When light is scarce, a camera can't determine its polarization — the image turns into chaos of scattered dots. It's like trying to restore a painting from a few random brushstrokes. But if the strokes lie along a line, an experienced eye guesses what's missing.
Researchers have created an algorithm that uses the same principle. It knows that polarization (the orientation of a light wave) usually changes smoothly from one color to another: it was trained on examples.
So, from a handful of spectroscopic (color) data, it predicts missing values.
The method requires no complex equipment and works even with single photons. It will be useful for studying distant exoplanets — for example, to assess whether they have vegetation from reflected light, even if only a few light particles reach us. Or for ultra-sensitive photometry (brightness measurement) in laboratories.
Ordinary polarizing glasses are almost useless at twilight: they block some light, making an already dim picture even darker. The new method recovers light orientation from scarce data, restoring the ability to see in the dark.