage.
In this paper we present observations, simulations, and analysis demonstrating the direct connection between the location of foreground emission on the sky and its location in cosmological power spectra from interferometric redshifted 21 cm experimen
ts. We begin with a heuristic formalism for understanding the mapping of sky coordinates into the cylindrically averaged power spectra measurements used by 21 cm experiments, with a focus on the effects of the instrument beam response and the associated sidelobes. We then demonstrate this mapping by analyzing power spectra with both simulated and observed data from the Murchison Widefield Array. We find that removing a foreground model which includes sources in both the main field-of-view and the first sidelobes reduces the contamination in high k_parallel modes by several percent relative to a model which only includes sources in the main field-of-view, with the completeness of the foreground model setting the principal limitation on the amount of power removed. While small, a percent-level amount of foreground power is in itself more than enough to prevent recovery of any EoR signal from these modes. This result demonstrates that foreground subtraction for redshifted 21 cm experiments is truly a wide-field problem, and algorithms and simulations must extend beyond the main instrument field-of-view to potentially recover the full 21 cm power spectrum.
We present in this paper the PolEMICA (Polarized Expectation-Maximization Independent Component Analysis) algorithm which is an extension to polarization of the SMICA (Spectral Matching Independent Component Analysis) temperature multi-detectors mult
i-components (MD-MC) component separation method (Delabrouille et al. 2003). This algorithm allows us to estimate blindly in harmonic space multiple physical components from multi-detectors polarized sky maps. Assuming a linear noisy mixture of components we are able to reconstruct jointly the anisotropies electromagnetic spectra of the components for each mode T, E and B, as well as the temperature and polarization spatial power spectra, TT, EE, BB, TE, TB and EB for each of the physical components and for the noise on each of the detectors. PolEMICA is specially developed to estimate the CMB temperature and polarization power spectra from sky observations including both CMB and foreground emissions. This has been tested intensively using as a first approach full sky simulations of the Planck satellite polarized channels for a 14-months nominal mission assuming a simplified linear sky model including CMB, and optionally Galactic synchrotron emission and a Gaussian dust emission. Finally, we have applied our algorithm to more realistic Planck full sky simulations, including synchrotron, realistic dust and free-free emissions.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
