Science

Scientists check their work and confirm it with update on iconic black hole image

He explained that when his team applied new advanced machine learning and artificial intelligence techniques to the original Event Horizon Telescope dataset, they found a black hole almost identical in size and shape to the historic EHT image.

✦ Extractive summary — built from the sources' own reporting•From 1 source•1 min read•Updated November 11, 2026, 5:02 PM UTC
Key points
  • This week, a small team of four Australian researchers have published their work confirming the result based on a new machine learning algorithm using the same base data.
  • To the relief of the EHT team, the new image recreated the iconic ring-like image seen in the original, according to a paper published in Nature today.
  • Potentially, alternative analyses of the data could have reconstructed an image without the iconic ring shape.

The 2019 Event Horizon Telescope (EHT) image came from hundreds of scientists working together to capture the first direct view of a black hole's shadow.

The image of the red ring around the black hole M87, produced by the Event Horizon Telescope (EHT) array, made front-page news around the world in 2019.

Additional details
  • "Importantly, our model had no idea what a black hole looked like when we applied it to the M87 data.
  • Reconstructing the image from the data so geographically distant meant instrument and environment errors could influence the accuracy of the resulting image.
  • Samuel Lai – a postdoctoral fellow at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Western Australia – and his team created an independent imaging algorithm to process the historic dataset to validate the result.
  • "It is extremely gratifying to see that an elegant, entirely independent method recovers the ring structure of M87 across several years, in excellent agreement with the EHT Collaboration's published results," he said.
  • This is the first truly independent validation of the EHT image, an important step in the scientific process," he said.

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