Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userOptimal Image Reconstruction in Radio Interferometry
341
0
0.0
(
0
)
Added by
Benjamin D. Wandelt
Publication date
2006
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We introduce a method for analyzing radio interferometry data which produces maps which are optimal in the Bayesian sense of maximum posterior probability density, given certain prior assumptions. It is similar to maximum entropy techniques, but with an exact accounting of the multiplicity instead of the usual approximation involving Stirlings formula. It also incorporates an Occam factor, automatically limiting the effective amount of detail in the map to that justified by the data. We use Gibbs sampling to determine, to any desired degree of accuracy, the multi-dimensional posterior density distribution. From this we can construct a mean posterior map and other measures of the posterior density, including confidence limits on any well-defined function of the posterior map.
rate research
Read More
Astronomical optical interferometers (OI) sample the Fourier transform of the intensity distribution of a source at the observation wavelength. Because of rapid atmospheric perturbations, the phases of the complex Fourier samples (visibilities) cannot be directly exploited , and instead linear relationships between the phases are used (phase closures and differential phases). Consequently, specific image reconstruction methods have been devised in the last few decades. Modern polychromatic OI instruments are now paving the way to multiwavelength imaging. This paper presents the derivation of a spatio-spectral (3D) image reconstruction algorithm called PAINTER (Polychromatic opticAl INTErferometric Reconstruction software). The algorithm is able to solve large scale problems. It relies on an iterative process, which alternates estimation of polychromatic images and of complex visibilities. The complex visibilities are not only estimated from squared moduli and closure phases, but also from differential phases, which help to better constrain the polychromatic reconstruction. Simulations on synthetic data illustrate the efficiency of the algorithm.
In radio interferometry imaging, the gridding procedure of convolving visibilities with a chosen gridding function is necessary to transform visibility values into uniformly sampled grid points. We propose here a parameterised family of least-misfit gridding functions which minimise an upper bound on the difference between the DFT and FFT dirty images for a given gridding support width and image cropping ratio. When compared with the widely used spheroidal function with similar parameters, these provide more than 100 times better alias suppression and RMS misfit reduction over the usable dirty map. We discuss how appropriate parameter selection and tabulation of these functions allow for a balance between accuracy, computational cost and storage size. Although it is possible to reduce the errors introduced in the gridding or degridding process to the level of machine precision, accuracy comparable to that achieved by CASA requires only a lookup table with 300 entries and a support width of 3, allowing for a greatly reduced computation cost for a given performance.
This paper presents a detailed analysis of the applicability and benefits of baseline dependent averaging (BDA) in modern radio interferometers and in particular the Square Kilometre Array (SKA). We demonstrate that BDA does not affect the information content of the data other than a well-defined decorrelation loss for which closed form expressions are readily available. We verify these theoretical findings using simulations. We therefore conclude that BDA can be used reliably in modern radio interferometry allowing a reduction of visibility data volume (and hence processing costs for handling visibility data) by more than 80%.
Most statistical tools used to characterize the complex structures of the interstellar medium can be related to the power spectrum, and therefore to the Fourier amplitudes of the observed fields. To tap into the vast amount of information contained in the Fourier phases, one may consider the probability distribution function (PDF) of phase increments, and the related concepts of phase entropy and phase structure quantity. We use these ideas here with the purpose of assessing the ability of radio-interferometers to detect and recover this information. By comparing current arrays such as the VLA and Plateau de Bure to the future ALMA instrument, we show that the latter is definitely needed to achieve significant detection of phase structure, and that it will do so even in the presence of a fair amount of atmospheric phase fluctuations. We also show that ALMA will be able to recover the actual amount of phase structure in the noise-free case, if multiple configurations are used.
We realize and model a Rydberg-state atom interferometer for measurement of phase and intensity of radio-frequency (RF) electromagnetic waves. A phase reference is supplied to the atoms via a modulated laser beam, enabling atomic measurement of the RF waves phase without an external RF reference wave. The RF and optical fields give rise to closed interferometric loops within the atoms internal Hilbert space. In our experiment, we construct interferometric loops in the state space ${ 6P_{3/2}, 90S_{1/2}, 91S_{1/2}, 90P_{3/2} }$ of cesium and employ them to measure phase and intensity of a 5 GHz RF wave in a room-temperature vapor cell. Electromagnetically induced transparency on the $6S_{1/2}$ to $6P_{3/2}$ transition serves as an all-optical interferometer probe. The RF phase is measured over a range of $pi$, and a sensitivity of 2 mrad is achieved. RF phase and amplitude measurements at sub-millimeter optical spatial resolution are demonstrated.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
