Interferometric Imaging Directly with Closure Phases and Closure Amplitudes

TL;DR

This paper introduces a novel interferometric imaging method using only closure phases and amplitudes, enabling high-fidelity images without calibration errors, especially useful for sparse arrays like the Event Horizon Telescope.

Contribution

The paper presents a closure-only imaging technique that reconstructs images independently of calibration, improving robustness and fidelity over traditional methods.

Findings

Closure-only imaging produces high-quality images with systematic errors eliminated.

The method works effectively with sparse arrays such as the Event Horizon Telescope.

Closure imaging matches or exceeds traditional self-calibration and CLEAN performance.

Abstract

Interferometric imaging now achieves angular resolutions as fine as 10 microarcsec, probing scales that are inaccessible to single telescopes. Traditional synthesis imaging methods require calibrated visibilities; however, interferometric calibration is challenging, especially at high frequencies. Nevertheless, most studies present only a single image of their data after a process of "self-calibration," an iterative procedure where the initial image and calibration assumptions can significantly influence the final image. We present a method for efficient interferometric imaging directly using only closure amplitudes and closure phases, which are immune to station-based calibration errors. Closure-only imaging provides results that are as non-committal as possible and allows for reconstructing an image independently from separate amplitude and phase self-calibration. While closure-only imaging eliminates some image information (e.g., the total image flux density and the image centroid), this information can be recovered through a small number of additional constraints. We demonstrate that closure-only imaging can produce high fidelity results, even for sparse arrays such as the Event Horizon Telescope, and that the resulting images are independent of the level of systematic amplitude error. We apply closure imaging to VLBA and ALMA data and show that it is capable of matching or exceeding the performance of traditional self-calibration and CLEAN for these data sets.