The Helium Decipherer: How to Read the Sun’s Invisible Past express

Original: "Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator"
arXiv:2606.08652 · 2026-06-07 · CC BY 4.0 · 1 min
A neural network decipherer has learned to turn old helium-light images of the Sun into detailed pictures of its invisible corona.

The solar corona (the outer atmosphere of the Sun, heated to millions of degrees) glows in ultraviolet light, but these rays are absorbed by the air and never reach Earth. Direct images of the corona from space have only been available since the 1990s. Yet since the 1970s, astronomers have observed the Sun in the infrared light of helium. The brightness of this glow depends on the ultraviolet 'illumination' from the corona: a helium image is a spectroscopy fingerprint of the corona. The neural network decipherer, trained on pairs of simultaneous images, learned to reconstruct the original ultraviolet picture, like a translator from the language of shadows to the language of flame.

The model reproduces even coronal holes well — dark regions from which the fast solar wind escapes, causing auroras on Earth.

The accuracy is such that the reconstructed frames match the few historical satellite data. Now we can assemble a continuous chronicle of the corona since the 1970s and trace how the Солнца activity changed in past cycles. This method unexpectedly turns old ground-based telescopes into time machines.

Archival helium images, accumulated over decades to track sunspots, have now found a second life as the key to the invisible corona.

One day, neural networks will reconstruct the appearance of distant stars from their faint spectral fingerprints.

Scientists
Arno PenziasRalph AlpherRobert Woodrow WilsonWilhelm WienMax PlanckLudwig Boltzmann
Concepts
solar corona Sun ultraviolet radiationPlanck's lawStefan–Boltzmann lawSaha equation