Fig. 1:
The Very Large Array (VLA) is a collection of 27 radio antennas located
on the plains of San Augustin near Socorro, New Mexico, each with a dish
25 meters in diameter and weighing more than 200 tons. The data from all
antennas can be combined electronically so that the array effectively
functions as one giant antenna. Image courtesy of NRAO/AUI
Fig. 2:
This is a false colour image of the region surrounding the W28 supernova
remnant with the radio emission detected with the VLA shown in blue. The
more compact objects north and south of W28 are regions of ionized
hydrogen not directly related to the remnant. The new image
reconstruction method will make it much easier to reconstruct
interferometry images of such extended sources. Credit: NRAO/AUI/NSF and Brogan et al.
Fig. 3:
A simulated observation of a galaxy cluster with the VLA. The image on
the top left shows the (real) input signal. The top right image shows
the reconstruction using the RESOLVE algorithm. The image on the bottom
left shows a reconstruction with a standard algorigthm (CLEAN) while the
image on the bottom right gives the relative uncertainty of the
reconstruction, note the different scale on this map.
Radio astronomers obtain extremely high resolution sky images by using
interferometers, instruments where several single radio telescopes are
linked together. However, optimal data analysis procedures for such an
instrument are significantly more involved than for a single
telescope. Scientists from the Max Planck Institute for Astrophysics
have now developed the algorithm RESOLVE which solves a number of
outstanding problems in radio imaging.
Using radio interferometers, scientists look into the deepest depths
of the Universe. These instruments deliver high-resolution images of
many different celestial objects, ranging from the Sun, over pulsars,
and the interstellar gas in the Milky Way, to distant sources such as
radio galaxies or quasars. The high-resolution radio images of such
objects often reveal their complex and extended structure.
Indeed, most of the radio emission from celestial sources originates
in extended cosmic plasma clouds, glowing only faintly to the observer
on Earth. In consequence, such extended regions of emission are
difficult to detect, since they have to be separated from unwanted
interferences as e.g. electronic noise from terrestrial technical
equipment or atmospheric effects.
Furthermore, imaging in radio interferometry is inherently more
complicated as for a single telescope. This is because an
interferometer does not detect the celestial sources directly, instead
the signals from different detectors are electronically
superimposed. To reconstruct the original signal from the data, a so
called Fourier transformation needs to be applied, usually implying
complex calculations on the computer. Unfortunately, standard imaging
methods have the drawback that they often only produce unreliable
results for weak and extended emission. Moreover, due to the complex
nature of the interferometric observation, in general an estimation of
the measurement uncertainty was unreliable so far as well.
In two recent publications, the new imaging algorithm RESOLVE ("Radio
Extended Sources Lognormal Deconvolution Estimator") is presented to
solve exactly these problems of current methods. RESOLVE employs a
statistical approach, estimating the most probable image
reconstruction compatible with the measured data. In this process, the
algorithm uses the vague prior knowledge of the observer on the source
— namely that it is an extended object — to differentiate
between likely and unlikely reconstructions. To this end, RESOLVE
assumes that the radio intensity does not change abruptly from one
place to the next, but instead that the source is comprised of
statistically similar structures, connected over several pixels, and
not necessarily exactly known prior to an observation. Mathematically,
this is expressed by a so-called spatial correlation function, unknown
at the beginning of the reconstruction process.
RESOLVE can roughly be divided into two major steps. In the first
part, the statistically most probable image reconstruction, compatible
with an extended source, is estimated. In this step, the spatial
correlation function is assumed to be known by the algorithm and thus
influences the reconstruction process. In the second part, the
correlation function is estimated using the intermediate image
reconstruction obtained in the first step. RESOLVE iterates this
two-step process until a statistically optimal reconstruction has been
obtained. Finally, from the last reconstruction, a map of the
measurement uncertainty is calculated.
This procedure can be extended to observations at different
wavelengths. For this, in addition, the spectral dependence of the
radio emission in every pixel is estimated using a very similar method
as just described.
Simulated reconstructions using RESOLVE show that from high quality
interferometric data, it is indeed possible to computationally reverse
the complicated measurement process of the interferometer with high
precision and to estimate the structure of an extended radio source with
high precision. In addition, the noise is removed from the measured
signal and a measurement uncertainty is estimated during this process.
Possible areas of application in observational radio astronomy range
from single objects in the Milky Way like e.g. remnants of exploding
stars, to distant radio galaxies and large galaxy clusters. The new
image reconstructions will allow for a deeper and better resolved view
into the radio sky.
Henrik Junklewitz, Michael Bell and Torsten Enßlin
REFERENCES
Henrik Junklewitz, Michael Bell, Marco Selig and Torsten Enßlin,
"RESOLVE: A new algorithm for aperture synthesis imaging in radio astronomy",
submitted to A&A
Henrik Junklewitz, Michael Bell and Torsten Enßlin, "A new approach to multi-frequency imaging in radio interferometry", submitted to A&A
