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.
Turning static radio images into dynamic imaging
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.”
Rethinking bright blazar ‘shock waves’
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. That’s not what the team found using kine.
The study authors explain, “We found no evidence that traveling bright components are strongly shocked regions, as previously proposed, because the component speeds are of the same order as the average flow speed in the same regions. The shock interpretation is also disfavored by the absence of correlation between the bright features and the peaks in the fractional polarization.”
Instead, the team says polarization evidence suggests the knots are locally brighter, magnetically energized regions, with their brightness boosted by their direction of motion. They found that the bright knots moved at speeds similar to the surrounding plasma. Earlier methods had not been able to measure these speeds.
The team notes that the results apply specifically to blazar 3C 345, and not automatically to all black hole jets. Future work could reveal whether the standard shock-wave explanation needs revising in other sources, and applying kine across major archival jet-monitoring programs could provide full motion maps for hundreds of active galactic nuclei. The researchers also note that the underlying reconstruction problem resembles MRI imaging, suggesting possible future improvements for imaging moving organs.
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Publication details
Marianna Foschi et al, Video reconstruction of variable VLBI observations with neural fields, Nature (2026). DOI: 10.1038/s41586-026-10988-5
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Continuous video of black hole radio observations challenges shock wave theory (2026, September 10)
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