arXiv subjects

Ata Karakci

Publications and source records attributed to Ata Karakci.

8 recordsLinked to original sources

arXiv2018

PASIPHAE: A high-Galactic-latitude, high-accuracy optopolarimetric survey

PASIPHAE (the Polar-Areas Stellar Imaging in Polarization High-Accuracy Experiment) is an optopolarimetric survey aiming to measure the linear polarization from millions of stars, and use these to create a three-dimensional tomographic map of the magnetic field threading dust clouds within the Milky Way. This map will provide invaluable information for future CMB B-mode experiments searching for inflationary gravitational waves, providing unique information regarding line-of-sight integration effects. Optical polarization observations of a large number of stars at known distances, tracing the same dust that emits polarized microwaves, can map the magnetic field between them. The Gaia mission is measuring distances to a billion stars, providing an opportunity to produce a tomographic map of Galactic magnetic field directions, using optical polarization of starlight. Such a map will not only boost CMB polarization foreground removal, but it will also have a profound impact in a wide range of astrophysical research, including interstellar medium physics, high-energy astrophysics, and evolution of the Galaxy. Taking advantage of the novel technology implemented in our high-accuracy Wide-Area Linear Optical Polarimeters (WALOPs) currently under construction at IUCAA, India, we will engage in a large-scale optopolarimetric program that can meet this challenge: a survey of both northern and southern Galactic polar regions targeted by CMB experiments, covering over 10,000 square degrees, which will measure linear optical polarization of over 360 stars per square degree (over 3.5 million stars, a 1000-fold increase over the state of the art). The survey will be conducted concurrently from the South African Astronomical Observatory in Sutherland, South Africa in the southern hemisphere, and the Skinakas Observatory in Crete, Greece, in the north.

astro-ph.IM↗

arXiv2017

A 3-D model of polarised dust emission in the Milky Way

We present a three-dimensional model of polarised galactic dust emission that takes into account the variation of the dust density, spectral index and temperature along the line of sight, and contains randomly generated small scale polarisation fluctuations. The model is constrained to match observed dust emission on large scales, and match on smaller scales extrapolations of observed intensity and polarisation power spectra. This model can be used to investigate the impact of plausible complexity of the polarised dust foreground emission on the analysis and interpretation of future CMB polarisation observations.

astro-ph.CO↗

arXiv2016

Bayesian semi-blind component separation for foreground removal in interferometric 21-cm observations

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.

astro-ph.CO↗

arXiv2014

Simulation of the analysis of interferometric microwave background polarization data

We present results from an end-to-end simulation pipeline interferometric observations of cosmic microwave background polarization. We use both maximum-likelihood and Gibbs sampling techniques to estimate the power spectrum. In addition, we use Gibbs sampling for image reconstruction from interferometric visibilities. The results indicate the level to which various systematic errors (e.g., pointing errors, gain errors, beam shape errors, cross- polarization) must be controlled in order to successfully detect and characterize primordial B modes as well as other scientific goals. In addition, we show that Gibbs sampling is an effective method of image reconstruction for interferometric data in other astrophysical contexts.

astro-ph.CO↗

arXiv2013

Probabilistic image reconstruction for radio interferometers

We present a novel, general-purpose method for deconvolving and denoising images from gridded radio interferometric visibilities using Bayesian inference based on a Gaussian process model. The method automatically takes into account incomplete coverage of the uv-plane, signal mode coupling due to the primary beam, and noise mode coupling due to uv sampling. Our method uses Gibbs sampling to efficiently explore the full posterior distribution of the underlying signal image given the data. We use a set of widely diverse mock images with a realistic interferometer setup and level of noise to assess the method. Compared to results from a proxy for point source- based CLEAN method we find that in terms of RMS error and signal-to-noise ratio our approach performs better than traditional deconvolution techniques, regardless of the structure of the source image in our test suite. Our implementation scales as O(np log np), provides full statistical and uncertainty information of the reconstructed image, requires no supervision, and provides a robust, consistent framework for incorporating noise and parameter marginalizations and foreground removal.

astro-ph.IM↗

arXiv2013

Maximum likelihood analysis of systematic errors in interferometric observations of the cosmic microwave background

We investigate the impact of instrumental systematic errors in interferometric measurements of the cosmic microwave background (CMB) temperature and polarization power spectra. We simulate interferometric CMB observations to generate mock visibilities and estimate power spectra using the statistically optimal maximum likelihood technique. We define a quadratic error measure to determine allowable levels of systematic error that do not induce power spectrum errors beyond a given tolerance. As an example, in this study we focus on differential pointing errors. The effects of other systematics can be simulated by this pipeline in a straightforward manner. We find that, in order to accurately recover the underlying B-modes for r=0.01 at 28<l<384, Gaussian-distributed pointing errors must be controlled to 0.7^\circ rms for an interferometer with an antenna configuration similar to QUBIC, in agreement with analytical estimates. Only the statistical uncertainty for 28<l<88 would be changed at ~10% level. With the same instrumental configuration, we find the pointing errors would slightly bias the 2-σupper limit of the tensor-to-scalar ratio r by ~10%. We also show that the impact of pointing errors on the TB and EB measurements is negligibly small.

astro-ph.CO↗

arXiv2013

Systematic Effects in Interferometric Observations of the CMB Polarization

The detection of the primordial $B$-mode spectrum of the polarized cosmic microwave background (CMB) signal may provide a probe of inflation. However, observation of such a faint signal requires excellent control of systematic errors. Interferometry proves to be a promising approach for overcoming such a challenge. In this paper we present a complete simulation pipeline of interferometric observations of CMB polarization, including systematic errors. We employ two different methods for obtaining the power spectra from mock data produced by simulated observations: the maximum likelihood method and the method of Gibbs sampling. We show that the results from both methods are consistent with each other, as well as, within a factor of 6, with analytical estimates. Several categories of systematic errors are considered: instrumental errors, consisting of antenna gain and antenna coupling errors, and beam errors, consisting of antenna pointing errors, beam cross-polarization and beam shape (and size) errors. In order to recover the tensor-to-scalar ratio, $r$, within a 10% tolerance level, which ensures the experiment is sensitive enough to detect the $B$-signal at $r=0.01$ in the multipole range $28 < \ell < 384$, we find that, for a QUBIC-like experiment, Gaussian-distributed systematic errors must be controlled with precisions of $|g_{rms}| = 0.1$ for antenna gain, $|ε_{rms}| = 5 \times 10^{-4}$ for antenna coupling, $δ_{rms} \approx 0.7^\circ$ for pointing, $ζ_{rms} \approx 0.7^\circ$ for beam shape, and $μ_{rms} = 5 \times 10^{-4}$ for beam cross-polarization.

astro-ph.CO↗

arXiv2013

Bayesian Inference of Polarized CMB Power Spectra from Interferometric Data

Detection of B-mode polarization of the cosmic microwave background (CMB) radiation is one of the frontiers of observational cosmology. Because they are an order of magnitude fainter than E-modes, it is quite a challenge to detect B-modes. Having more manageable systematics, interferometers prove to have a substantial advantage over imagers in detecting such faint signals. Here, we present a method for Bayesian inference of power spectra and signal reconstruction from interferometric data of the CMB polarization signal by using the technique of Gibbs sampling. We demonstrate the validity of the method in the flat-sky approximation for a simulation of an interferometric observation on a finite patch with incomplete uv-plane coverage, a finite beam size and a realistic noise model. With a computational complexity of O(n^{3/2}), n being the data size, Gibbs sampling provides an efficient method for analyzing upcoming cosmology observations.

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