Subtraction Of Point Sources From Interferometric Radio Images Through An Algebraic Forward Modeling Scheme

Details Subtraction Of Point Sources From Interferometric Radio Images Through An Algebraic Forward Modeling Scheme Subtraction Of Point Sources From Interferometric Radio Images Through An Algebraic Forward Modeling Scheme

Jan 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21711607b&link_type=abstract

American Astronomical Society, AAS Meeting #217, #116.07; Bulletin of the American Astronomical Society, Vol. 43, 2011

Mathematics

Logic

Scientific paper

Cutting edge cosmological investigations of the Epoch of Reionization (EoR) are driving a renovated effort in building low frequency radio interferometers. In order to detect the tiny EoR signal, high dynamic range (DR) imaging at frequencies below 200 MHz is required.
High DR images are traditionally obtained by subtraction of bright sources from the ungridded visibilities, however, future generations of large-N radiotelescopes will generate such high volume data stream that the cost of storing the raw ungridded visibilities will be prohibitive. The DR will therefore be limited by well known pixelization effects.
Further challenges for an image based deconvolution at low frequencies are a point spread function which varies significantly across the field of view, a time and frequency variable receptor response and ionospheric variability.
In this presentation, we introduce a deconvolution algorithm which makes use of forward modeling to mitigate against the limitations of image-based deconvolution. Through forward modeling it is possible to generate a spatially variable point spread function and relate the sky brightness distribution to astrophysical parameters which are then retrieved through a non linear least squares minimization.
We applied the method to the deconvolution of point sources on simulated observations of the Murchison Wide-field Array (MWA). MWA is the array with the largest number of correlated elements currently under construction (512 final elements) and will not have the option of storing the raw visibility data over long time integrations.
We find that the accuracy to which point sources can be deconvolved/subtracted is only limited by their signal to noise ratio, not by their number or positions, therefore the DR increases with integration time. These results indicate this method to be promising for applications that require high DR imaging, like the detection of the EoR signal.
This work was supported by the U.S. National Science Foundation.

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