相关论文: Multi-Detector Multi-Component spectral matching a…

We present a new method for multi-component power spectra estimation in multi-frequency observations of the CMB. Our method is based on matching a model to the cross and auto power spectra of observed maps. All the component power spectra…

We present a blind multi-detector multi-component spectral matching method for all sky observations of the cosmic microwave background, working on the spherical harmonics basis. The method allows to estimate on a set of observation maps the…

We have developed a fast, accurate and generally applicable method for inferring the power spectrum and its uncertainties from maps of the cosmic microwave background (CMB) in the presence of inhomogeneous and correlated noise. For maps…

We present an extension of the harmonic-space maximum-entropy component separation method (MEM) for multi-frequency CMB observations that allows one to perform the separation with more plausible assumptions about the receiver noise and…

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are 1) conditional…

In recent years the goal of estimating different cosmological parameters precisely has set new challenges in the effort to accurately measure the angular power spectrum of CMB. This has required removal of foreground contamination as well…

We develop a novel method to separate the components of a diffuse emission process based on an association with the energy spectra. Most of the existing methods use some information about the spatial distribution of components, e.g.,…

We perform a blind multi-component analysis of the WMAP 1 year foreground cleaned maps using SMICA (Spectral Matching Independent Component Analysis). We provide a new estimate of the CMB power spectrum as well as the amplitude of the CMB…

We present a new blind formulation of the Cosmic Microwave Background (CMB) inference problem. The approach relies on a phenomenological model of the multi-frequency microwave sky without the need for physical models of the individual…

We propose a solution to the CMB component separation problem based on standard parameter estimation techniques. We assume a parametric spectral model for each signal component, and fit the corresponding parameters pixel by pixel in a…

We address the extended problem of component separation for CMB applications when a mixture of both astrophysical and instrumental components are present in the observations, and show how standard methods can be adapted to handle this more…

The Correlated Component Analysis (CCA) allows us to estimate how the different diffuse emissions mix in CMB experiments, exploiting also complementary information from other surveys. It is especially useful to deal with possible additional…

We present a technique for the blind separation of components in CMB data. The method uses a spectral EM algorithm which recovers simultaneously component templates, their emission law as a function of wavelength, and noise levels. We test…

The signal measured by an astronomical spectrometer may be due to radiation from a multi-component mixture of plasmas with a range of physical properties (e.g. temperature, Doppler velocity). Confusion between multiple components may be…

We discuss new techniques and ideas in mm-wave instrumentation that can be used in CMB (Cosmic Microwave background) polarization experiments. Novel techniques in antenna receiver, beam combining and detector systems have resulted in…

Multipole vectors and pseudoentropies provide powerful tools for a numerically fast and vivid investigation of possible statistically anisotropic, respectively non-Gaussian signs in CMB temperature fluctuations. After reviewing and linking…

Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of `multi-fold' or `multi-dimensional' covariance mapping. Explicit formulae…

Multimodal manifold modeling methods extend the spectral geometry-aware data analysis to learning from several related and complementary modalities. Most of these methods work based on two major assumptions: 1) there are the same number of…

We present a new approach to component separation in multifrequency CMB experiments by formulating the problem as that of partitioning the sky into pixel clusters such that within each pixel cluster the foregrounds have similar spectrum,…

In this work we deal with the problem of simultaneous multifrequency detection of extragalactic point sources in maps of the Cosmic Microwave Background. We apply a linear filtering technique that uses spatial information and the…