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  • richardmitnick 11:13 am on April 1, 2016 Permalink | Reply
    Tags: , Griffith U, Quantum Computing   

    From Griffith: “Unlocking the gates to quantum computing” 

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    Griffith University

    An artist’s rendering of the quantum Fredkin (controlled-SWAP) gate, powered by entanglement, operating on photonic qubits. (Image by Raj Patel and Geoff Pryde, Center for Quantum Dynamics, Griffith University.)

    Researchers have overcome one of the key challenges to quantum computing by simplifying a complex quantum logic operation. They demonstrated this by experimentally realising a challenging circuit, the quantum Fredkin gate, for the first time.

    “The allure of quantum computers is the unparalleled processing power that they provide compared to current technology,” said Dr Raj Patel from Griffith’s Centre for Quantum Dynamics.

    “Much like our everyday computer, the brains of a quantum computer consist of chains of logic gates, although quantum logic gates harness quantum phenomena.”

    The main stumbling block to actually creating a quantum computer has been in minimising the number of resources needed to efficiently implement processing circuits.

    “Similar to building a huge wall out lots of small bricks, large quantum circuits require very many logic gates to function. However, if larger bricks are used the same wall could be built with far fewer bricks,” said Dr Patel.

    In an experiment involving researchers from Griffith University and the University of Queensland, it was demonstrated how to build larger quantum circuits in a more direct way without using small logic gates.

    At present, even small and medium scale quantum computer circuits cannot be produced because of the requirement to integrate so many of these gates into the circuits. One example is the Fredkin (controlled- SWAP) gate. This is a gate where two qubits are swapped depending on the value of the third.

    Usually the Fredkin gate requires implementing a circuit of five logic operations. The research team used the quantum entanglement of photons – particles of light – to implement the controlled-SWAP operation directly.

    “There are quantum computing algorithms, such as Shor’s algorithm for finding prime factors, that require the controlled-SWAP operation,” said Professor Tim Ralph from the University of Queensland.

    The quantum Fredkin gate can also be used to perform a direct comparison of two sets of qubits (quantum bits) to determine whether they are the same or not. This is not only useful in computing but is an essential feature of some secure quantum communication protocols where the goal is to verify that two strings, or digital signatures, are the same.”

    Professor Geoff Pryde, from Griffith’s Centre for Quantum Dynamics, is the project’s chief investigator.

    “What is exciting about our scheme is that it is not limited to just controlling whether qubits are swapped, but can be applied to a variety of different operations opening up ways to control larger circuits efficiently,” said Professor Pryde.

    “This could unleash applications that have so far been out of reach.”

    The team is part of the Australian Research Council’s Centre for Quantum Computation and Communication Technology, an effort to exploit Australia’s strong expertise in developing quantum information technologies.

    The research has been published as A quantum Fredkin gate in Science Advances [no link present].

    See the full article here .

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    In 1971, Griffith was created to be a new kind of university—one that offered new degrees in progressive fields such as Asian studies and environmental science. At the time, these study areas were revolutionary—today, they’re more important than ever.

    Since then, we’ve grown into a comprehensive, research-intensive university, ranking in the top 5% of universities worldwide. Our teaching and research spans five campuses in South East Queensland and all disciplines, while our network of more than 120,000 graduates extends around the world.

    Griffith continues the progressive traditions of its namesake, Sir Samuel Walker Griffith, who was twice the Premier of Queensland, the first Chief Justice of the High Court of Australia, and the principal author of the Australian Constitution.

  • richardmitnick 7:41 am on March 18, 2016 Permalink | Reply
    Tags: , , Quantum Computing   

    From Physics: “Q&A: Building Quantum Computers with Superconductors” 

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    March 17, 2016
    No writer credit found

    Britton Plourde explains why he’s homed in on using superconducting circuits to make a quantum computer.

    Quantum approach to big data. MIT
    Quantum approach to big data. MIT

    Circuits have always captivated Britton Plourde. As a kid he designed and built model airplanes, a hobby that required wiring together numerous electronic parts. In graduate school he turned to fabricating even smaller and more complex circuits made from micrometer-sized superconducting materials. Today Plourde heads a group at Syracuse University in New York that is trying to build superconducting elements for a quantum computer. To learn more, Physics met up with Plourde at his lab at Syracuse.

    –Katherine Wright
    What are you working on at the moment?

    My focus is on quantum bits (qubits): How to make them, how to make them better, and how to increase the qubit lifetime—the time it takes the qubit to decay from a quantum superposition of states to a classical state. I’m also trying to understand ways to make multiple qubits interact with each other, to do things like generate entangled states between several qubits.

    Your main interest is superconducting qubits. What are they?

    They are microfabricated electrical circuits that contain superconducting elements, and they behave like artificial atoms with discrete energy levels. Two different electrical excitations in the circuit correspond to the two states of the qubit.

    There are many ways to make qubits. Why have you focused on using superconductors?

    Right before I started my postdoc at UC Berkley in 2000, a group in Japan had made the very first superconducting qubit. At the time, superconducting circuits seemed like an intriguing research direction, but they only had lifetimes of a nanosecond or so—nowhere close to being practical. But superconducting elements can, in principle, be integrated into a large processor using techniques similar to those developed by the semiconductor industry, which could allow for the rapid manufacture of billions of superconducting circuits. We wanted to leverage the same technology for quantum computers. But first we had to figure out if we could make robust quantum states from superconducting circuits. Back in 2000 that was a big if.

    And now?

    Right now we’re at a level where it’s feasible to build a small-scale quantum processor with a superconducting circuit. It’s possible to make systems with ten qubits, maybe a little bit beyond that. More importantly, qubit lifetimes have improved by 5 orders of magnitude since 2000. Also there have been key steps towards implementing circuits and control techniques that can correct for quantum errors, a critical element for building a quantum computer. It’s exciting!

    What calculations have been run on superconducting quantum computers?

    There have been several initial demonstrations of quantum algorithms, including factoring 15 into 5 and 3. The factoring algorithm was one of the original algorithms that kicked off research into quantum computers because there is no known efficient classical algorithm that can factor large numbers into primes. As the number gets really big, the time for the computation blows up rapidly. If a number contained 2000 bits—600 digits—the time needed to factor it would be longer than the age of the Universe. A quantum computer could factor such a large number in roughly a day, but the computer would need well over a million qubits, amongst other things, so we’re a little ways off!

    Are there other things a quantum computer could do?

    There is currently a lot of interest in quantum simulation—using a quantum computer to simulate another quantum system, such as complex molecules, which are difficult to simulate numerically on a classical computer. This wouldn’t need anywhere near a million qubits, but could be done with say tens or hundreds. [Simulation] will probably be the first breakthrough for quantum processors in which they perform faster than a classical approach.

    Do you think we’ll ever have personal quantum computers?

    No. There is not going to be a day when everybody has a quantum computer on their desks. And quantum computers will not be able to solve all problems faster than a classical computer—that’s a common misconception. There are many problems where a quantum computer would be slower, or simply wouldn’t make sense to use. You wouldn’t run a spreadsheet or write your term paper for history class on a quantum computer.

    Why is 2016 a great time to be working on quantum computing?

    The field is at this exciting intersection between fundamental physics and cutting-edge technology. We’re now able to engineer artificial quantum systems and to study fundamental properties of quantum mechanics in big systems that we can control. That’s neat. And several companies are trying to build superconducting quantum computers. Someone getting an advanced degree in this area certainly has good opportunities.

    See the full article here .

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  • richardmitnick 9:01 am on January 26, 2016 Permalink | Reply
    Tags: A new quantum approach to big data, , , Quantum Computing   

    From MIT: “A new quantum approach to big data” 

    MIT News

    January 25, 2016
    David L. Chandler | MIT News Office

    Quantum approach to big data
    This diagram demonstrates the simplified results that can be obtained by using quantum analysis on enormous, complex sets of data. Shown here are the connections between different regions of the brain in a control subject (left) and a subject under the influence of the psychedelic compound psilocybin (right). This demonstrates a dramatic increase in connectivity, which explains some of the drug’s effects (such as “hearing” colors or “seeing” smells). Such an analysis, involving billions of brain cells, would be too complex for conventional techniques, but could be handled easily by the new quantum approach, the researchers say. Courtesy of the researchers

    From gene mapping to space exploration, humanity continues to generate ever-larger sets of data — far more information than people can actually process, manage, or understand.

    Machine learning systems can help researchers deal with this ever-growing flood of information. Some of the most powerful of these analytical tools are based on a strange branch of geometry called topology, which deals with properties that stay the same even when something is bent and stretched every which way.

    Such topological systems are especially useful for analyzing the connections in complex networks, such as the internal wiring of the brain, the U.S. power grid, or the global interconnections of the Internet. But even with the most powerful modern supercomputers, such problems remain daunting and impractical to solve. Now, a new approach that would use quantum computers to streamline these problems has been developed by researchers at MIT, the University of Waterloo, and the University of Southern California.

    The team describes their theoretical proposal this week in the journal Nature Communications. Seth Lloyd, the paper’s lead author and the Nam P. Suh Professor of Mechanical Engineering, explains that algebraic topology is key to the new method. This approach, he says, helps to reduce the impact of the inevitable distortions that arise every time someone collects data about the real world.

    In a topological description, basic features of the data (How many holes does it have? How are the different parts connected?) are considered the same no matter how much they are stretched, compressed, or distorted. Lloyd explains that it is often these fundamental topological attributes “that are important in trying to reconstruct the underlying patterns in the real world that the data are supposed to represent.”

    It doesn’t matter what kind of dataset is being analyzed, he says. The topological approach to looking for connections and holes “works whether it’s an actual physical hole, or the data represents a logical argument and there’s a hole in the argument. This will find both kinds of holes.”

    Using conventional computers, that approach is too demanding for all but the simplest situations. Topological analysis “represents a crucial way of getting at the significant features of the data, but it’s computationally very expensive,” Lloyd says. “This is where quantum mechanics kicks in.” The new quantum-based approach, he says, could exponentially speed up such calculations.

    Lloyd offers an example to illustrate that potential speedup: If you have a dataset with 300 points, a conventional approach to analyzing all the topological features in that system would require “a computer the size of the universe,” he says. That is, it would take 2300 (two to the 300th power) processing units — approximately the number of all the particles in the universe. In other words, the problem is simply not solvable in that way.

    “That’s where our algorithm kicks in,” he says. Solving the same problem with the new system, using a quantum computer, would require just 300 quantum bits — and a device this size may be achieved in the next few years, according to Lloyd.

    “Our algorithm shows that you don’t need a big quantum computer to kick some serious topological butt,” he says.

    There are many important kinds of huge datasets where the quantum-topological approach could be useful, Lloyd says, for example understanding interconnections in the brain. “By applying topological analysis to datasets gleaned by electroencephalography or functional MRI, you can reveal the complex connectivity and topology of the sequences of firing neurons that underlie our thought processes,” he says.

    The same approach could be used for analyzing many other kinds of information. “You could apply it to the world’s economy, or to social networks, or almost any system that involves long-range transport of goods or information,” says Lloyd, who holds a joint appointment as a professor of physics. But the limits of classical computation have prevented such approaches from being applied before.

    While this work is theoretical, “experimentalists have already contacted us about trying prototypes,” he says. “You could find the topology of simple structures on a very simple quantum computer. People are trying proof-of-concept experiments.”

    Ignacio Cirac, a professor at the Max Planck Institute of Quantum Optics in Munich, Germany, who was not involved in this research, calls it “a very original idea, and I think that it has a great potential.” He adds “I guess that it has to be further developed and adapted to particular problems. In any case, I think that this is top-quality research.”

    The team also included Silvano Garnerone of the University of Waterloo in Ontario, Canada, and Paolo Zanardi of the Center for Quantum Information Science and Technology at the University of Southern California. The work was supported by the Army Research Office, Air Force Office of Scientific Research, Defense Advanced Research Projects Agency, Multidisciplinary University Research Initiative of the Office of Naval Research, and the National Science Foundation.

    See the full article here .

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  • richardmitnick 8:29 pm on December 20, 2015 Permalink | Reply
    Tags: , , Quantum Computing   

    From MIT Tech Review: “Google’s Quantum Dream Machine” 

    MIT Technology Review
    M.I.T Technology Review

    December 18, 2015
    Tom Simonite

    John Martinis has been researching how quantum computers could work for 30 years. Now he could be on the verge of finally making a useful one. No image credit.

    John Martinis used the arm of his reading glasses to indicate the spot where he intends to demonstrate an almost unimaginably powerful new form of computer in a few years. It is a cylindrical socket an inch and a half across, at the bottom of a torso-sized stack of plates, blocks, and wires of brass, copper, and gold. The day after I met with him this fall, he loaded the socket with an experimental superconducting chip etched with a microscopic Google logo and cooled the apparatus to a hundredth of a degree Celsius above absolute zero. To celebrate that first day of testing the machine, Martinis threw what he called “a little party” at a brewpub with colleagues from his newly outfitted Google lab in Santa Barbara, California.

    That party was nothing compared with the celebration that will take place if Martinis and his group can actually create the wonder computer they seek. Because it would harness the strange properties of quantum physics that arise in extreme conditions like those on the ultracold chip, the new computer would let a Google coder run calculations in a coffee break that would take a supercomputer of today millions of years. The software that Google has developed on ordinary computers to drive cars or answer questions could become vastly more intelligent. And earlier-stage ideas bubbling up at Google and its parent company, such as robots that can serve as emergency responders or software that can converse at a human level, might become real.

    The theoretical underpinnings of quantum computing are well established. And physicists can build the basic units, known as qubits, out of which a quantum computer would be made. They can even operate qubits together in small groups. But they have not made a fully working, practical quantum computer.

    Martinis is a towering figure in the field: his research group at the University of California, Santa Barbara, has demonstrated some of the most reliable qubits around and gotten them running some of the code a quantum computer would need to function. He was hired by Google in June 2014 after persuading the company that his team’s technology could mature rapidly with the right support. With his new Google lab up and running, Martinis guesses that he can demonstrate a small but useful quantum computer in two or three years. “We often say to each other that we’re in the process of giving birth to the quantum computer industry,” he says.

    Google and quantum computing are a match made in algorithmic heaven. The company is often said to be defined by an insatiable hunger for data. But Google has a more pressing strategic addiction: to technology that extracts information from data, and even creates intelligence from it. The company was founded to commercialize an algorithm for ranking Web pages, and it built its financial foundations with systems that sell and target ads. More recently, Google has invested heavily in the development of AI software that can learn to understand language or images, perform basic reasoning, or steer a car through traffic—all things that remain tricky for conventional computers but should be a breeze for quantum ones. “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything,” Google’s CEO, Sundar Pichai, recently informed investors. Supporting that effort would be the first of many jobs for Martinis’s new quantum industry.

    Dream maker

    As recently as last week the prospect of a quantum computer doing anything useful within a few years seemed remote. Researchers in government, academic, and corporate labs were far from combining enough qubits to make even a simple proof-of-principle machine. A well-funded Canadian startup called D-Wave Systems sold a few of what it called “the world’s first commercial quantum computers” but spent years failing to convince experts that the machines actually were doing what a quantum computer should (see The CIA and Jeff Bezos Bet on Quantum Computing).

    Then NASA summoned journalists to building N-258 at its Ames Research Center in Mountain View, California, which since 2013 has hosted a D-Wave computer bought by Google. There Hartmut Neven, who leads the Quantum Artificial Intelligence lab Google established to experiment with the D-Wave machine, unveiled the first real evidence that it can offer the power proponents of quantum computing have promised. In a carefully designed test, the superconducting chip inside D-Wave’s computer—known as a quantum annealer—had performed 100 million times faster than a conventional processor.

    However, this kind of advantage needs to be available in practical computing tasks, not just contrived tests. “We need to make it easier to take a problem that comes up at an engineer’s desk and put it into the computer,” said Neven, a talkative machine-learning expert. That’s where Martinis comes in. Neven doesn’t think D-Wave can get a version of its quantum annealer ready to serve Google’s engineers quickly enough, so he hired Martinis to do it. “It became clear that we can’t just wait,” Neven says. “There’s a list of shortcomings that need to be overcome in order to arrive at a real technology.” He says the qubits on D-Wave’s chip are too unreliable and aren’t wired together thickly enough. (D-Wave’s CEO, Vern Brownell, responds that he’s not worried about competition from Google.)

    Google will be competing not only with whatever improvements D-Wave can make, but also with Microsoft and IBM, which have substantial quantum computing projects of their own (see Microsoft’s Quantum Mechanics and IBM Shows Off a Quantum Computing Chip). But those companies are focused on designs much further from becoming practically useful. Indeed, a rough internal time line for Google’s project estimates that Martinis’s group can make a quantum annealer with 100 qubits as soon as 2017. D-Wave’s latest chip already has 1,097 qubits, but Neven says a high-quality chip with fewer qubits will probably be useful for some tasks nonetheless. A quantum annealer can run only one particular algorithm, but it happens to be one well suited to the areas Google most cares about. The applications that could particularly benefit include pattern recognition and machine learning, says William Oliver, a senior staff member at MIT Lincoln Laboratory who has studied the potential of quantum computing.

    John Martinis, 57, is the perfect person to wrestle a mind-bogglingly complex strand of quantum physics research into a new engineering discipline. Not only can he dive into the esoteric math, but he loves to build things. Operating even a single qubit is a puzzle assembled from deep quantum theory, solid-state physics, materials science, microfabrication, mechanical design, and conventional electronics. Martinis, who is tall with a loud, friendly voice, makes a point of personally mastering the theory and technical implementation of every piece. Giving a tour of his new lab at Google, he is as excited about the new soldering irons and machine tools in the conventional workshop area as he is about the more sophisticated equipment that chills chips and operates them. “To me it’s fun,” he says. “I’ve been able to do experiments no one else could do, because I could build my own electronics.”

    This experimental chip, etched with the Google logo, is cooled to just above absolute zero in order to generate quantum effects.No image credit.

    Martinis and his team have to be adept at so many things because qubits are fickle. They can be made in various ways—Martinis uses aluminum loops chilled with tiny currents until they become superconductors—but all represent data by means of delicate quantum states that are easily distorted or destroyed by heat and electromagnetic noise, potentially ruining a calculation.

    Qubits use their fragile physics to do the same thing that transistors use electricity to do on a conventional chip: represent binary bits of information, either 0 or 1. But qubits can also attain a state, called a superposition, that is effectively both 0 and 1 at the same time. Qubits in a superposition can become linked by a phenomenon known as entanglement, which means an action performed on one has instant effects on the other. Those effects allow a single operation in a quantum computer to do the work of many, many more operations in a conventional computer. In some cases, a quantum computer’s advantage over a conventional one should grow exponentially with the amount of data to be worked on.

    The difficulty of creating qubits that are stable enough is the reason we don’t have quantum computers yet. But Martinis has been working on that for more than 11 years and thinks he’s nearly there. The coherence time of his qubits, or the length of time they can maintain a superposition, is tens of microseconds—about 10,000 times the figure for those on D-Wave’s chip.

    Martinis’s confidence in his team’s hardware even has him thinking he can build Google an alternative to a quantum annealer that would be even more powerful. A universal quantum computer, as it would be called, could be programmed to take on any kind of problem, not just one kind of math. The theory behind that approach is actually better understood than the one for annealers, in part because most of the time and money in quantum computing research have been devoted to universal quantum computing. But qubits have not been reliable enough to translate the theory into a working universal quantum computer.

    This structure of metal plates is necessary to cool and shield quantum chips. No image credit.

    Until March, that is, when Martinis and his team became the first to demonstrate qubits that crossed a crucial reliability threshold for a universal quantum computer (see Google Researchers Make Quantum Computing Components More Reliable). They got a chip with nine qubits to run part of an error-checking program, called the surface code, that’s necessary for such a computer to operate (IBM has since gotten part of the surface code working on four qubits). “We demonstrated the technology to a point where I knew we could scale up,” says Martinis. “This was for real.”

    Martinis aims to show off a complete universal quantum computer with about 100 qubits around the same time he delivers Google’s new quantum annealer, in about two years. That would be a milestone in computer science, but it would be unlikely to help Google’s programmers right away. Such is the complexity of the surface code that although a chip with 100 qubits could run the error-checking program, it would be unable to do any useful work in addition to that, says Robert McDermott, who leads a quantum computing research group at the University of Wisconsin. Yet Martinis thinks that once he can get his qubits reliable enough to put 100 of them on a universal quantum chip, the path to combining many more will open up. “This is something we understand pretty well,” he says. “It’s hard to get coherence but easy to scale up.”

    Stupid algorithms

    When Martinis explains why his technology is needed at Google, he doesn’t spare the feelings of the people working on AI. “Machine-learning algorithms are really kind of stupid,” he says, with a hint of wonder in his voice. “They need so many examples to learn.”

    Indeed, the machine learning used by Google and other computing companies is pathetic next to the way humans or animals pick up new skills or knowledge. Teaching a piece of software new tricks, such as how to recognize cars and cats in photos, generally requires thousands or millions of carefully curated and labeled examples. Although a technique called deep learning has recently produced striking advances in the accuracy with which software can learn to interpret images and speech, more complex faculties like understanding the nuances of language remain out of machines’ reach.

    Figuring out how Martinis’s chips can make Google’s software less stupid falls to Neven. He thinks that the prodigious power of qubits will narrow the gap between machine learning and biological learning—and remake the field of artificial intelligence. “Machine learning will be transformed into quantum learning,” he says. That could mean software that can learn from messier data, or from less data, or even without explicit instruction. For instance, Google’s researchers have designed an algorithm they think could allow machine-learning software to pick up a new trick even if as much as half the example data it’s given is incorrectly labeled. Neven muses that this kind of computational muscle could be the key to giving computers capabilities today limited to humans. “People talk about whether we can make creative machines–the most creative systems we can build will be quantum AI systems,” he says.

    More practically, with only D-Wave’s machine to practice on for now, Google’s researchers can’t do much more than speculate about what exactly they could or should do with the chips Martinis is building. Even when they do get their hands on them, it will take time to invent and build the infrastructure needed to operate large numbers of the exotic devices so they can contribute materially to Google’s business.

    Neven is confident that Google’s quantum craftsmen and his team can get through all that. He pictures rows of superconducting chips lined up in data centers for Google engineers to access over the Internet relatively soon. “I would predict that in 10 years there’s nothing but quantum machine learning–you don’t do the conventional way anymore,” he says. A smiling Martinis warily accepts that vision. “I like that, but it’s hard,” he says. “He can say that, but I have to build it.”

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  • richardmitnick 10:17 am on December 7, 2015 Permalink | Reply
    Tags: , Quantum Computing,   

    From UNSW: “Major innovation boost for UNSW’s quantum mission” 

    U NSW bloc

    University of New South Wales

    07 Dec 2015
    Denise Knight

    Professor Michelle Simmons

    UNSW Australia welcomes the federal government’s announcement today of a $26 million investment in the University’s world-leading quantum computing research.

    The major funding boost over five years will support the development of silicon quantum computing technology in Australia in association with the Australian Research Council (ARC) Centre for Quantum Computation and Communication Technology, headquartered at UNSW.

    It is based on a focused, ambitious and targeted program to build a 10 qubit prototype – demonstrating all the fundamental criteria of a scalable quantum computer – within five years.

    The announcement has been made as part of the federal government’s $1.1 billion National Innovation and Science Agenda.

    “Australia needs to take advantage of and evolve with the rapid pace of this technological change,” the government’s statement said.

    “If Australian researchers are successful in developing a quantum computing capability, it would mean the development of a valuable new industry.

    “Quantum computers have the potential to solve problems in minutes that would take conventional computers centuries. The technology will transform Australian and global business, from banks undertaking financial analysis, transport companies planning optimal logistic routes, or improvements in medical drug design.”

    UNSW President and Vice-Chancellor Professor Ian Jacobs said: “UNSW researchers, led by Scientia Professor Michelle Simmons, are currently leading the global race to build the world’s first quantum computer.

    “I applaud the government’s vision in recognising the global significance of this research. It is a wonderful funding boost and follows a substantial investment by UNSW in this ground-breaking work,” Professor Jacobs said.

    Director of the ARC Centre of Excellence for Quantum Computation and Communication Technology Professor Simmons welcomed the announcement.

    “We are delighted by this news. Quantum computing is a transformational technology in which Australia has an international lead, and there is now an opportunity for translating this research here in Australia. It is based on a focused, ambitious and targeted program to build a 10 qubit prototype – demonstrating all the fundamental criteria of a scalable quantum computer – within five years,” said Professor Simmons.

    “This announcement sends a very powerful message about supporting internationally leading Australian research in areas of breakthrough technology. Our program has had backing from visionary Australian companies who are technology leaders in their space, such as the Commonwealth Bank, who see the long-term benefit to their organisation.”

    Without a boost to public and private investment, Australia would have been at risk of missing out on the long-term benefits of the research conducted at the ARC Centre of Excellence, Professor Simmons said.

    Quantum computing in silicon is an entirely new system at the atomic-scale and Australia leads the world in single atom engineering. In the long term, one of these next-generation quantum computers has the potential to exceed the combined power of all the computers now on Earth for certain high value applications. They will be ideal for searching huge databases much faster than conventional computers, and for performing tasks beyond the capability of even the most powerful supercomputers, such as modelling complex biological molecules for drug development.

    Broader innovation strategy welcomed

    Professor Jacobs said the federal government’s broader strategy to boost the country’s innovation capacity is an important development and recognises the essential role greater collaboration between industry and universities will play in securing future economic and social prosperity.

    “The national Innovation Statement is an important contribution to the ongoing effort by governments, universities, industry and research institutions to scale up innovation and work more collaboratively for a far greater impact.

    “Universities clearly play a key role in that agenda and by working effectively with industry, government and leaders across the entire innovation ecosystem, we have a profound impact,” he said.

    “UNSW welcomes the Prime Minister’s commitment to major research infrastructure, which supports the entire innovation agenda. We particularly welcome the long-term commitment over a 10-year period for the National Collaborative Research Infrastructure Strategy.”

    This announcement sends a very powerful message about supporting internationally leading Australian research in areas of breakthrough technology.

    UNSW is at the forefront of innovation. It leads nationally in industry-linked research funding under the ARC Linkage Grant scheme; has the largest student start-up program in Australia; and was one of the first adopters of the world-leading easy access IP scheme.

    “We see the creation of intellectual property and knowledge as a national treasure and asset, to be shared with society. We share our knowledge and innovation with industry, government and society through our teaching, consultancy, collaborative and contract research, licensing, company creation, networking and professional development,” Professor Jacobs said.

    The University’s new 10-year strategy, UNSW 2025, includes a bold commitment to significantly scale up our innovation efforts. Some of these commitments include:

    Expanding UNSW industry incubators on campus and 100 more student start-ups per year
    A new Innovation Park adjacent to UNSW Randwick campus by 2020
    Opening an internationally accredited Clinical Health Research Facility
    A new Academic Health Science Partnership (three universities, three local health districts and six medical research institutes)
    1000 new industry internships and a Fellowship Scheme
    Expanding our Easy Access IP model and an Easy Access Innovation Portal
    Vouchers for SMEs, entrepreneurs and start-ups to purchase university engagement.

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  • richardmitnick 10:04 am on December 3, 2015 Permalink | Reply
    Tags: , Quantum Computing,   

    From TUM: “Quantum computer made of standard semiconductor materials” 

    Techniche Universitat Munchen

    Techniche Universitat Munchen

    Electron in a quantum dot influenced by the spins in the proximity – Image: Fabian Flassik / TUM

    Prof. Jonathan J. Finley
    Walter Schottky Institute
    Technical University of Munich
    85748 Garching; Germany
    Tel.: +49 89 289 11481

    Physicists at the Technical University of Munich, the Los Alamos National Laboratory and Stanford University (USA) have tracked down semiconductor nanostructure mechanisms that can result in the loss of stored information – and halted the amnesia using an external magnetic field. The new nanostructures comprise common semiconductor materials compatible with standard manufacturing processes.

    Quantum bits, qubits for short, are the basic logical elements of quantum information processing (QIP) that may represent the future of computer technology. Since they process problems in a quantum-mechanical manner, such quantum computers might one day solve complex problems much more quickly than currently possible, so the hope of researchers.

    In principle, there are various possibilities of implementing qubits: photons are an option equally as viable as confined ions or atoms whose states can be altered in a targeted manner using lasers. The key questions regarding their potential use as memory units are how long information can be stored in the system and which mechanisms might lead to a loss of information.

    A team of physicists headed by Alexander Bechtold and Professor Jonathan Finley at the Walter Schottky Institute of the Technical University of Munich and the Excellence Cluster Nanosystems Initiative Munich (NIM) have now presented a system comprising a single electron trapped in a semiconductor nanostructure. Here, the electron’s spin serves as the information carrier.

    The researchers were able to precisely demonstrate the existence of different data loss mechanisms and also showed that stored information can nonetheless be retained using an external magnetic field.

    Electrons trapped in a quantum dot

    The TUM physicists evaporated indium gallium arsenide onto a gallium arsenide substrate to form their nanostructure. As a result of the different lattice spacing of the two semiconductor materials strain is produced at the interface between the crystal grids. The system thus forms nanometer-scale “hills” – so-called quantum dots.

    When the quantum dots are cooled down to liquid helium temperatures and optically excited, a singe electron can be trapped in each of the quantum dots. The spin states of the electrons can then be used as information stores. Laser pulses can read and alter the states optically from outside. This makes the system ideal as a building block for future quantum computers.

    Spin up or spin down correspond to the standard logical information units 0 and 1. But, on top of this come additional intermediate states of quantum mechanical up and down superpositions.

    Hitherto unknown memory loss mechanisms

    However, there is one problem: “We found out that the strain in the semiconductor material leads to a new and until recently unknown mechanism that results in the loss of quantum information,” says Alexander Bechtold. The strain creates tiny electric fields in the semiconductor that influence the nuclear spin orientation of the atomic nuclei.

    “It’s a kind of piezoelectric effect,” says Bechthold. “It results in uncontrolled fluctuations in the nuclear spins.” These can, in turn, modify the spin of the electrons, i.e. the stored information. The information is lost within a few hundred nanoseconds.

    In addition, Alexander Bechthold’s team was able to provide concrete evidence for further information loss mechanisms, for example that electron spins are generally influenced by the spins of the surrounding 100,000 atomic nuclei.

    Preventing quantum mechanical amnesia

    “However, both loss channels can be switched off when a magnetic field of around 1.5 tesla is applied,” says Bechtold. “This corresponds to the magnetic field strength of a strong permanent magnet. It stabilizes the nuclear spins and the encoded information remains intact.”

    “Overall, the system is extremely promising,” according to Jonathan Finley, head of the research group. “The semiconductor quantum dots have the advantage that they harmonize perfectly with existing computer technology since they are made of similar semiconductor material.” They could even be equipped with electrical contacts, allowing them to be controlled not only optically using a laser, but also using voltage pulses.

    The research was funded by the European Union (S3 Nano and BaCaTeC), the US Department of Energy, the US Army Research Office (ARO), the German Research Foundation DFG (excellence cluster Nanosystems Munich (NIM) and SFB 631), the Alexander von Humboldt Foundation as well as the TUM Institute for Advanced Study (Focus Group Nanophotonics and Quantum Optics).


    Three-stage decoherence dynamics of an electron spin qubit in an optically active quantum dot; Alexander Bechtold, Dominik Rauch, Fuxiang Li, Tobias Simmet, Per-Lennart Ardelt, Armin Regler, Kai Müller, Nikolai A. Sinitsyn and Jonathan J. Finley; Nature Physics, 11, 1005-1008 (2015) – DOI: 10.1038/nphys3470

    See the full article here .

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    Techniche Universitat Munchin Campus

    Technische Universität München (TUM) is one of Europe’s top universities. It is committed to excellence in research and teaching, interdisciplinary education and the active promotion of promising young scientists. The university also forges strong links with companies and scientific institutions across the world. TUM was one of the first universities in Germany to be named a University of Excellence. Moreover, TUM regularly ranks among the best European universities in international rankings.

  • richardmitnick 8:32 pm on September 28, 2015 Permalink | Reply
    Tags: , , Quantum Computing,   

    From WIRED: “The Other Way A Quantum Computer Could Revive Moore’s Law” 

    Wired logo


    Cade Metz

    D-Wave’s quantum chip. Google

    Google is upgrading its quantum computer. Known as the D-Wave, Google’s machine is making the leap from 512 qubits—the fundamental building block of a quantum computer—to more than a 1000 qubits. And according to the company that built the system, this leap doesn’t require a significant increase in power, something that could augur well for the progress of quantum machines.

    Together with NASA and the Universities Space Research Association, or USRA, Google operates its quantum machine at the NASA Ames Research center not far from its Mountain View, California headquarters. Today, D-Wave Systems, the Canadian company that built the machine, said it has agreed to provide regular upgrades to the system—keeping it “state-of-the-art”—for the next seven years. Colin Williams, director of business development and strategic partnerships for D-Wave, calls this “the biggest deal in the company’s history.” The system is also used by defense giant Lockheed Martin, among others.

    Though the D-Wave machine is less powerful than many scientists hope quantum computers will one day be, the leap to 1000 qubits represents an exponential improvement in what the machine is capable of. What is it capable of? Google and its partners are still trying to figure that out. But Google has said it’s confident there are situations where the D-Wave can outperform today’s non-quantum machines, and scientists at the University of Southern California have published research suggesting that the D-Wave exhibits behavior beyond classical physics.

    Over the life of Google’s contract, if all goes according to plan, the performance of the system will continue to improve. But there’s another characteristic to consider. Williams says that as D-Wave expands the number of qubits, the amount of power needed to operate the system stays roughly the same. “We can increase performance with constant power consumption,” he says. At a time when today’s computer chip makers are struggling to get more performance out of the same power envelope, the D-Wave goes against the trend.

    The Qubit

    A quantum computer operates according to the principles of quantum mechanics, the physics of very small things, such as electrons and photons. In a classical computer, a transistor stores a single “bit” of information. If the transistor is “on,” it holds a 1, and if it’s “off,” it holds a 0. But in quantum computer, thanks to what’s called the superposition principle, information is held in a quantum system that can exist in two states at the same time. This “qubit” can store a 0 and 1 simultaneously.

    Two qubits, then, can hold four values at any given time (00, 01, 10, and 11). And as you keep increasing the number of qubits, you exponentially increase the power of the system. The problem is that building a qubit is a extreme difficult thing. If you read information from a quantum system, it “decoheres.” Basically, it turns into a classical bit that houses only a single value.

    D-Wave believes it has found a way around this problem. It released its first machine, spanning 16 qubits, in 2007. Together with NASA, Google started testing the machine when it reached 512 qubits a few years back. Each qubit, D-Wave says, is a superconducting circuit—a tiny loop of flowing current—and these circuits are dropped to extremely low temperatures so that the current flows in both directions at once. The machine then performs calculations using algorithms that, in essence, determine the probability that a collection of circuits will emerge in a particular pattern when the temperature is raised.

    Reversing the Trend

    Some have questioned whether the system truly exhibits quantum properties. But researchers at USC say that the system appears to display a phenomenon called “quantum annealing” that suggests it’s truly operating in the quantum realm. Regardless, the D-Wave is not a general quantum computer—that is, it’s not a computer for just any task. But D-Wave says the machine is well-suited to “optimization” problems, where you’re facing many, many different ways forward and must pick the best option, and to machine learning, where computers teach themselves tasks by analyzing large amount of data.

    D-Wave says that most of the power needed to run the system is related to the extreme cooling. The entire system consumes about 15 kilowatts of power, while the quantum chip itself uses a fraction of a microwatt. “Most of the power,” Williams says, “is being used to run the refrigerator.” This means that the company can continue to improve its performance without significantly expanding the power it has to use. At the moment, that’s not hugely important. But in a world where classical computers are approaching their limits, it at least provides some hope that the trend can be reversed.

    See the full article here .

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  • richardmitnick 8:11 pm on September 10, 2015 Permalink | Reply
    Tags: , Quantum Computing,   

    From UNSW: “Quantum industry needs more Australian government support” 

    U NSW bloc

    University of New South Wales

    10 Sep 2015
    Myles Gough

    Australia may win the race to build a revolutionary quantum computer, but UNSW global research leader Michelle Simmons warns that without investment we risk losing the industry offshore.

    Scientia Professor Michelle Simmons addresses the Chief Executive Women annual dinner event in Sydney. Photo: supplied

    Australia may be poised to win the international race to build a quantum computer, but without investment to scale-up and industrialise the technology, the long-term benefits could be lost offshore, says UNSW Scientia Professor Michelle Simmons.

    Two weeks after winning the CSIRO Eureka Prize for Leadership in Science, Simmons is again in the spotlight, delivering a guest lecture at the Chief Executive Women’s 2015 annual dinner in Sydney.

    As the Director of the Australian Research Council Centre of Excellence for Quantum Computation and Communication Technology, Simmons has been instrumental in positioning Australia as the front-runner in the global race to build a quantum computer based in silicon.

    Addressing more than 900 of the nation’s top female leaders from the public and private sectors, Simmons spoke about her passion for physics and the importance of science education in high schools.

    She also warned that Australia is at risk of missing out on the long-term benefits of her world-leading research conducted in her Centre.

    “We are at risk of all the technology we have developed, and the trained human capital, being transferred overseas with little long-term benefit to Australia. The significance of this work to Australia should not be underestimated.”

    “Australia has established a unique approach [to developing a quantum computer] with a competitive edge that has been described by our US funding agencies as having a two to three year lead over the rest of the world,” says Simmons.

    Despite leading the world, she says “there is no mechanism in Australia to scale-up what we have achieved and to translate it industrially”.

    “We are at risk of all the technology we have developed, and the trained human capital, being transferred overseas with little long-term benefit to Australia. The significance of this work to Australia should not be underestimated.”

    Michelle Simmons, WINNER 2015 Eureka Prize for Leadership in Science
    Download mp4 here.

    Exponential increase

    Quantum computers are predicted to provide an extraordinary speed-up in computational power. For each quantum [bit] added to a circuit, the processing power doubles.

    Instead of performing calculations one after the other like a conventional computer, these futuristic machines – which exploit the unusual quantum properties of single atoms, the fundamental constituents of all matter – work in parallel, calculating all possible outcomes at the same time.

    They will be ideal for encrypting information and searching huge databases much faster than conventional computers, and for performing tasks beyond the capability of even the most powerful supercomputers, such as modelling complex biological molecules for drug development.

    “It is predicted that 40% of all Australian industry will be impacted if we realise this technology.”

    Simmons says an Australian-made prototype system using technologies patented by her team, where all functional components are manufactured and controlled on the atomic-scale, could be ready within five years.

    The Commonwealth Bank of Australia recently invested $5 million into the project and Simmons says she is “negotiating contracts with several other major computing, communications and aerospace industries both here and abroad”.

    “We are at risk of all the technology we have developed, and the trained human capital, being transferred overseas with little long-term benefit to Australia.” NO image credit.

    But the rest of the world is making giant strides, and putting up big money: the UK government recently put forward £270 million and the Dutch government €300 million to support quantum information research.

    “Australia is a fantastic place to innovate,” says Simmons. “We attract the best young people from across the world and we undertake leading international science.

    “Our challenge going forward is how to create the environment, opportunities and industries to keep them here.”

    Choosing Australia

    Simmons can speak from first-hand experience. She came to Australia back in 1999 for two reasons: the first, she says, “was academic freedom to pursue something ambitious and high risk”, and the second “was Australia’s ‘can do’ attitude”.

    In the mid-1990s, Simmons was working as an experimental quantum physicist at the University of Cambridge. She had mastered how to design, fabricate and measure electrical devices, which displayed strong quantum effects, and was looking for a new challenge: “to leapfrog the global IT industry and create devices at the atomic scale.”

    When she was awarded an Australian Fellowship to come to UNSW, she withdrew applications for a fellowship to remain at Cambridge, and another for a faculty position at Stanford University in the US.

    “The UK offered years surrounded by pessimistic academics, who would tell you a thousand reasons why your ideas would not work,” she says. “The US offered a highly competitive environment where you would fight both externally and internally for funds.

    “Australia offered independent fellowships, ability to work on large projects with other academics and the ‘can do’ attitude to give it a go.”

    Once in Australia, she set up a team that is still “unique internationally”.

    “Our goal was to adapt the scanning tunnelling microscope (STM) developed by IBM not just to image atoms, but to manipulate them and to make a functional electronic device where the active component is a single atom.”

    Inside the Australian National Fabrication Facility (ANFF) at UNSW, where much of the work on the quantum computer is carried out. Photo: ANFF-NSW/Paul Henderson-Kelly

    Critics, including senior scientists at IBM, believed there were at least eight insurmountable technical challenges.

    “The consensus view within the scientific community was that the chances … were near impossible,” she says.

    Simmons also had to combine two technologies in a way that had never been done before – the STM, which provides the ability to image and manipulate single atoms, and something known as molecular beam epitaxy, which provides the ability to grow a layer of material atom by atom.

    “When I told the two independent system manufacturers in Germany about the idea, they said they would make a laboratory to my design, but that there would be no guarantee that it would work. It was a $3.5 million risk.

    “To my delight it worked a factor of six better than I had hoped. And over the past decade we have systematically solved all those eight challenges that were predicted to block our way.”

    Her team has since developed the world’s first single atom transistor, as well as the narrowest conducting wires in silicon.

    “Australia is a fantastic place to innovate. We attract the best young people from across the world and we undertake leading international science”. Scientia Professor Michelle Simmons with Research Associate Bent Webber.

    Finding physics

    Simmons’ foray into physics began, in part, thanks to a chess match.

    Simmons used to watch her father and brother playing intense games in her family’s living room in south-east London in the 1970s.

    One day, the eight-year-old observer asked to play, eliciting a “somewhat dismissive and terse” response from her father, she recalls.

    “A girl! Wanting to play chess. Well, he indulged me and did something that I believe changed the course of my life,” she says.

    A surprise victory over her father, and several more over the coming weeks and months, saw Simmons take-up competitive chess at her father’s behest, ultimately becoming the London girls chess champion at 12.

    Ultimately, it wasn’t her calling, but chess, she says, taught her to challenge herself and other people’s expectations, and to pursue something she truly loved.

    That love ended up being physics: “I decided to pick the hardest thing that I could find that I enjoyed. Something that I could imagine I would always look forward to; would have to struggle to understand and would feel euphoric about when I had mastered it.”

    She also credits an excellent physics teacher who challenged and encouraged her – and even lined up a phone conversation with a US astronaut, after he learned this was Simmons’ dream profession.

    “The significance of having a passionate teacher, well versed in the subject they teach, cannot be underestimated,” she says. “Great teachers with high expectations challenge their students to be the best they can be.”

    Simmons has exemplified that belief. She was named NSW Scientist of the Year in 2012, was awarded an ARCl Laureate Fellowship in 2013, and in 2014 joined the likes of Stephen Hawking and Albert Einstein as an elected member of the American Academy of Arts and Science.

    “For me, the next challenge is not one of quantum physics but of finding a way working with Australian government, and industries both here and abroad, to establish a high-tech quantum industry in Australia,” she says.

    “To back its brightest and best and to ensure that Australian innovation stays here in Australia.

    “It’s a challenge that I am up for. I fundamentally believe it is the right thing to do and now is the right time to do it.”

    Based at UNSW, the ARC Centre of Excellence for Quantum Computation and Communication Technology is an interdisciplinary, multi-institute centre with more than 180 researchers. In addition to Simmons, key staff members at UNSW include Scientia Professors Andrew Dzurak and Sven Rogge, and Associate Professor Andrea Morello.

    See the full article for additional links.

    See the full article here .

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    U NSW Campus

    Welcome to UNSW Australia (The University of New South Wales), one of Australia’s leading research and teaching universities. At UNSW, we take pride in the broad range and high quality of our teaching programs. Our teaching gains strength and currency from our research activities, strong industry links and our international nature; UNSW has a strong regional and global engagement.

    In developing new ideas and promoting lasting knowledge we are creating an academic environment where outstanding students and scholars from around the world can be inspired to excel in their programs of study and research. Partnerships with both local and global communities allow UNSW to share knowledge, debate and research outcomes. UNSW’s public events include concert performances, open days and public forums on issues such as the environment, healthcare and global politics. We encourage you to explore the UNSW website so you can find out more about what we do.

  • richardmitnick 9:56 pm on August 12, 2015 Permalink | Reply
    Tags: , , Quantum Computing   

    From phys.org: “Quantum computing advance locates neutral atoms” 


    August 12, 2015
    A’ndrea Elyse Messer

    “We are studying neutral atom qubits because it is clear that you can have thousands in an apparatus,” said Weiss. “They don’t take up much space and they don’t interact with each other unless we want them to.” Credit: © iStock Photo monsitj

    For any computer, being able to manipulate information is essential, but for quantum computing, singling out one data location without influencing any of the surrounding locations is difficult. Now, a team of Penn State physicists has a method for addressing individual neutral atoms without changing surrounding atoms.

    “There are a set of things that we have to have to do quantum computing,” said David S. Weiss, professor of physics. “We are trying to step down that list and meet the various criteria. Addressability is one step.”

    Quantum computers are constructed and operate in completely different ways from the conventional digital computers used today. While conventional computers store information in bits, 1’s and 0’s, quantum computers store information in qubits. Because of a strange aspect of quantum mechanics called superposition, a qubit can be in both its 0 and 1 state at the same time. The methods of encoding information onto neutral atoms, ions or Josephson junctions—electronic devices used in precise measurement, to create quantum computers—are currently the subject of much research. Along with superposition, quantum computers will also take advantage of the quantum mechanical phenomena of entanglement, which can create a mutually dependent group of qubits that must be considered as a whole rather than individually.

    “Quantum computers can solve some problems that classical computers can’t,” said Weiss. “But they are unlikely to replace your laptop.”

    According to the researchers, one area where quantum computers will be valuable is in factoring very large numbers created by multiplying prime numbers, an approach used in creating difficult-to-break security codes.

    Weiss and his graduate students Yang Wang and Aishwarya Kumar, looked at using neutral atoms for quantum computing and investigated ways to individually locate and address an atom to store and retrieve information. They reported their results in a recent issue of Physical Review Letters.

    The researchers first needed to use laser light to create a 3-dimensional lattice of traps for neutral cesium atoms with no more than one atom at each lattice site. Other researchers are investigating ions and superconducting Josephson junctions, but Weiss’s team chose neutral atoms. Research groups at the University of Wisconsin, in France and elsewhere are also investigating neutral atoms for this purpose.

    “We are studying neutral atom qubits because it is clear that you can have thousands in an apparatus,” said Weiss. “They don’t take up much space and they don’t interact with each other unless we want them to.”

    However, Weiss notes that neutral atoms cannot be held in place as well as ions, because background atoms in the near vacuum occasionally knock them out of their traps.

    Once the cesium atoms are in place, the researchers set them to their lowest quantum state by cooling them. They then shift the internal quantum states of the atoms using two perpendicular, circularly polarized addressing beams. Many atoms are shifted, but the targeted atom, which is where the beams cross, is shifted by about twice as much as any other atom. This allows them to then uss microwaves to change the qubit state of the target atom without affecting the states of any other atoms.

    “One atom gate takes about half a millisecond,” said Weiss. “It takes about 5 microseconds to retarget to another atom.”

    Currently, the researchers can only fill about 50 percent of the laser atom traps with atoms, but they can perform quantum gates on those atoms with 93 percent fidelity and cross talk that is too small to measure. The goal is 99.99 percent fidelity. With continued improvements the researchers think that this goal is in reach.

    See the full article here.

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    About Phys.org in 100 Words

    Phys.org™ (formerly Physorg.com) is a leading web-based science, research and technology news service which covers a full range of topics. These include physics, earth science, medicine, nanotechnology, electronics, space, biology, chemistry, computer sciences, engineering, mathematics and other sciences and technologies. Launched in 2004, Phys.org’s readership has grown steadily to include 1.75 million scientists, researchers, and engineers every month. Phys.org publishes approximately 100 quality articles every day, offering some of the most comprehensive coverage of sci-tech developments world-wide. Quancast 2009 includes Phys.org in its list of the Global Top 2,000 Websites. Phys.org community members enjoy access to many personalized features such as social networking, a personal home page set-up, RSS/XML feeds, article comments and ranking, the ability to save favorite articles, a daily newsletter, and other options.

  • richardmitnick 7:59 am on April 27, 2015 Permalink | Reply
    Tags: , , Quantum Computing   

    From COSMOS: “Breakthrough for quantum computers” 

    Cosmos Magazine bloc


    27 Apr 2015
    Cathal O’Connell

    Andrea Morello at work. The computer he and his team are trying to build would use silicon chips not dissimilar to those in a conventional computer.Credit: Marcus Eno

    Electrical engineers at the University of New South Wales trying to develop a silicon quantum computer have cleared one of the last hurdles to building a simple device. The researchers have reported this missing piece in the journal Science Advances.

    “Once you have demonstrated all the parts, then it’s like a Lego box – you can start building up a large architecture by piecing its components together,” project leader Andrea Morello says.

    In their quest to build a silicon quantum computer, Morello and his colleagues have so far been perfecting its basic element, the “quantum bit”. This is a single phosphorus atom entombed in a silicon crystal. Using a carefully tuned magnetic field, the researchers can manipulate the atom’s quantum “spin”, flipping it up or down.

    That phosphorus atom is equivalent to a transistor in an ordinary computer. A transistor is on or off, which is how it represents the 1s and 0s of the binary code the computer uses to process instructions. A quantum bit is more complex. It can be spin-up, spin-down or in a “superposition” of both: 1 and 0 at the same time. Theoretically, this should enable a quantum computer to weigh multiple solutions to a complex problem at once, and solve it at phenomenal speed.

    A quantum computer is “not just a ‘faster’ computer,” Morello says. “They are the equivalent of a jet plane to a bicycle.”

    Last year the UNSW team showed they can write, read and store the spin of a single quantum bit with better than 99.99% accuracy using a magnetic field. But to carry out complex calculations, a quantum computer needs thousands, or even millions of quantum bits, that can all be individually controlled. And for that, the high frequency oscillating magnetic fields Morello has been using to master the control of a single quantum bit are not suitable.

    For a start, the magnetic field generators Morello and his team used are around $100,000 a pop. If they had to use one for each quantum bit in a large array, the cost would be astronomical. There is also a practical problem. Magnetic fields spread, making it impossible to control one quantum bit in an array without inadvertently affecting all its neighbours.

    In their latest work, carried out by experimental physicist Arne Laucht, Morello and his team found a way to control each quantum bit using a simple electrical pulse. Instead of each phosphorus atom having a dedicated magnetic field generator to control it, their new design floods the whole device with a single magnetic field.

    This field is broadcast at a frequency the phosphorus atoms are not tuned in to, and so they don’t feel its magnetic tug. But when a precise electrical pulse is applied to the quantum bit, the electron orbiting the phosphorus atom feels a strong force, stretching its orbit. This distortion to the electron’s orbit works like twisting a tuning knob on a radio – the phosphorus atom is tuned in to the frequency of the magnetic field being broadcast around it, which then causes the quantum bit to flip.

    By timing their electrical pulses, the team can tune the phosphorus atom in and out of the oscillating magnetic field, and so flip the phosphorus atom’s spin into any position they want – up, down or an intermediate superposition – without affecting its neighbours.

    This idea of combining electric and magnetic fields to control individual quantum bits in an array, called “A-gate” control, has been around since 1998. Bruce Kane, an American quantum physicist who was then working at UNSW, proposed it in a paper in Nature that Morello calls “visionary”. Now, 17 years later, technology has caught up with Kane’s ideas as we can now routinely make structures at the scale needed to build his design.

    Kane – now at the University of Maryland and not directly involved in Morello’s research – says he’s been impressed by the “outstanding” work on the design done at UNSW in recent years. The devices work even better than he anticipated. Back in 1998, Kane worried that imperfections in the materials would prevent the device from working as it should. But, he says, the recent work at UNSW, such as the demonstration of an A-gate, proves material imperfections “will not be a show-stopper for silicon quantum computing”.

    Kane cautions that we are still a long way from large-scale quantum computing in silicon, as the challenges that remain, such as moving quantum information around and controlling interactions between large numbers of spins, are daunting. “I continue to believe that large-scale silicon quantum computing will become a reality, but there is still a long, steep road ahead of us,” he says.

    The group is already at work on these challenges. Morello is confident they will have all the elements in place to build a small-scale test-system within 10 years.

    And as for a large-scale quantum computer capable of making useful calculations? Here, Morello is more coy: “To quote Niels Bohr, ‘It’s hard to make predictions, especially about the future’.”

    More on this topic from Cosmos: The quantum spinmeister

    Can physics protect us from Big Brother’s snooping?

    Quantum computing? Yes, no and maybe.

    See the full article here.

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