Lifeboat Foundation

Today’s particle accelerators are massive machines, but physicists have been working on shrinking them down to tabletop scales for years. The Gordon and Betty Moore Foundation just awarded a $13.5 million grant to Stanford University to develop a working “accelerator on a chip” the size of a shoebox over the next five years.

The international collaboration will build on prior experiments by physicists at SLAC/Stanford and Germany’s Friedrich-Alexander University in Erlangen-Nuremberg. If successful, the prototype could usher in a new generation of compact particle accelerators that could fit on a laboratory bench, with potential applications in medical therapies, x-ray imaging, and even security scanner technologies.

The idea is to “do for particle accelerators what the microchip industry did for computers,” SLAC National Accelerator Laboratory physicist Joel England told Gizmodo. Computers used to fill entire rooms back when they relied on bulky vacuum tube technology. The invention of the transistor and subsequent development of the microchip made it possible to shrink computers down to laptop and cell phone scales. England envisions a day when we might be able to build a handheld particle accelerator, although “there’d be radiation issues, so you probably wouldn’t want to hold one in your hand.”

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The Star Trek computer is close. Phasers can’t be far behind.

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Laser cooling isn’t a new idea, but this is the first time it’s actually worked in real-world conditions.

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Engineers from the University of New South Wales, Australia, have made an important breakthrough that brings quantum computers one step closer to reality.

The team created a quantum version of a standard computer code within a silicon chip. The discovery shows that it is possible to construct realistic and reliable quantum computers.

Quantum computers have the potential to solve problems much more quickly than any computer that exists today, as they combine the rules of informatics to phenomena of quantum mechanics that are not observed in everyday life. Namely, the principle of superposition, popularized by Schrödinger’s cat being both alive and dead, and entanglement.

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D-Wave Systems Inc., the world’s first quantum computing company, announced that Los Alamos National Laboratory will acquire and install the latest D-Wave quantum computer, the 1000+ qubit D-Wave 2X™ system. Los Alamos, a multidisciplinary research institution engaged in strategic science on behalf of national security, will lead a collaboration within the Department of Energy and with select university partners to explore the capabilities and applications of quantum annealing technology, consistent with the goals of the government-wide National Strategic Computing Initiative. The National Strategic Computing Initiative, created by executive order of President Barack Obama in late July, is intended “to maximize [the] benefits of high-performance computing (HPC) research, development, and deployment.”

“Eventually Moore’s Law (that predicted that the number of transistors on an integrated circuit would double every two years) will come to an end,” said John Sarrao, associate director for Theory, Simulation, and Computation at Los Alamos. “Dennard Scaling (that predicted that performance per watt of computing would grow exponentially at roughly the same rate) already has. Beyond these two observations lies the end of the current ‘conventional’ computing era, so new technologies and ideas are needed.”

“As conventional computers reach their limits in terms of scaling and performance per watt, we need to investigate new technologies to support our mission,” said Mark Anderson of the Laboratory’s Weapons Physics Directorate. “Researching and evaluating quantum annealing as the basis for new approaches to address intractable problems is an essential and powerful step, and will enable a new generation of forward thinkers to influence its evolution in a direction most beneficial to the nation.”

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Nvidia shared some more details on its upcoming Pascal architecture for 2016 — the new GPU will offer 1TB/s of memory bandwidth and up to 16GB of VRAM.

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A team of quantum physicists in Martinis Lab have come a step closer in creating the circuitry that would allow them to process super computing done by quantum computers. The revolution is promised by the new quantum bits (qubits) compared to the previously done classical computing. Qubits infuse the system with high levels of reliability and speed, thus building foundations for large scale superconducting quantum computers.

Till now computing has been done by classical methods in which the bits were either in states 0 or 1, but qubits exist at all the positions simultaneously, in different dimensions. This special property of being omnipresent is called ‘superpositioning’. However, one of the difficulties is keeping the qubits stable to reproduce same result each time. This superpositioning characteristic makes qubits prone to ‘flipping’, therefore making it difficult to work with.

Julian Kelly, graduate student researcher and co-lead author of a research paper that was published in the journal Nature said:

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A computer simulation of a cognitive model entirely made up of artificial neurons learns to communicate through dialog starting from a state of tabula rasa —

A group of researchers from the University of Sassari (Italy) and the University of Plymouth (UK) has developed a cognitive model, made up of two million interconnected artificial neurons, able to learn to communicate using human language starting from a state of ‘tabula rasa’, only through communication with a human interlocutor. The model is called ANNABELL (Artificial Neural Network with Adaptive Behavior Exploited for Language Learning) and it is described in an article published in PLOS ONE. This research sheds light on the neural processes that underlie the development of language.

How does our brain develop the ability to perform complex cognitive functions, such as those needed for language and reasoning? This is a question that certainly we are all asking ourselves, to which the researchers are not yet able to give a complete answer. We know that in the human brain there are about one hundred billion neurons that communicate by means of electrical signals. We learned a lot about the mechanisms of production and transmission of electrical signals among neurons. There are also experimental techniques, such as functional magnetic resonance imaging, which allow us to understand which parts of the brain are most active when we are involved in different cognitive activities. But a detailed knowledge of how a single neuron works and what are the functions of the various parts of the brain is not enough to give an answer to the initial question.

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“The subtitle to this post is a variation of William Gibson’s famous remark: “The future is already here — it’s just not very evenly distributed.” An obvious follow up question is: if the future is already here, where can I find it?”

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