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:

    How much faster is a quantum computer than your laptop?
    Supercomputing chaps talk qubits and more with Dan Olds

    It turns out that there are three broad categories of problem where your best bet is a quantum computer. The first is a Monte Carlo type simulation, the second is machine learning, and the third is optimization problems that would drive a regular computer nuts – or, at least, take a long time for it to process.

    An example of this type of optimization problem is this: Consider the approximately 2,000 professional hockey players in North America. Your task is to select the very best starting line-up from that roster of guys.

    There are a lot of variables to consider.

    When you start adding variables like this, the problem gets exponentially more difficult to solve.

    But it’s right up the alley of a quantum computer. A D Wave system would consider all of the possible solutions at the same time, then collapse down to the optimal set of player. It’s more complicated than I’m making out, of course, but it’s a good layman-like example.

    So how much faster can quantum computers perform than their digital counterparts? Before purchasing their own D Wave system a few years back, Google put it through its paces and found that when the problem size got to the 500 qubit size range, the D Wave system outperformed its binary cousins by 10,000 times – a solid win in anyone’s book.

    More recently, Google and NASA found that a D Wave 2 system with 1,097 qubits outperformed existing supercomputers by more than 3,600 times (and personal computers by 100 million x) on an optimization problem, solving it in mere seconds.

    These performance numbers I’m citing are from corner cases that hit right on the quantum sweet spot.

  2. Tomi Engdahl says:

    Shor’s Algorithm In Five Atoms

    If you want to factor a number, one way to do it is Shor’s algorithm. That’s a quantum algorithm and finds prime factors of integers. That’s interesting because prime factorization is a big deal of creating or breaking most modern encryption techniques.

    Back in 2001, a group at IBM factored 15 (the smallest number that the algorithm can factor) using a 7 qubit system that uses nuclear magnetic resonance. Later, other groups duplicated the feat using photonic qubits. Typical implementations take 12 qubits. However, recent work at MIT and the University of Innsbruck can do the same trick with 5 atoms caught in an ion trap. The researchers believe their implementation will easily scale to larger numbers.

    Each qubit is an atom and LASER pulses perform the logic operations.

    The beginning of the end for encryption schemes?
    New quantum computer, based on five atoms, factors numbers in a scalable way.

    What are the prime factors, or multipliers, for the number 15? Most grade school students know the answer — 3 and 5 — by memory. A larger number, such as 91, may take some pen and paper. An even larger number, say with 232 digits, can (and has) taken scientists two years to factor, using hundreds of classical computers operating in parallel.

    Because factoring large numbers is so devilishly hard, this “factoring problem” is the basis for many encryption schemes for protecting credit cards, state secrets, and other confidential data. It’s thought that a single quantum computer may easily crack this problem, by using hundreds of atoms, essentially in parallel, to quickly factor huge numbers.

    In 1994, Peter Shor, the Morss Professor of Applied Mathematics at MIT, came up with a quantum algorithm that calculates the prime factors of a large number, vastly more efficiently than a classical computer. However, the algorithm’s success depends on a computer with a large number of quantum bits. While others have attempted to implement Shor’s algorithm in various quantum systems, none have been able to do so with more than a few quantum bits, in a scalable way.

    Now, in a paper published today in the journal Science, researchers from MIT and the University of Innsbruck in Austria report that they have designed and built a quantum computer from five atoms in an ion trap. The computer uses laser pulses to carry out Shor’s algorithm on each atom, to correctly factor the number 15. The system is designed in such a way that more atoms and lasers can be added to build a bigger and faster quantum computer, able to factor much larger numbers. The results, they say, represent the first scalable implementation of Shor’s algorithm.

  3. Tomi Engdahl says:

    Ion Trap Makes Programmable Quantum Computer

    The Joint Quantum Institute published a recent paper detailing a quantum computer constructed with five qubits formed from trapped ions. The novel architecture allows the computer to accept programs for multiple algorithms.

    Quantum computers make use of qubits and trapped ions–ions confined with an electromagnetic field–are one way to create them. In particular, a linear radio frequency trap and laser cooling traps five ytterbium ions with a separation of about 5 microns. To entangle the qubits, the device uses 50 to 100 laser pulses on individual or pairs of ions. The pulse shape determines the actual function performed, which is how the device is programmable. The operations depend on the sequence of laser pulses that activate it.

    Ion-trap quantum computer is programmable and reconfigurable

    Five-ion trap

    Chris Monroe’s group at the Joint Quantum Institute and the Joint Center for Quantum Information and Computer Science, at the University of Maryland in the US, uses trapped ions as qubits. In this technique, information is stored in the atomic-ions’ states. Electromagnetically confining a number of such ions, or “trapping” them, the particles can then be entangled by applying appropriate laser beams. The finely tuned laser light manipulates each ion in a specific way, depending upon its state. “In this way, the collective motion of the chain of ions behaves as a data bus that allows qubits to talk to each other,” say Monroe.

    While small ion-trap quantum computers have previously been built, each was a single-purpose device, capable of running a particular algorithm or generating a fixed entangled state. Now though, Monroe, together with Shantanu Debnath and colleagues, has demonstrated that the device can be programmed with multiple algorithms.

  4. Tomi Engdahl says:

    D-Wave’s 2,000-Qubit Quantum Annealing Computer Now 1,000x Faster Than Previous Generation

    D-Wave, a Canadian company developing the first commercial “quantum computer,” announced its next-generation quantum annealing computer with 2,000 qubits, which is twice as many as its previous generation had. One highly exciting aspect of quantum computers of all types is that beyond the seemingly Moore’s Law-like increase in number of qubits every two years, their performance increases much more than just 2x, unlike with regular microprocessors. This is because qubits can hold a value of 0, 1, or a superposition of the two, making quantum systems able to deal with much more complex information. If D-Wave’s 2,000-qubit computer is now 1,000 faster than the previous 1,000-qubit generation (D-Wave 2X), that would mean that, for the things Google tested last year, it should now be 100 billion times faster than a single-core CPU.

    Last year, Google said that D-Wave’s 1,000 qubit computer proved to be 100 million times faster than a classical computer with a single core: “We found that for problem instances involving nearly 1,000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10^8 times faster than simulated annealing running on a single core,” said Hartmut Neven, Google’s Director of Engineering.

    D-Wave’s 2,000-Qubit Quantum Annealing Computer Now 1,000x Faster Than Previous Generation,32768.html

  5. Tomi Engdahl says:

    System Bits: Oct. 25
    Quantum 3D wiring; special-purpose computer; inexact computing.

    Scalable quantum computers
    In what they say is a significant step towards to the realization of a scalable quantum computer, researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits.

    The quantum socket is a wiring method that uses 3D based on spring-loaded pins to address individual qubits, they said, and which connects classical electronics with quantum circuits, extendable far beyond current limits, from one to possibly a few thousand qubits.

    The team used microwave pulses to control and measure superconducting qubits, typically sent from dedicated sources and pulse generators through a network of cables connecting the qubits in the cryostat’s cold environment to the room-temperature electronics.

    New 3-D wiring technique brings scalable quantum computers closer to reality

  6. Tomi Engdahl says:

    D-Wave goes public with open-source quantum-classical hybrid software
    Search the universe with qbsolv

    Want to fool around with some quantum-ish computing? D-Wave has open sourced a software tool that prepares optimisation problems to run on its hardware.

    You can think of the software, qbsolv, as a D-Wave-specific compiler: in the white paper it’s posted along with the tool at GitHub, the company’s Michael Booth, Steven Reinhardt and Aidan Roy explain its role.

    Qbsolv is “a tool that solves large quadratic unconstrained binary optimisation (QUBO) problems” for execution on a D-Wave computer, a task that has to be handled with care because the problem has to be partitioned to match the number of qubits on the target chip.


Leave a Comment

Your email address will not be published. Required fields are marked *