Computing at the speed of light

Univ. of Utah engineers have taken a step forward in creating the next generation of computers and mobile devices capable of speeds millions of times faster than current machines.

The Utah engineers have developed an ultracompact beamsplitter—the smallest on record—for dividing light waves into two separate channels of information. The device brings researchers closer to producing silicon photonic chips that compute and shuttle data with light instead of electrons. Electrical and computer engineering associate professor Rajesh Menon and colleagues describe their invention in Nature Photonics.

Silicon photonics could significantly increase the power and speed of machines such as supercomputers, data center servers and the specialized computers that direct autonomous cars and drones with collision detection. Eventually, the technology could reach home computers and mobile devices and improve applications from gaming to video streaming.

Chinese Awards Part 2

Tim Studt here again, and mostly recovered from my day-long travel on Friday. Hot and humid here in Taipei, about 25 F warmer than in Chicago.

Today's judging at the Taiwan Excellence Awards covered healthcare-based tablet computers, electronic memory modules, top-end gaming computers, electric scooters, racing bicycles and even off-road mountain racing bike tires. All of these are state-of-the-art systems and market leaders in their respective industries with number one or two market shares.

The other judges are experts in quality, design and marketing assembled mostly in pairs. My R&D counterpart is the President of the Industrial Research Technology Institute (ITRI)—a frequent submitter and multiple winner of R&D 100 awards over the past several years. One of his R&D 100 Award winners from several years ago—flat panel electrostatic speakers—was the technology that we reviewed yesterday in the Bluetooth portable speakers.

Advances in molecular electronics

Scientists at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and the Univ. of Konstanz are working on storing and processing information on the level of single molecules to create the smallest possible components that will combine autonomously to form a circuit. As recently reported in Advanced Science, the researchers can switch on the current flow through a single molecule for the first time with the help of light.

Dr. Artur Erbe, physicist at the HZDR, is convinced that in the future molecular electronics will open the door for novel and increasingly smaller—while also more energy efficient—components or sensors: "Single molecules are currently the smallest imaginable components capable of being integrated into a processor." Scientists have yet to succeed in tailoring a molecule so that it can conduct an electrical current and that this current can be selectively turned on and off like an electrical switch.

Graphics in reverse

Most recent advances in artificial intelligence—such as mobile apps that convert speech to text—are the result of machine learning, in which computers are turned loose on huge data sets to look for patterns.

To make machine-learning applications easier to build, computer scientists have begun developing so-called probabilistic programming languages, which let researchers mix and match machine-learning techniques that have worked well in other contexts. In 2013, the U.S. Defense Advanced Research Projects Agency (DARPA), an incubator of cutting-edge technology, launched a four-year program to fund probabilistic-programming research.

Team tightens bounds on quantum information “speed limit”

If you're designing a new computer, you want it to solve problems as fast as possible. Just how fast is possible is an open question when it comes to quantum computers, but physicists at NIST have narrowed the theoretical limits for where that "speed limit" is. The research implies that quantum processors will work more slowly than some research has suggested.

The work offers a better description of how quickly information can travel within a system built of quantum particles such as a group of individual atoms. Engineers will need to know this to build quantum computers, which will have vastly different designs and be able to solve certain problems much more easily than the computers of today. While the new finding does not give an exact speed for how fast information will be able to travel in these as-yet-unbuilt computers—a longstanding question—it does place a far tighter constraint on where this speed limit could be.

Electrical control of quantum bits in silicon paves the way to large quantum computers

A Univ. of New South Wales (UNSW)-led research team has encoded quantum information in silicon using simple electrical pulses for the first time, bringing the construction of affordable large-scale quantum computers one step closer to reality.

Lead researcher, UNSW Assoc. Prof. Andrea Morello from the School of Electrical Engineering and Telecommunications, said his team had successfully realized a new control method for future quantum computers.

The findings were published in Science Advances.

Unlike conventional computers that store data on transistors and hard drives, quantum computers encode data in the quantum states of microscopic objects called qubits.

The UNSW team, which is affiliated with the ARC Centre of Excellence for Quantum Computation & Communication Technology, was first in the world to demonstrate single-atom spin qubits in silicon, reported in Nature in 2012 and 2013.

Carbon nanotube composites show promise for use in “unconventional” computing

As we approach the miniaturization limits of conventional electronics, alternatives to silicon-based transistors—the building blocks of the multitude of electronic devices we've come to rely on—are being hotly pursued.

Inspired by the way living organisms have evolved in nature to perform complex tasks with remarkable ease, a group of researchers from Durham Univ. and the Univ. of São Paulo-USP are exploring similar "evolutionary" methods to create information processing devices.

In the Journal of Applied Physics, the group describes using single-walled carbon nanotube composites (SWCNTs) as a material in "unconventional" computing. By studying the mechanical and electrical properties of the materials, they discovered a correlation between SWCNT concentration/viscosity/conductivity and the computational capability of the composite.