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Researchers generate optical skyrmions

Researchers generate optical skyrmions

6 years ago
Anonymous $dicfOfy7s2

https://phys.org/news/2018-07-optical-skyrmions.html

The term "skyrmion" is derived from the name of Dr. Tony Skyrme, an English physicist who, in 1962, discovered that high-energy arrangements of physical systems with fields that have a "hedgehog-like configuration" enjoy an enhanced stability. Over the years, the concept was applied to several material systems, most notably in magnets. Hedgehog arrangements are considered a highly promising alternative for data representation, which could drastically increase computer memory storage.

Currently, most of the world's information is inserted or extracted on hard drives via a mechanical arm. But information management based on skyrmions only requires weak electrical currents. And skyrmions are of nanoscale dimensions – with diameters 10,000 times smaller than that of a hair strand. Such features are why skyrmions are expected to dramatically optimize, speed up and reduce the costs of information processing, transfer and storage.

Researchers generate optical skyrmions

Jul 27, 2018, 2:32pm UTC
https://phys.org/news/2018-07-optical-skyrmions.html > The term "skyrmion" is derived from the name of Dr. Tony Skyrme, an English physicist who, in 1962, discovered that high-energy arrangements of physical systems with fields that have a "hedgehog-like configuration" enjoy an enhanced stability. Over the years, the concept was applied to several material systems, most notably in magnets. Hedgehog arrangements are considered a highly promising alternative for data representation, which could drastically increase computer memory storage. > Currently, most of the world's information is inserted or extracted on hard drives via a mechanical arm. But information management based on skyrmions only requires weak electrical currents. And skyrmions are of nanoscale dimensions – with diameters 10,000 times smaller than that of a hair strand. Such features are why skyrmions are expected to dramatically optimize, speed up and reduce the costs of information processing, transfer and storage.