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Current issue

ELEKTRO 11/2017 was released on November 6th 2017. Its digital version will be available on November 27th 2017.

Topic: Electrical distribution switchboards and switchboard technology; Rotating electrical machines

Main Article
Analysis of the CFD settings for simulating the temperature field of sinusoidal filter
On-line optimisation of current commutation angles in phases of BLDC motor

SVĚTLO (Light) 5/2017 was released on September 18th 2017. Its digital version will be available on September 18th 2017.

Luminaires and luminous apparatuses
MAYBE STYLE introducing LED design luminaires of German producer Lightnet
TREVOS – new luminaires for industry and offices
How many types of LED panels produces MODUS?
Intelligent LED luminaire RENO PROFI

Interiors lighting
The light in indoor flat interior – questions and answers

Using nanotechnology to create parallel computers

30.03.2016 | Lund University | www.lunduniversity.lu.se

Researchers at Lund University in Sweden have utilised nanotechnology to create a biological computer that can solve certain mathematical problems far faster and more energy-efficiently than conventional electrical computers.

Conventional computers have contributed to major advances for society over the past few decades, but have a weakness: they can only do one thing at a time. The more arithmetic operations a problem requires, the longer it takes to perform the calculations. This means that electronic computers are not efficient in dealing with combinatorial problems, for example in cryptography and mathematical optimisation, which require the computer to test a large number of different solutions.

Nanotechnology helps computers

However, nanotechnology researchers at Lund are on the track of a solution. They have shown that a parallel computer utilising molecular motors can find all the correct solutions to a combinatorial problem, rapidly and energy-efficiently. Parallel computers perform several calculations simultaneously, instead of sequentially, which in theory makes them extremely fast at solving combinatorial problems. Up to now the limiting factors for parallel computers have been scalability and practical implementation.

Biological computers use a strategy similar to that of so-called quantum computers. Quantum mechanics uses qubits – ones and zeroes – whereas biocomputers use molecules that work in parallel.

Read more at Lund University

Image Credit: Lund University

-jk-