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Liquid Mirror Breakthrough Could Make State-of-the-Art Optics Cheap

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A $120 million Earth-based telescope using brand new adaptive optics just trumped Hubble's deep space image clarity three-fold, but such high tech optics aren't just reserved for high-dollar observatories. A breakthrough in deformable liquid mirror technology could drastically reduce the price associated with adaptive optics, making the best in high-tech telescopes more widely available.
Imagine a volume of reflective liquid like mercury in a bowl. Spin the bowl, and the liquid will push toward the edges, forming a concave mirror as smooth as the best mirror glass. But unlike highly specialized mirror glass, it's just a bowl of mercury. It costs next to nothing by comparison.
As such, liquid mirrors should be important, inexpensive astronomical tools but they're not. For one, you can't turn a bowl of mercury on its side, so a liquid mirror could only power a telescope that looks straight up. More importantly, the advent of better adaptive optics for glass mirrors has kept glass in favor among astronomers.

When light from space passes through the atmosphere it degrades, giving earth-based telescopes a murky picture of the cosmos. To compensate, adaptive optics systems employ either very thin, pliable mirrors or honeycomb arrays of tiny hexagonal mirrors that can be adjusted to compensate for the light degradation, undoing the effects of atmosphere on light.

Liquid mirrors, however, could come back into fashion in a big way thanks to some developments that make them act like adaptive optics systems without requiring the adaptive optics price tag. Using a ferromagnetic liquid (rather than mercury), researchers pioneered a novel way to create deformable liquid mirrors a few years back, but there were some problems. For one, the magnetic fields used to deform the liquid couldn't be cycled quickly enough to be useful in astronomy. For another, there was a non-linear disconnect between the deformation of the mirror and the magnetic field strength that required a highly complex algorithm to be built from scratch.


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