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Category: computing – Page 843

Silicon forms the basis of everything from solar cells to the integrated circuits at the heart of our modern electronic gadgets. However the laser, one of the most ubiquitous of all electronic devices today, has long been one component unable to be successfully replicated in this material. Now researchers have found a way to create microscopically-small lasers directly from silicon, unlocking the possibilities of direct integration of photonics on silicon and taking a significant step towards light-based computers.

Whilst there has been a range of microminiature lasers incorporated directly into silicon over the years, including melding germanium-tin lasers with a silicon substrate and using gallium-arsenide (GaAs) to grow laser nanowires, these methods have involved compromise. With the new method, though, an international team of researchers has integrated sub-wavelength cavities, the basic components of their minuscule lasers, directly onto the silicon itself.

To help achieve this, a team of collaborating scientists from Hong Kong University of Science and Technology, the University of California, Santa Barbara, Sandia National Laboratories and Harvard University, first had to find a way to refine silicon crystal lattices so that their inherent defects were reduced significantly enough to match the smooth properties found in GaAs substrate lasers. They did this by etching nano-patterns directly onto the silicon to confine the defects and ensure the necessary quantum confinement of electrons within quantum dots grown on this template.

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On May 11, 2016, the Berggruen Philosophy and Culture Center invited Yuval Noah Harari, a professor of history at Hebrew University of Jerusalem and author of the international bestseller “Sapiens: A Brief History of Humankind,” to deliver a talk on “The New Inequalities” at Tsinghua University in Beijing. Prior to the talk, Harari was interviewed by BPPC director Daniel A. Bell. This is an edited transcript of the interview.

You argue in your book that material progress, for example in the agriculture revolution and industrial capitalism doesn’t necessarily contribute to human happiness. In fact, it may lead to the opposite. Can you elaborate on that?

Until the middle of the 19th century there was a complete lack of correlation between material progress and the well-being of individual humans. For thousands of years until about 1850 you see humans accumulating more and more power by the invention of new technologies and by new systems of organization in the economy and in politics, but you don’t see any real improvement in the well-being of the average person. If you are the emperor of China, then obviously you’re much better off. But if you’re an average Chinese peasant in 1850, it’s very, very hard to say that your life is any better than the life of hunter-gatherers in the Yangtze Valley 20,000 years ago. You work much harder than them, your diet is worse, you suffer far more from infectious diseases, and you suffer far more from social inequality and economic exploitation.

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Gene-based circuits are about to get decidedly more sophisticated. MIT scientists have developed a method for integrating both analog and digital computing into those circuits, turning living cells into complex computers. The centerpiece is a threshold sensor whose gene expression flips DNA, converting analog chemical data into binary output — basically, complex data can trigger simple responses that match the language of regular computers.

The practical applications are huge. Along with general-purpose computing, you could have advanced sensors that trigger different kinds of chemical production depending on levels for other chemicals. You could produce insulin when there’s too much glucose, for instance, or deliver different kinds of cancer therapy. And this isn’t just talk. Clinical trials for a simple gene circuit (which will treat gut diseases) are starting within a year, so you could see these organic machines in action before too long.

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Terahertz radiation, or T-rays, can do some really incredible stuff. It can be used to scan for tumors and bombs build ultrafast wireless networks and see through solid objects. As an imaging technology, however, T-ray cameras have always had a resolution limitation. Well, they used to. Researchers at the University of Exter has developed a new terahertz camera that can see at a microscopic level — and they want to use it to find defects in microchips.

This breakthrough kind of changes the game for terahertz imaging. The radiation has always been able to look through solid objects without damaging them — which is why it’s frequently used in the art world to look past the surface layer of various masterpieces — but resolution limitations kept it from being used to diagnose broken computer chips.

Project lead Rayko Stantchev says his team has effectively doubled the technology’s resolution, creating a proof-of-principle prototype that can see a microscopic image printed on a circuit board obscured by a thick silicon wafer. “With our device you could test the quality of microchips that have buried under optically-opaque materials,” Stantchev says. “Allowing you to tell if a hidden chip is broken without having to open it up.”

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Of course it can — why we have Biocomputing efforts today.

Living cells are capable of performing complex computations on the environmental signals they encounter.

These computations can be continuous, or analogue, in nature—the way eyes adjust to gradual changes in the light levels. They can also be digital, involving simple on or off processes, such as a cell’s initiation of its own death.

Synthetic biological systems, in contrast, have tended to focus on either analogue or digital processing, limiting the range of applications for which they can be used.

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Definitely aligns with my NextGen transformational roadmap leading to Singularity. 5th Revolution is with Quantum technology, BMI, early Biocomputing. 6th Revolution is Singularity with Biocomputing evolved and all things living are enhanced via both technology and Biocomputing and several cases of hybrids through synthetic genes and technology. So, no shocker here.

A team of researchers at MIT has developed a technique to integrate both analogue and digital computation in living cells, allowing them to form gene circuits capable of carrying out complex processing operations.

Living cells are capable of performing complex computations on the environmental signals they encounter.

These computations can be continuous, or analogue, in nature — the way eyes adjust to gradual changes in the light levels. They can also be digital, involving simple on or off processes, such as a cell’s initiation of its own death.

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It certainly is.

Quantum computing’s full potential may still be years away, but there are plenty of benefits to be realized right now.

So argues Vern Brownell, president and CEO of D-Wave Systems, whose namesake quantum system is already in its second generation.

Launched 17 years ago by a team with roots at Canada’s University of British Columbia, D-Wave introduced what it called “the world’s first commercially available quantum computer” back in 2010. Since then the company has doubled the number of qubits, or quantum bits, in its machines roughly every year. Today, its D-Wave 2X system boasts more than 1,000.

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(Phys.org)—In order to determine how fast quantum technologies can ultimately operate, physicists have established the concept of “quantum speed limits.” Quantum speed limits impose limitations on how fast a quantum system can transition from one state to another, so that such a transition requires a minimum amount of time (typically on the order of nanoseconds). This means, for example, that a future quantum computer will not be able to perform computations faster than a certain time determined by these limits.

Although physicists have been investigating different quantum speed limits for different types of quantum systems, it has not been clear what the best way to do this is, or how many different quantum speed limits there are.

Now in a new paper published in Physical Review X, Diego Paiva Pires et al., from the UK and Brazil, have used techniques from information geometry to show that there are an infinite number of quantum speed limits. They also develop a way to determine which of these speed limits are the strictest, or in other words, which speed limits offer the tightest lower bounds. As the researchers explain, the search for the ultimate quantum speed limits is closely related to the very nature of time itself.

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