This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: For years, scientists have relied primarily on radio imaging from techniques like very long baseline interferometry (VLBI) to study jets from the active galactic nuclei of supermassive black holes. This allows for the detection of broad, unresolved features, called components, moving at what appear to be faster-than-light speeds.
However, traditional imaging has poor resolution and treats each observation as a separate snapshot in time, limiting information about how the features move. Astronomers have overcome this issue, but only to a degree, by reconstructing unknown aspects with the help of algorithms. Newer modeling methods can sharpen static radio images, but dynamic imaging has remained difficult, especially across large monitoring datasets.
But now, a team of researchers has developed an AI-based method that turns scattered radio observations into a continuous, polarized video. Their new study, published in Nature, applies this method to blazar 3C 345, a type of energetic active galactic nucleus, and the results have upended their understanding of the blazar. The team involved in the new study created an algorithm they refer to as kine, which they describe as a "video reconstruction algorithm for VLBI observations of variable sources." Kine uses a neural representation of the video to simultaneously process images taken at different times while learning and leveraging spatiotemporal correlations from the data.
Using 116 VLBI radio observations of blazar 3C 345 from the MOJAVE monitoring program, they reconstructed a video of its motion. The reconstruction achieved a resolution about four times higher than the usual limit and roughly 140 times the overall image contrast of traditional methods. The video allowed the researchers to estimate local plasma motion throughout the jet, rather than just track individual bright knots like previous methods.
The study authors write, "First, simultaneous imaging of all observations allows information to be shared across frames, improving resolution and dynamic range beyond what is achievable by frame-by-frame imaging. Second, the neural representation produces a smooth, continuous model of the flux density, sampleable at any time coordinate, enabling continuous and local motion analysis by optical flow. "Applied to multi-epoch observations, kine can provide marked advances in jet kinematics studies: from high-resolution time-continuous videos, it becomes possible to measure the instantaneous local velocity field rather than only tracking model-fitted components." For blazar 3C 345, the new method revealed significant insights.
Earlier studies of the blazar had tracked broad, bright features that appeared to be moving faster than light. These were interpreted as traveling shock waves caused by disturbances in the jet compressing the plasma. However, for this to be true, the shock wave must travel at a different speed from the relativistic jet.
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