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  • richardmitnick 10:57 am on September 19, 2016 Permalink | Reply
    Tags: , Google, ,   

    From New Scientist- “Revealed: Google’s plan for quantum computer supremacy” 

    NewScientist

    New Scientist

    31 August 2016 [This just now appeared in social media.]
    Jacob Aron

    1
    Superconducting qubits are tops. UCSB

    The field of quantum computing is undergoing a rapid shake-up, and engineers at Google have quietly set out a plan to dominate.

    SOMEWHERE in California, Google is building a device that will usher in a new era for computing. It’s a quantum computer, the largest ever made, designed to prove once and for all that machines exploiting exotic physics can outperform the world’s top supercomputers.

    And New Scientist has learned it could be ready sooner than anyone expected – perhaps even by the end of next year.

    The quantum computing revolution has been a long time coming. In the 1980s, theorists realised that a computer based on quantum mechanics had the potential to vastly outperform ordinary, or classical, computers at certain tasks. But building one was another matter. Only recently has a quantum computer that can beat a classical one gone from a lab curiosity to something that could actually happen. Google wants to create the first.

    The firm’s plans are secretive, and Google declined to comment for this article. But researchers contacted by New Scientist all believe it is on the cusp of a breakthrough, following presentations at conferences and private meetings.
    .

    “They are definitely the world leaders now, there is no doubt about it,” says Simon Devitt at the RIKEN Center for Emergent Matter Science in Japan. “It’s Google’s to lose. If Google’s not the group that does it, then something has gone wrong.”

    We have had a glimpse of Google’s intentions. Last month, its engineers quietly published a paper detailing their plans (arxiv.org/abs/1608.00263). Their goal, audaciously named quantum supremacy, is to build the first quantum computer capable of performing a task no classical computer can.

    “It’s a blueprint for what they’re planning to do in the next couple of years,” says Scott Aaronson at the University of Texas at Austin, who has discussed the plans with the team.

    So how will they do it? Quantum computers process data as quantum bits, or qubits. Unlike classical bits, these can store a mixture of both 0 and 1 at the same time, thanks to the principle of quantum superposition. It’s this potential that gives quantum computers the edge at certain problems, like factoring large numbers. But ordinary computers are also pretty good at such tasks. Showing quantum computers are better would require thousands of qubits, which is far beyond our current technical ability.

    Instead, Google wants to claim the prize with just 50 qubits. That’s still an ambitious goal – publicly, they have only announced a 9-qubit computer – but one within reach.

    To help it succeed, Google has brought the fight to quantum’s home turf. It is focusing on a problem that is fiendishly difficult for ordinary computers but that a quantum computer will do naturally: simulating the behaviour of a random arrangement of quantum circuits.

    Any small variation in the input into those quantum circuits can produce a massively different output, so it’s difficult for the classical computer to cheat with approximations to simplify the problem. “They’re doing a quantum version of chaos,” says Devitt. “The output is essentially random, so you have to compute everything.”

    To push classical computing to the limit, Google turned to Edison, one of the most advanced supercomputers in the world, housed at the US National Energy Research Scientific Computing Center. Google had it simulate the behaviour of quantum circuits on increasingly larger grids of qubits, up to a 6 × 7 grid of 42 qubits.

    This computation is difficult because as the grid size increases, the amount of memory needed to store everything balloons rapidly. A 6 × 4 grid needed just 268 megabytes, less than found in your average smartphone. The 6 × 7 grid demanded 70 terabytes, roughly 10,000 times that of a high-end PC.

    Google stopped there because going to the next size up is currently impossible: a 48-qubit grid would require 2.252 petabytes of memory, almost double that of the top supercomputer in the world. If Google can solve the problem with a 50-qubit quantum computer, it will have beaten every other computer in existence.

    Eyes on the prize

    By setting out this clear test, Google hopes to avoid the problems that have plagued previous claims of quantum computers outperforming ordinary ones – including some made by Google.

    Last year, the firm announced it had solved certain problems 100 million times faster than a classical computer by using a D-Wave quantum computer, a commercially available device with a controversial history. Experts immediately dismissed the results, saying they weren’t a fair comparison.

    Google purchased its D-Wave computer in 2013 to figure out whether it could be used to improve search results and artificial intelligence. The following year, the firm hired John Martinis at the University of California, Santa Barbara, to design its own superconducting qubits. “His qubits are way higher quality,” says Aaronson.

    It’s Martinis and colleagues who are now attempting to achieve quantum supremacy with 50 qubits, and many believe they will get there soon. “I think this is achievable within two or three years,” says Matthias Troyer at the Swiss Federal Institute of Technology in Zurich. “They’ve showed concrete steps on how they will do it.”

    Martinis and colleagues have discussed a number of timelines for reaching this milestone, says Devitt. The earliest is by the end of this year, but that is unlikely. “I’m going to be optimistic and say maybe at the end of next year,” he says. “If they get it done even within the next five years, that will be a tremendous leap forward.”

    The first successful quantum supremacy experiment won’t give us computers capable of solving any problem imaginable – based on current theory, those will need to be much larger machines. But having a working, small computer could drive innovation, or augment existing computers, making it the start of a new era.

    Aaronson compares it to the first self-sustaining nuclear reaction, achieved by the Manhattan project in Chicago in 1942. “It might be a thing that causes people to say, if we want a full-scalable quantum computer, let’s talk numbers: how many billions of dollars?” he says.

    Solving the challenges of building a 50-qubit device will prepare Google to construct something bigger. “It’s absolutely progress to building a fully scalable machine,” says Ian Walmsley at the University of Oxford.

    For quantum computers to be truly useful in the long run, we will also need robust quantum error correction, a technique to mitigate the fragility of quantum states. Martinis and others are already working on this, but it will take longer than achieving quantum supremacy.

    Still, achieving supremacy won’t be dismissed.

    “Once a system hits quantum supremacy and is showing clear scale-up behaviour, it will be a flare in the sky to the private sector,” says Devitt. “It’s ready to move out of the labs.”

    “The field is moving much faster than expected,” says Troyer. “It’s time to move quantum computing from science to engineering and really build devices.”

    See the full article here .

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  • richardmitnick 8:03 pm on July 24, 2016 Permalink | Reply
    Tags: , Google, ,   

    From Science Alert: “Google’s quantum computer just accurately simulated a molecule for the first time” 

    ScienceAlert

    Science Alert

    22 JUL 2016
    DAVID NIELD

    1

    It’s a quantum world, we’re just living in it.

    Google’s engineers just achieved a milestone in quantum computing: they’ve produced the first completely scalable quantum simulation of a hydrogen molecule.

    That’s big news, because it shows similar devices could help us unlock the quantum secrets hidden in the chemistry that surrounds us.

    Researchers working with the Google team were able to accurately simulate the energy of hydrogen H2 molecules, and if we can repeat the trick for other molecules, we could see the benefits in everything from solar cells to medicines.

    These types of predictions are often impossible for ‘classical’ computers or take an extremely long time – working out the energy of something like a propane (C3H8) molecule would take a supercomputer in the region of 10 days.

    To achieve the feat, Google’s engineers teamed up with researchers from Harvard University, Lawrence Berkeley National Labs, UC Santa Barbara, Tufts University, and University College London in the UK.

    “While the energies of molecular hydrogen can be computed classically (albeit inefficiently), as one scales up quantum hardware it becomes possible to simulate even larger chemical systems, including classically intractable ones,” writes Google Quantum Software Engineer Ryan Babbush.

    Chemical reactions are quantum in nature, because they form highly entangled quantum superposition states. In other words, each particle’s state can’t be described independently of the others, and that causes problems for computers used to dealing in binary values of 1s and 0s.

    Enter Google’s universal quantum computer, which deals in qubits – bits that themselves can be in a state of superposition, representing both 1 and 0 at the same time.

    To run the simulation, the engineers used a supercooled quantum computing circuit called a variational quantum eigensolver (VQE) – essentially a highly advanced modelling system that attempts to mimic our brain’s own neural networks on a quantum level.

    2
    Credit: Google

    When the results of the VQE were compared against the actual released energy of the hydrogen molecule, the curves matched almost exactly, as you can see in the graph above.

    Babbush explains that going from qualitative and descriptive chemistry simulations to quantitative and predictive ones “could modernise the field so dramatically that the examples imaginable today are just the tip of the iceberg”.

    We’re dealing with the very first steps of modelling reality, and Google says we could start to see applications in all kinds of systems involving chemistry: improved batteries, flexible electronics, new types of materials, and more.

    One potential use is modelling the way bacteria produce fertiliser. The way humans produce fertiliser is extremely inefficient in terms of the environment, and costs 1-2 percent of the world’s energy per year – so any improvements in understanding the chemical reactions involved could produce massive gains.

    It’s still early days though, and while we’ve described Google’s hardware as a quantum computer for simplicity’s sake, there’s still an ongoing debate over whether we’ve cracked the quantum computing code just yet.

    Some say Google’s machine is still a prototype, part-quantum computer rather than the real deal. But while the scientists discuss the ins and outs of that argument, at least we’re starting to reap the benefits of the technology – and can look forward to a near future where computing power is almost unimaginable.

    The findings are published in Physical Review X.

    See the full article here .

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

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

    Wired logo

    Wired

    09.28.15
    Cade Metz

    1
    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 9:53 am on August 18, 2015 Permalink | Reply
    Tags: , Google,   

    From wired: “How Much Can You Save With Solar Panels? Just Ask Google” 

    Wired logo

    Wired

    08.18.15
    Cade Metz

    1
    Google

    If you’re considering solar power but aren’t quite sure it’s worth the expense, Google wants to point you in the right direction. Tapping its trove of satellite imagery and the latest in artificial intelligence, the company is offering a new online service that will instantly estimate how much you’ll save with a roof full of solar panels.

    3
    The first three concentrated solar power (CSP) units of Spain’s Solnova Solar Power Station in the foreground, with the PS10 and PS20 solar power towers in the background

    On Monday, the company unveiled Project Sunroof, a tool that calculates your home’s solar power potential using the same high-resolution aerial photos Google Earth uses to map the planet. After creating a 3-D model of your roof, the service estimates how much sun will hit those solar panels during the year and how much money the panels could save you over the next two decades. “People search Google all the time to learn about solar,” says Google’s Joel Conkling. “But it would be much more helpful if they could learn whether their particular roof is a good fit.”

    2
    Google

    The service is now available for homes in the San Francisco Bay Area, central California, and the greater Boston area. Google is headquartered in California, you see, and project creator Carl Elkin lives in Boston. Based in the company’s Cambridge offices, Elkin typically works on Google’s search engine, but he developed Project Sunroof during his “20 percent time“—that slice of the work week Googlers can use for independent projects.

    How Google Parses Your Roof

    Elkin’s own home has solar panels, and he once volunteered with Solarize Massachusetts to promote solar in the Bay State. He and Google see Project Sunroof pushing solar use further still. “We people want to go solar but don’t understand how cheap it is,” Elkin says. “I wanted people to understand that they can actually save money.”

    As Google notes in a blog post announcing Project Sunroof, the time is ripe for such a tool. “This is an extremely useful thing,” says Roland Winston, a professor at the University of California, Merced, who specializes in solar energy. “Solar technology is cheaper than ever.” Indeed, others have developed services along these lines, including academics and companies like Geostellar and Mapdwell.

    But Google’s service is a bit different. It has Google behind it—and the company is taking a particularly comprehensive approach. In analyzing satellite images of your home, Google uses “deep learning” neural networks to separate your roof from the surrounding trees and shadows. “Even a strong solar advocate like me wouldn’t recommend putting solar panels on your trees,” Elkin says. Mimicking the web of neurons in the human brain, this sort of neural network is the same technology used to recognize faces on Facebook or instantly translate from one language to another on Skype.

    Project Sunroof also simulates the shadows that typically cover your home on any given day (see animation above), and it tracks local weather patterns. “We’re able show how much energy is hitting each part of your roof,” Conkling says. And if you like, you can further hone that company’s calculations by providing how much you typically spend on electricity (otherwise, the service relies on public utility rates in your area).

    Beyond Elkin’s personal crusade, Google has a long history of advocating for solar power. In addition to investing in solar as a means of powering its global network of data centers, the company previously has invested in residential solar projects. But this isn’t mere charity work. Project Sunroof also recommends solar providers in your area, and it plans to eventually take a referral fee from these providers. “We want to help people understand the potential of solar power,” says Conkling. “But we can make some money off of that as well.”

    See the full article here.

    Please help promote STEM in your local schools.

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  • richardmitnick 2:34 pm on January 22, 2013 Permalink | Reply
    Tags: , Google, ScienceSprings   

    A Note About the ScienceSprings Fan Page at Facebook 

    Some time ago, as an experiment, I started a Fan Page for ScienceSprings at Facebook. I assumed it would be a total flop. I mean, you know, it is hard enough to get people to be interested in Science; how far can one go in asking for their allegiance.

    A problem occurred through my own ignorance: since I “Liked” the page, entires there went through to my own Facebook page, and I assumed that they went to all of my “friends” at Facebook. But my daughter let me know that was not the case. She commented that she had not seen anything from me in quite a while. So, I put a note on the Fan Page that I needed to stop using it.

    Now, just today, a friend explained to my how it all works. So I started in the business of bringing the Fan Page up to date from about December 8, 2012, until the present.

    Well, the digirati at Facebook went nuts, told me I was going “too fast” and “blocked” me for two days. Too fast? What does “digital” mean? How can one go “too fast”?

    Anyway, now that I know how it works, I will be re-energizing the page for all of those interested.

    BTW, ScienceSprings is now also at Google+. You can search “Richard Mitnick”, or, I am told, you can actually search “ScienceSprings”. If you are using Google+, please search me up and add me to your circles.

     
  • richardmitnick 8:45 am on April 22, 2011 Permalink | Reply
    Tags: , , Google, , ,   

    From the WCG Chat Room Forum: Google to Donate 1 Billion Core Hours to Research 

    i1

    1 billion core-hours of computational capacity for researchers
    April 07, 2011

    Posted by Dan Belov, Principal Engineer and David Konerding, Software Engineer

    We’re pleased to announce a new academic research grant program: Google Exacycle for Visiting Faculty. Through this program, we’ll award up to 10 qualified researchers with at least 100 million core-hours each, for a total of 1 billion core-hours. The program is focused on large-scale, CPU-bound batch computations in research areas such as biomedicine, energy, finance, entertainment, and agriculture, amongst others. For example, projects developing large-scale genomic search and alignment, massively scaled Monte Carlo simulations, and sky survey image analysis could be an ideal fit.

    Exacycle for Visiting Faculty expands upon our current efforts through University Relations to stimulate advances in science and engineering research, and awardees will participate through the Visiting Faculty Program. We invite full-time faculty members from universities worldwide to apply. All grantees, including those outside of the U.S., will work on-site at specific Google offices in the U.S. or abroad. The exact Google office location will be determined at the time of project selection.

    Technical Specifications and Requirements

    Proposals that are ideal for Google Exacycle include, but are not limited to, research projects like Folding@Home, Rosetta@Home, various [other] BOINC projects, and grid parameter sweeps. Other examples include large-scale genomic search and alignment, protein family modeling and sky survey image analysis.

    The best projects will have a very high number of independent work units, a high CPU to I/O ratio, and no inter-process communication (commonly described as Embarrassingly or Pleasantly Parallel). The higher the CPU to I/O rate, the better the match with the system. Programs must be developed in C/C++ and compiled via Native Client. Awardees will be able to consult an on-site engineering team.

    Preference will be given to projects that are fairly high-risk/high-reward with the potential to drastically transform the scientific landscape. Even projects that yield negative results can still provide public data that the community can continue to analyze. At completion of the project, we recommend, but do not require, that all the researcher’s data be made freely available to the academic community.

    We are excited to accept proposals starting today. The application deadline is 11:59 p.m. PST May 31, 2011. Applicants are encouraged to send in their proposals early as awards will be granted starting in June.

    More information and details on how to apply for a Google Exacycle for Visiting Faculty grant can be found on the Google Exacycle for Visiting Faculty website.

     
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