14 posts tagged computation
Could ‘solid’ light compute previously unsolvable problems?
An “artificial atom” makes photons behave like exotic matter
Researchers at Princeton University have “crystallized” light. They are not shining light through crystal — they are actually transforming light into crystal, as part of an effort to develop exotic materials such as room-temperature superconductors. The researchers locked together photons so that they became fixed in place. “It’s something that we have never seen before,” said Andrew Houck, an associate professor of electrical engineering and one of the researchers. “This is a new behavior for light.” The results raise intriguing possibilities for a variety of future materials, and also address questions in condensed matter physics — the fundamental study of matter. “We are interested in exploring — and ultimately controlling and directing — the flow of energy at the atomic level,” said Hakan Türeci, an assistant professor of electrical engineering and a member of the research team. “The goal is to better understand current materials and processes and to evaluate materials that we cannot yet create.” The team’s findings, reported online Sept. 8 in the journal Physical Review X (open access), are part of an effort to answer fundamental questions about atomic behavior by creating a device that can simulate the behavior of subatomic particles. Special-purpose quantum computers Such a tool could be an invaluable method for answering questions about atoms and molecules that are not answerable even with today’s most advanced computers. In part, that’s because current computers operate under the rules of classical mechanics, while the world of atoms and photons obeys the rules of quantum mechanics, which include a number of strange and very counterintuitive features. One of these odd properties is called “entanglement,” in which multiple particles become linked and can affect each other over long distances. A computer based on the rules of quantum mechanics could help crack problems that are currently unsolvable. But building a general-purpose quantum computer has proven to be incredibly difficult. Another approach, which the Princeton team is taking, is to build a system that directly simulates the desired quantum behavior. Although each machine is limited to a single task, it would allow researchers to answer important questions without having to solve some of the more difficult problems involved in creating a general-purpose quantum computer. The device could also allow physicists to explore fundamental questions about the behavior of matter by mimicking materials that only exist in physicists’ imaginations. (via Could ‘solid’ light compute previously unsolvable problems? | KurzweilAI)
Can physical systems from bacteria to black holes act as a computer? A University of York computer scientist and colleagues from the universities of Oxford and Leeds address this question in newly published research which seeks to define unconventional computational devices. Professor Susan Stepney, of the Department of Computer Science at York and her fellow researchers propose a framework which which defines and distinguishes scientific experiments, physical computation, and engineering technology. The evolving focus on the physical basis of computing has been prompted by a growing interest in non-standard computing systems including quantum and biological computers. But there is no consensus on how identify if a physical system is operating as a computer or not. The new research, published in Proceedings of the Royal Society A,introduces a formal framework that can be used to determine whether or not a physical system is performing a computation. The researchers demonstrate how the abstract computational level interacts with the physical device level, drawing the comparison with the use of mathematical models to represent physical objects in experimental science. This formulation allows a precise description of the similarities between experiments, computation, simulation, and technology, leading the researchers to conclude: physical computing is the use of a physical system to predict the outcome of an abstract evolution. They give conditions that must be satisfied in order for computation to occur, and illustrate them with a range of non-standard computing scenarios. The framework also covers broader computing contexts, where there is no human computer user. They define the notion of a ‘computational entity’, and show the role it plays in defining when computing is taking place in physical systems.
Scientists create transistor-like biological device
Stanford researchers demonstrate ‘transcriptors’ inside E coli bacteria, in advance in synthetic biology
Scientists have used biological tissue to recreate one of the main components of a modern computer inside living cells.
The biological device behaves like a transistor, one of the tiny switches that are etched on to microchips in the billions to perform computer calculations.
The researchers demonstrated the device inside E coli bacteria, one of the most common bugs used in genetic engineering. The work marks one of the latest advances in the growing field of synthetic biology, which recasts biology as a toolset for engineers.
Writing in the journal Science, researchers at Stanford University explain how their biological transistors could be connected together inside living cells to perform computing jobs such as controlling how genes are expressed in an organism.
Led by Drew Endy, a pioneer in the field, the team showed that different arrangements of biological transistors worked like logic gates, which take input signals and process them into different outputs. In keeping with their heritage, Endy calls these arrangements Boolean Integrase Logic (BIL) gates.
Normal transistors control the flow of electrons along metal wires. In the biological device, dubbed a “transcriptor”, the wire is a strand of DNA and the electrons are replaced by an enzyme. A modern computer chip holds several billion transistors that are wired together to carry out calculations. The same can be achieved with transcriptors, each of which is built from about 150 letters of the genetic code. (via Scientists create transistor-like biological device | Science | The Guardian)
Artificial muscle computer performs as a universal Turing machine
In 1936, Alan Turing showed that all computers are simply manifestations of an underlying logical architecture, no matter what materials they’re made of. Although most of the computer’s we’re familiar with are made of silicon semiconductors, other computers have been made of DNA, light, legos, paper, and many other unconventional materials.
Now in a new study, scientists have built a computer made of artificial muscles that are themselves made of electroactive polymers. The artificial muscle computer is an example of the simplest known universal Turing machine, and as such it is capable of solving any computable problem given sufficient time and memory. By showing that artificial muscles can “think,” the study paves the way for the development of smart, lifelike prostheses and soft robots that can conform to changing environments.
The authors, Benjamin Marc O’Brien and Iain Alexander Anderson at the University of Auckland in New Zealand, have published their study on the artificial muscle computer in a recent issue of Applied Physics Letters.
"To the best of our knowledge, this is the first time a computer has been built out of artificial muscles," O’Brien told Phys.org. “What makes it exciting is that the technology can be directly and intimately embedded into artificial muscle devices, giving them lifelike reflexes. Even though our computer has hard bits, the technology is fundamentally soft and stretchy, something that traditional methods of computation struggle with.” (via Artificial muscle computer performs as a universal Turing machine)
You’ve heard the hype a hundred times: Physicists hope to someday build a whiz-bang quantum computer that can solve problems that would overwhelm an ordinary computer. Now, four separate teams have taken a step toward achieving such “quantum speed-up” by demonstrating a simpler, more limited form of quantum computing that, if it can be improved, might soon give classical computers a run for their money. But don’t get your hopes up for a full-fledged quantum computer. The gizmos may not be good for much beyond one particular calculation. Even with the caveats, the challenge of quantum computing has proven so difficult that the new papers are gaining notice. “The question is, does this give you a first step to doing a hard calculation quantum mechanically, and it looks like it might,” says Scott Aaronson, a theoretical computer scientist at the Massachusetts Institute of Technology (MIT) in Cambridge and an author on one of the papers. (via New Form of Quantum Computation Promises Showdown With Ordinary Computers - ScienceNOW)
Exactly how memories are stored and accessed in the brain is unclear. Neuroscientists, however, do know that a primitive structure buried in the center of the brain, called the hippocampus, is a pivotal region of memory formation. Here, changes in the strengths of connections between neurons, which are called synapses, are the basis for memory formation. Networks of neurons linking up in the hippocampus are likely to encode specific memories. Since direct tests cannot be performed in the brain, experimental evidence for this process of memory formation is difficult to obtain but mathematical and computational models can provide insight. To this end, Eng Yeow Cheu and co-workers at the A*STAR Institute for Infocomm Research, Singapore, have developed a model that sheds light on the exact synaptic conditions required in memory formation1.
This volume, with a foreword by Sir Roger Penrose, discusses the foundations of computation in relation to nature. It focuses on two main questions: What is computation? How does nature compute? The contributors are world-renowned experts who have helped shape a cutting-edge computational understanding of the universe. They discuss computation in the world from a variety of perspectives, ranging from foundational concepts to pragmatic models to ontological conceptions and philosophical implications. The volume provides a state-of-the-art collection of technical papers and non-technical essays, representing a field that assumes information and computation to be key in understanding and explaining the basic structure underpinning physical reality. It also includes a new edition of Konrad Zuse’s “Calculating Space” (the MIT translation), and a panel discussion transcription on the topic, featuring worldwide experts in quantum mechanics, physics, cognition, computation and algorithmic complexity. The volume is dedicated to the memory of Alan M Turing — the inventor of universal computation, on the 100th anniversary of his birth, and is part of the Turing Centenary celebrations. (via A Computable Universe: Understanding and Exploring Nature as Computation | KurzweilAI)
Before packed audiences in a petite London theatre, computational scientist Stephen Emmott has been giving a new kind of talk. The brainchild of Emmott and director Katie Mitchell at the Royal Court Theatre, 10 Billion is a daring one man show in which Emmott desperately strives to pull together into one grand and devastating portrait the many ways we are impacting the planet. Standing on a set that he admits eerily resembles his office in Cambridge, UK, where he is the head of Computational Science at Microsoft Research, Emmott takes theatregoers on a brisk and bracing tour through our own history and use of Earth’s resources, before offering a glimpse of what the future might look like if the population reaches 10 billion. It isn’t good. (via CultureLab: Can the planet survive 10 billion people?)