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White Rabbit (WR) is a technology developed at CERN, in collaboration with institutes and companies, to synchronise devices in the accelerators down to sub-nanoseconds and solve the challenge of establishing a common notion of time across a network. Indeed, at a scale of billionths of a second, the time light takes to travel through a fibre-optic cable and the time the electronics take to process the signal are no longer negligible. To avoid potential delays, the co-inventors of White Rabbit designed a new ethernet switch.

First used in 2012, the application of this fully open-source technology has quickly expanded outside the field of particle physics. In 2020, it was included in the worldwide industry standard known as Precision Time Protocol (PTP), governed by the Institute of Electrical and Electronics Engineers (IEEE).

What’s more, CERN recently launched the White Rabbit Collaboration, a membership-based global community whose objective is to maintain a high-performance open-source technology that meets the needs of users and to facilitate its uptake by industry. The WR Collaboration will provide dedicated support and training, facilitate R&D projects between entities with common interests and complementary expertise and establish a testing ecosystem fostering trust in products that incorporate the open-source technology. At CERN, the WR Collaboration Bureau – a dedicated team composed of senior White Rabbit engineers and a community coordinator – will facilitate the day-to-day running of the Collaboration’s activities and support its members.

Small, shelled, and unassuming, chitons have eyes unlike any other creature in the animal kingdom.

Some of these marine mollusks have thousands of bulbous little peepers embedded in their segmented shells, all with lenses made of a mineral called aragonite. Although tiny and primitive, these sensory organs called ocelli are thought to be capable of true vision, distinguishing shapes as well as light.

Other chiton species, however, sport smaller ‘eyespots’ that function more like individual pixels, much like the components of an insect’s or mantis shrimp’s compound eye, forming a visual sensor distributed over the chiton’s shell.

The calculation, which took around 75 days to complete, was carried out with 36 of the company’s proprietary solid-state drives (SSDs) — a storage medium fitted into many of the newest laptops — that stored altogether around 1 petabyte (1 million gigabytes) of data.

Processors are also needed to perform the number-crunching — with more powerful components reducing the time it takes to perform the necessary calculations. However, reliable and large-capacity storage is arguably more important because you need to store a massive amount of data in such a process.

The achievement “was no small feat,” Solidigm owner Brian Beeler said in the statement. “It involved meticulous planning, optimization, and execution.”

The printed solenoids could enable electronics that cost less and are easier to manufacture — on Earth or in space.

Imagine being able to build an entire dialysis machine using nothing more than a 3D printer.

This could not only reduce costs and eliminate manufacturing waste, but since this machine could be produced outside a factory, people with limited resources or those who live in remote areas may be able to access this medical device more easily.

Even the most complicated data processing on a computer can be broken down into small, simple logical steps: You can add individual bits together, you can reverse logical states, you can use combinations such as “AND” or “OR.” Such operations are realized on the computer by very specific sets of transistors. These sets then form larger circuit blocks that carry out more complex data manipulations.