Systems Theory
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Systems Theory
theoretical aspects of (social) systems theory
Curated by Ben van Lier
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How do you build a large-scale quantum computer?

How do you build a large-scale quantum computer? | Systems Theory | Scoop.it

Physicists led by ion-trapper Christopher Monroe at the JQI have proposed a modular quantum computer architecture that promises scalability to much larger numbers of qubits. The components of this architecture have individually been tested and are available, making it a promising approach. In the paper, the authors present expected performance and scaling calculations, demonstrating that their architecture is not only viable, but in some ways, preferable when compared to related schemes.


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Andreas Pappas's curator insight, March 28, 2014 4:40 AM

This article shows how scientists can increase the scale of quantum machine while still making them behave quantum mechanically by reading the qu-bits with lasers instead of conventional wiring.

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Beyond the Moore's Law: Nanocomputing using nanowire tiles

Beyond the Moore's Law: Nanocomputing using nanowire tiles | Systems Theory | Scoop.it

An interdisciplinary team of scientists and engineers from The MITRE Corporation and Harvard University have taken key steps toward ultra-small electronic computer systems that push beyond the imminent end of Moore's Law, which states that the device density and overall processing power for computers will double every two to three years.

The ultra-small, ultra-low-power control processor—termed a nanoelectronic finite-state machine or "nanoFSM"—is smaller than a human nerve cell. It is composed of hundreds of nanowire transistors, each of which is a switch about ten-thousand times thinner than a human hair. The nanowire transistors use very little power because they are "nonvolatile." That is, the switches remember whether they are on or off, even when no power is supplied to them.


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James Jandebeur's curator insight, February 1, 2014 12:57 PM

It mentions that the processors can now be made smaller than a neuron, I wonder how its power compares. Still, quite a breakthrough if it works out.

aanve's curator insight, February 1, 2014 11:09 PM
www.aanve.com
Christian Verstraete's curator insight, February 3, 2014 1:29 AM

Will this address our needs when we reach the physical limits of our current chip technology?

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Biology Confronts Data Complexity

Biology Confronts Data Complexity | Systems Theory | Scoop.it

New technologies have launched the life sciences into the age of big data. Biologists must now make sense of their informational windfall.


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Gary Bamford's curator insight, October 21, 2013 1:53 AM

The very definition of 'complexity'!

Germán Morales's curator insight, October 22, 2013 11:26 AM

Tratar la vida como un cumulo de datos... qué se yo... estamos yendo a eso.

tatiyana fuentes's curator insight, October 24, 2013 8:49 AM

It was difficult to find sequence the human genome, but now it’s comparatively simple to compare genomes of the microorganisms living in our bodies, the ocean, the soil, and everywhere because of the new technologies. Life scientists are embarking on countless other big data projects, including efforts to analyze the genomes of many cancers, to map the human brain, and to develop better biofuels and other crops. Compared to fields like physics, astronomy and computer science that have been dealing with the challenges of massive datasets for decades, the big data revolution in biology has also been quick, leaving little time to adapt. Biologists must overcome a number of hurdles, from storing and moving data to integrating and analyzing it, which will require a substantial cultural shift.

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Is it time to move past the idea that our brain is like a computer?

Is it time to move past the idea that our brain is like a computer? | Systems Theory | Scoop.it

Ever since the days of Alan Turing, neuroscientists have, in increasing numbers, compared the human brain to a computer. It's an analogy that makes a hell of a lot of sense, and it's done much to help us understand this remarkable grey blob that sits between our ears. But as a recent essay by philosopher Daniel Dennett points out, while the brain should most certainly be considered a kind of machine — one with a trillion moving parts — its inner workings are far removed from anything we have ever developed. Consequently, scientists need to take note and update their models accordingly. Calling the brain a "computer," says Dennett, is accurate, but insufficient.


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Graphene nanoribbons could be the savior of Moore’s Law

Graphene nanoribbons could be the savior of Moore’s Law | Systems Theory | Scoop.it

With each new generation of microchips, transistors are being placed closer and closer together. This can only go on so long before there’s no more room to improve, or something revolutionary has to come along to change everything. One of the materials that might be the basis of that revolution is none other than graphene. Researchers at the University of California at Berkeley are hot on the trail of a form of so-called nanoribbon graphene that could increase the density of transistors on a computer chip by as much as 10,000 times.


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Thierry Bodhuin's curator insight, February 18, 2014 4:10 AM

Moore's law may continue ... 

 

Yaroslav Writtle's curator insight, February 18, 2014 6:44 AM

Interesting stuff - wonder what could this mean for computing capacity 10 years down the line?

Benjamin Rees's curator insight, March 27, 2015 8:06 AM

For the past few decades, the concept of Moore's Law has proven to be relatively accurate in saying that the density of transistors able to be placed on an integrated circuit roughly doubles every two years. However, as transistors are manufactured to be placed increasingly close together, it can be foreseen that there will soon be no more room for improvement using current methods and materials. Recent developments in graphene technology may allow for more spatially efficient  circuits in the future, thereby continuing this trend of doubling transistor density.

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Synaptic Transistor Learns While it Computes

Synaptic Transistor Learns While it Computes | Systems Theory | Scoop.it

Materials scientists at the Harvard School of Engineering and Applied Sciences (SEAS) have now created a new type of transistor that mimics the behavior of a synapse. The novel device simultaneously modulates the flow of information in a circuit and physically adapts to changing signals.

Exploiting unusual properties in modern materials, the synaptic transistor could mark the beginning of a new kind of artificial intelligence: one embedded not in smart algorithms but in the very architecture of a computer. 

 


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In-brain monitoring shows memory network

In-brain monitoring shows memory network | Systems Theory | Scoop.it

Working with patients with electrodes implanted in their brains, researchers at the University of California, Davis, and The University of Texas Health Science Center at Houston (UTHealth) have shown for the first time that areas of the brain work together at the same time to recall memories. The unique approach promises new insights into how we remember details of time and place.


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Why the Frontiers of Biology Might Be Inside a Computer Chip

Why the Frontiers of Biology Might Be Inside a Computer Chip | Systems Theory | Scoop.it

When David Harel started the experiment, the petri dish of mouse cells looked just like any other. Genes were being expressed, proteins were being made, and the tissue was being perfused with oxygen-rich blood.
But then things started to change. First one cell changed position and moved across the plate, followed quickly by another. Eventually, through migration and other changes in cell functionality and signaling, the cells had differentiated, with the lucky ones becoming fully-fledged thymus gland T cells. And it all happened in a fraction of the time that biologists would have expected based on several decades of physiological and development studies; after all, this experiment was happening inside a computer, in virtual organs modeled by complicated diagrams, simulating their real-world counterparts.


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