Generalized Redundant Calibration of Radio Inteferferometers. (arXiv:2107.10186v1 [astro-ph.IM])

<a href="http://arxiv.org/find/astro-ph/1/au:+Adari_P/0/1/0/all/0/1">Prakruth Adari</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Slosar_A/0/1/0/all/0/1">Anže Slosar</a>

Redundant calibration is a technique in radio astronomy that allows

calibration of radio arrays, whose antennas lie on a lattice by exploiting the

fact that redundant baselines should see the same sky signal. Because the

number of measured visibilities scales quadratically with the number of

antennas, but the number of unknowns describing the individual antenna

responses and the available information about the sky scale only linearly with

the array size, the problem is always over-constrained as long as the array is

big and dense enough. This is true even for non-lattice array configurations.

In this work we study a generalized algorithm in which a per-antenna gain is

replaced with a number of gains. We show that it can successfully describe data

from an approximately redundant array on square lattice with pointing and

geometry errors. We discuss the parameterization, limitations and possible

extensions of this algorithm.

Redundant calibration is a technique in radio astronomy that allows

calibration of radio arrays, whose antennas lie on a lattice by exploiting the

fact that redundant baselines should see the same sky signal. Because the

number of measured visibilities scales quadratically with the number of

antennas, but the number of unknowns describing the individual antenna

responses and the available information about the sky scale only linearly with

the array size, the problem is always over-constrained as long as the array is

big and dense enough. This is true even for non-lattice array configurations.

In this work we study a generalized algorithm in which a per-antenna gain is

replaced with a number of gains. We show that it can successfully describe data

from an approximately redundant array on square lattice with pointing and

geometry errors. We discuss the parameterization, limitations and possible

extensions of this algorithm.

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