Commercial Quantum Computer?

Quantum computers could revolutionize the way we tackle problems that stump even the best classical computers.
Single atom transistor recently introduced has been seen as a tool that could lead the way to building a quantum computer. For general introduction how quantum computer work, read A tale of two qubits: how quantum computers work article.

D-Wave Announces Commercially Available Quantum Computer article tells that computing company D-Wave has announced that they’re selling a quantum computing system commercially, which they’re calling the D-Wave One. D-Wave system comes equipped with a 128-qubit processor that’s designed to perform discrete optimization operations. The processor uses quantum annealing to perform these operations.

D-Wave is advertisting a number of different applications for its quantum computing system, primarily in the field of artificial intelligence. According to the company, its system can handle virtually any AI application that can be translated to a Markov random field.


Learning to program the D-Wave One blog article tells that the processor in the D-Wave One – codenamed Rainier – is designed to perform a single mathematical operation called discrete optimization. It is a special purpose processor. When writing applications the D-Wave One is used only for the steps in your task that involve solving optimization problems. All the other parts of your code still run on your conventional systems of choice. Rainier solves optimization problems using quantum annealing (QA), which is a class of problem solving approaches that use quantum effects to help get better solutions, faster. Learning to program the D-Wave One is the first in a series of blog posts describing the algorithms we have run on D-Wave quantum computers, and how to use these to build interesting applications.

But is this the start of the quantum computers era? Maybe not. D-Wave Announces Commercially Available Quantum Computer article comments tell a story that this computer might not be the quantum computer you might be waiting for. It seem that the name “quantum computer” is a bit misleading for this product. There are serious controversies around the working and “quantumness” of the machine. D-Wave has been heavily criticized by some scientists in the quantum computing field. First sale for quantum computing article tells that uncertainty persists around how the impressive black monolith known as D-Wave One actually works. Computer scientists have long questioned whether D-Wave’s systems truly exploit quantum physics on their products.

Slashdot article D-Wave Announces Commercially Available Quantum Computer comments tell that this has the same central problem as before. D-Wave’s computers haven’t demonstrated that their commercial bits are entangled. There’s no way to really distinguish what they are doing from essentially classical simulated annealing. Recommended reading that is skeptical of D-Wave’s claims is much of what Scott Aaronson has wrote about them. See for example, although interestingly after he visited D-Wave’s labs in person his views changed slightly and became slightly more sympathetic to them

So it is hard to say if the “128 qubits” part is snake oil or for real. If the 128 “qubits” aren’t entangled at all, which means it is useless for any of the quantum algorithms that one generally thinks of. It seem that this device simply has 128 separate “qubits” that are queried individually, and is, essentially an augmented classical computer that gains a few minor advantages in some very specific algorithms (i.e. the quantum annealing algorithm) due to this qubit querying, but is otherwise indistinguishable from a really expensive classical computer for any other purpose. This has the same central problem as before: D-Wave’s computers haven’t demonstrated that their commercial bits are entangled.

Rather than constantly adding more qubits and issuing more hard-to-evaluate announcements, while leaving the scientific characterization of its devices in a state of limbo, why doesn’t D-Wave just focus all its efforts on demonstrating entanglement, or otherwise getting stronger evidence for a quantum role in the apparent speedup? There’s a reason why academic quantum computing groups focus on pushing down decoherence and demonstrating entanglement in 2, 3, or 4 qubits: because that way, at least you know that the qubits are qubits! Suppose D-Wave were marketing a classical, special-purpose, $10-million computer designed to perform simulated annealing, for 90-bit Ising spin glass problems with a certain fixed topology, somewhat better than an off-the-shelf computing cluster. Would there be even 5% of the public interest that there is now?


  1. Tomi Engdahl says:

    Microsoft Quantum Simulator Goes to Linux and Mac

    Everyone seems to be gearing up for the race to be the king of quantum computers. The latest salvo is Microsoft’s, they have announced that their quantum simulator will now run on macOS and Linux, with associated libraries and examples that are now fully open source. They have produced a video about the new release, which you can see below.

    Microsoft also claims that their simulator is much faster than before, especially on large simulations. Of course, really large simulations suffer from memory problems, not speed problems. You can run their simulator locally or on their Azure cloud.

    Microsoft pushes its Q# language which blends ideas from traditional languages with the quantum environment. There’s also experimental support for Python.

  2. Tomi Engdahl says:

    Quantum Algorithms Struggle Against Old Foe: Clever Computers

    February 1, 2018

    The quest for “quantum supremacy” – unambiguous proof that a quantum computer does something faster than an ordinary computer – has paradoxically led to a boom in quasi-quantum classical algorithms.

    A popular misconception is that the potential — and the limits — of quantum computing must come from hardware.

    50-qubit quantum machines now coming online from the likes of Intel and IBM have inspired predictions that we are nearing “quantum supremacy”

    But quantum supremacy is not a single, sweeping victory to be sought — a broad Rubicon to be crossed — but rather a drawn-out series of small duels. It will be established problem by problem, quantum algorithm versus classical algorithm. “With quantum computers, progress is not just about speed,” said Michael Bremner, a quantum theorist at the University of Technology Sydney. “It’s much more about the intricacy of the algorithms at play.”

    Paradoxically, reports of powerful quantum computations are motivating improvements to classical ones, making it harder for quantum machines to gain an advantage. “Most of the time when people talk about quantum computing, classical computing is dismissed, like something that is past its prime,” said Cristian Calude, a mathematician and computer scientist at the University of Auckland in New Zealand. “But that is not the case. This is an ongoing competition.”

    Before the dream of a quantum computer took shape in the 1980s, most computer scientists took for granted that classical computing was all there was.

  3. Tomi Engdahl says:

    Not even IBM is sure where its quantum computer experiments will lead
    But it will be fun to find out.

  4. Tomi Engdahl says:

    A Preview of Bristlecone, Google’s New Quantum Processor

    The goal of the Google Quantum AI lab is to build a quantum computer that can be used to solve real-world problems. Our strategy is to explore near-term applications using systems that are forward compatible to a large-scale universal error-corrected quantum computer. In order for a quantum processor to be able to run algorithms beyond the scope of classical simulations, it requires not only a large number of qubits.

    Today we presented Bristlecone, our new quantum processor, at the annual American Physical Society meeting in Los Angeles. The purpose of this gate-based superconducting system is to provide a testbed for research into system error rates and scalability of our qubit technology, as well as applications in quantum simulation, optimization, and machine learning.

    The guiding design principle for this device is to preserve the underlying physics of our previous 9-qubit linear array technology1, 2, which demonstrated low error rates for readout (1%), single-qubit gates (0.1%) and most importantly two-qubit gates (0.6%) as our best result. This device uses the same scheme for coupling, control, and readout, but is scaled to a square array of 72 qubits.

  5. Tomi Engdahl says:

    Google Joins the Quantum Race

    This week Google leaped into an increasingly competitive race in quantum computing with its Bristlecone 72-qubit processor.

    IBM has an operational 50-qubit quantum computer. Intel has shipped a 49-qubit quantum processor to its research partners for testing. Rigetti has an operational 19-qubit quantum computer. D-Wave has an operational 2048-qubit annealing quantum computer, and Fujitsu has an operational 1024-qubit annealing quantum computer. The last two are not so-called general-purpose systems, but they are still relevant to the industry racing to quantum supremacy.

    Quantum supremacy is the crossover point when quantum computers can solve or massively accelerate relevant problems that classical computers cannot solve today. Proof of quantum supremacy also requires that the result of the quantum program can be validated.

  6. Tomi Engdahl says:

    Silicon CMOS Architecture For A Spin-based Quantum Computer

    UNSW researchers have shown how a quantum computer can be manufactured using mostly standard silicon technology.

    University of New South Wales researchers have shown how a quantum computer can be manufactured using mostly standard silicon technology.

    Indeed, research teams all over the world are exploring different ways to design a working computing chip that can integrate quantum interactions. Now, these UNSW engineers believe they have cracked the problem, reimagining the silicon microprocessors we know to create a complete design for a quantum computer chip that can be manufactured using mostly standard industry processes and components.

    Complete design of a silicon quantum computer chip unveiled

  7. Tomi Engdahl says:

    Quantum Computers Strive to Break Out of the Lab

    Tech giants and startups alike want to bring quantum computing into the mainstream, but success is uncertain

  8. Tomi Engdahl says:

    Are We All Quantum Computers? Scientists Are Conducting Tests to Find Out
    It’s actually less crazy than it sounds.

  9. Tomi Engdahl says:

    Simple Quantum Computing in 150 Lines of Python

    What does it take to build a quantum computer? Lots of exotic supercooled hardware. However, creating a simulator isn’t nearly as hard and can give you a lot of insight into how this kind of computing works. A simulator doesn’t even have to be complicated. Here’s one that exists in about 150 lines of Python code.

    You might wonder what the value is. After all, there are plenty of well-done simulators including Quirk that we have looked at in the past. What’s charming about this simulator is that with only 150 lines of code, you can reasonably read the whole thing in a sitting and gain an understanding of how the different operations really affect the state.

  10. Tomi Engdahl says:

    20 Entangled Qubits Bring the Quantum Computer Closer

    In 1981, Richard Feynman suggested that a quantum computer might be able to simulate the evolution of quantum systems much better than classical computers. Except for several proof-of-principle experiments, no working quantum computer has yet been built.

    While researchers have succeeded in creating qubits that survive long enough to take part in computations, entangling qubits so that they can form quantum registers that are large enough for any practical purposes has eluded experimenters up to now.

  11. Tomi Engdahl says:

    Present and Future of Quantum Computing

    Modern computing is a staple of contemporary society, underpinning everything from the internet and e-commerce to space exploration and mobile phone technology. But as the human quest for progress advances and new frontiers are targeted, the challenges become more complex.

    Big data – from a satellite orbiting Mars, the genome data of an entire country or drug interactions in human or animal models – requires massive computing power. Such problems are too complex for even the most powerful of today’s supercomputers.

    As a consequence, many of the world’s biggest questions remain beyond the analytical grasp of traditional digital computers. But the next generation of computers is being created right now in the labs of technology leaders such as IBM, Google and others. These machines work in a completely different physical realm, seeking to exploit the mind-boggling properties of quantum physics.

    “This leap forward in computing could boost the performance of machine-learning algorithms and transform industries by providing new computational tools for materials science and algorithms to solve optimization tasks,” says Dr. Stefan Filipp, a quantum physicist and technical leader with IBM Research in Zurich.

  12. Tomi Engdahl says:


    The coldest place in the known universe is on Earth! It’s quantum computing company D-Wave’s HQ, and they actually let Linus in!

  13. Tomi Engdahl says:

    Boffins build a 2D ‘quantum walk’ that’s not a computer, but could still blow them away
    Analogue simulation a short-cut to faster computing

  14. Tomi Engdahl says:

    Fujitsu’s CMOS Digital Annealer Produces Quantum Computer Speeds

    Fujitsu has designed a new computer architecture running on silicon that the company claims rivals that of quantum computers in utility. Dubbed the Digital Annealer, Fujitsu has begun offering cloud services this month employing the technology to resolve combinatorial optimization problems such as finding similarities between patterns of molecules to speed up drug discovery, choosing investments for financial portfolios, and rearranging the layout of components in warehouses and factories to increase productivity.

    The announced service comes as activity in the quantum computer field ramps up. D-Wave Systems based in Burnaby, Canada, is marketing its latest generation 2000Q quantum annealer computer and is racing to introduce a 5,000-qubit model within the next two years

  15. Tomi Engdahl says:

    Fujitsu’s CMOS Digital Annealer Produces Quantum Computer Speeds

    While quantum computer makers struggle to bring down costs, the Japanese computer giant has created a dedicated silicon chip to match quantum computer performance

  16. Tomi Engdahl says:

    The password should be replaced by a passphrase

    Almost half of Finns use the same password in several services. According to Delay’s survey, 46 percent of Finns are guilty of this very common mistake. According to Delay, the salutation would solve the problem for many users.

    The issue of cyberspace security conducted in spring this year reveals that every third Finnish password is easy to remember for a number or letter combination. Every fifth of those surveyed say they use the same password at home and at work, and almost half recognize that they use the same single password on multiple web services.

    Different passwords should be used at least in the most critical accounts that can be accessed through multiple passwords through one password. If you use the same password for many services, it is quite possible that your username and password have already been leaked for some service. Using different passwords in different services significantly reduces the risk of being subjected to data interference.

    According to Delay’s survey, Finns are not very concerned about passwords. The worst about password usage is under 20 years of age. Less than every third respondent changes their password regularly. However, according to Deloitte’s security experts, changing the password does not always increase security

    - I would like to forget about the complexity of the passwords and focus on the length. The statement is a password-safe option. What makes people feel complicated and hard to guess passwords is almost as easy to break down as a simpler word. Complex character and character requirements often only make it difficult to remember a password.


  17. Tomi Engdahl says:

    Intel’s New Path to Quantum Computing

    Intel’s director of quantum hardware, Jim Clarke, explains the company’s two quantum computing technologies

    Despite a comparatively late start, Intel is progressing quickly along the road to a useful quantum computer. The company’s director of quantum hardware, Jim Clarke, came by IEEE Spectrum’s offices on 9 May to prove it.

    Tangle Lake, a specially packaged chip containing 49-superconducting qubits that Intel CEO Brian Krzanich, showed off at CES in January.

    The other was something new: a full silicon wafer of test chips, each containing up to 26-qubits that rely on the spins of individual electrons.

    IEEE Spectrum: What’s special about Tangle Lake?

    Jim Clarke: I can’t underscore, for these systems, how important the packaging is. Typically we make our computers to run at room temperature, in our back pocket or on our wrist or slightly higher temperatures, but never at a fraction of a degree above absolute zero [as you need for superconducting qubits]. So these guys developed a package that could withstand the temperatures mechanically and still be relatively clean from a signal perspective.

    IEEE Spectrum: Is there a limit to the density of qubits using the technology in Tangle Lake? Those pinouts look pretty big.

    Clarke: I think already this is the largest chip-to-[printed circuit board] attachment that Intel has ever done. So any larger than this on a single piece—the coefficient of thermal expansion and shrinkage would be severe. Not only that, as you see, the actual connectors have a very large footprint, and those are important right now.

    IEEE Spectrum: So how do you get to millions of qubits?

    Clarke: I can see a path with this technology to perhaps 1000. Beyond that, I think you have to get creative. That’s one of the reasons that we’re working on multiple qubit technologies.

    IEEE Spectrum: How’s the silicon spin qubit work?

    Clarke: Think of a conventional transistor with a steady stream of current flowing through it. Well, what we have is a single electron trapped in the transistor. That single electron can have one of two states: spin up or spin down. Those are the two states of the qubit. So what we are doing is essentially creating a series of single-electron transistors and coupling them together using our advanced transistor process technology.

    IEEE Spectrum: So how many qubits are on this one wafer?

    Clarke: Just like a conventional wafer, you dice it up into individual chips. Each chip has 3, 7, 11, or 26 qubits.

    We’re trying to build a quantum system that is extensible. So it can go [on without a hitch] whether it’s 50 qubits or whether it’s 1 million qubits.

  18. Tomi Engdahl says:

    How Close Are We—Really—to Building a Quantum Computer?

    Intel’s head of quantum computing talks about the challenges of developing algorithms, software programs and other necessities for a technology that doesn’t yet exist

    If we take a look at quantum computing, some will say this is the computing technology for the next 100 years. It’s natural for the U.S. and other governments to want to own it. The E.U. has a billion-dollar flagship that would fund quantum research across the E.U. China last fall announced a $10-billion research facility focused on quantum information sciences. The question is: What can we do as a country at the national level?

    What impact, if any, might quantum computing have on the development of artificial intelligence?

    Typically the first quantum algorithms that get proposed are for security (such as cryptography) or chemistry and materials modeling. These are problems that are essentially intractable with conventional computers. That said, there are a host of papers as well as start-up companies and university groups working on things like machine learning and AI using quantum computers. Given the time frame for AI development, I would expect conventional chips optimized specifically for AI algorithms to have more of an impact on the technology than quantum chips. Still, AI is certainly fair game for quantum computing.

    When will we see working quantum computers solving real-world problems?

    The first transistor was introduced in 1947. The first integrated circuit followed in 1958. Intel’s first microprocessor—which had only about 2,500 transistors—didn’t arrive until 1971. Each of those milestones was more than a decade apart. People think quantum computers are just around the corner, but history shows these advances take time. If 10 years from now we have a quantum computer that has a few thousand qubits, that would certainly change the world in the same way the first microprocessor did. We and others have been saying it’s 10 years away.

  19. Tomi Engdahl says:

    Finally, a Problem That Only Quantum Computers Will Ever Be Able to Solve
    June 21, 2018

    Computer scientists have been searching for years for a type of problem that a quantum computer can solve but that any possible future classical computer cannot. Now they’ve found one.

  20. Tomi Engdahl says:

    Quantum Computing Becoming Real

    Technology has the potential to reshape processing everywhere, starting with limited scientific and commercial applications.

  21. Tomi Engdahl says:

    Quantum Computing Becoming Real

    Technology has the potential to reshape processing everywhere, starting with limited scientific and commercial applications.

    Quantum computing will begin rolling out in increasingly useful ways over the next few years, setting the stage for what ultimately could lead to a shakeup in high-performance computing and eventually in the cloud.

    Quantum computing has long been viewed as some futuristic research project with possible commercial applications. It typically needs to run at temperatures close to absolute zero, which means most people never actually will see this technology in action, which is probably a good thing because quantum computers today are still a sea of crudely connected cables. And so far, it has proven difficult to create enough qubits for a long enough period of time to be useful. But the tide appears to be turning, both for how to extend the lifetime of quantum bits, also known as qubits, as well as the number of qubits that are available.

    “The first applications will probably be in things like quantum chemistry or quantum simulations,”

    “People are looking for new materials, simulating molecules such as drug molecules, and to do that you probably only need to be at around 100 qubits. We’re at 50 qubits today. So we’re not that far off. It’s going to happen within the next year or two. The example I give is the caffeine molecule, because it’s a molecule we all love. It’s a fairly small molecule that has 95 electrons. To simulate the molecule, you simulate the electron states. But if you were to exactly simulate the 95 electrons on that to actually figure out the energy state configuration, it would take 1048 classical bits. There are 1050 atoms in the planet Earth, so there’s no way you’re ever going to build a system with 1048 classical bits. It’s nuts. It would only require 160 qubits to do those all exactly, because the qubits can take on exactly all the quantum states and have all the right entanglements.”

    Exact numbers and timing tend to get a bit fuzzy here.

    “There are two elements driving this technology,” said Jean-Eric Michellet, senior director of innovation and technology at Leti. “One is the quality of the qubit. The other is the number of qubits. You need to achieve both quality and quantity, and that is a race that is going on right now.”

    These two factors are closely intertwined, because there also are two different types of qubits, logical and physical. The logical qubit can be used for programming, while the physical qubit is an actual implementation of a qubit. Depending on the quality of the qubit, which is measured in accuracy and coherency time (how long a qubit lasts), the ratio of logical and physical qubits will change. The lower the quality, the more physical qubits are required.

    Challenges remain
    Today’s qubits are far from perfect. Unlike classical bits, they don’t exist for very long, and they aren’t completely accurate.

    “That’s the major focus for quantum computing right now,” said IBM’s Welser. “It’s not only how to increase the number of qubits, which we know how to do just by continuing to build more of them. But how do you build them and get the error rates down, and increase coherency time, so that you can actually have time to manipulate those qubits and have them interact together? If you have 100 qubits, but the coherency time is only 100 microseconds, you can’t get them all to interact efficiently to do an actual algorithm before they all have an error.

  22. Tomi Engdahl says:

    Wired and IBM Explain Quantum Computing to Students from Grade School to Grad School

    Have you ever heard the old axiom that if you want to design a simple system, ask yourself if your grandmother could use it? Maybe that was on Wired’s mind because they asked a quantum computing expert — particularly IBM’s [Dr. Talia Gershon] — to explain what exactly quantum computing is at 5 levels. In the video they shot, which you can see below, [Dr. Gershon] talks to a younger child, a teenager, an undergraduate computer science student, a graduate student, and then a physicist.

    Quantum Computing Expert Explains One Concept in 5 Levels of Difficulty | WIRED


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