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Hardware

D-Wave Announces New Hardware, Compiler, and Plans For Quantum Computing (arstechnica.com) 23

On Tuesday, D-Wave released its roadmap for upcoming processors and software for its quantum annealers. The company is also announcing that it's going to be developing its own gate-based hardware, which it will offer in parallel with the quantum annealer. Ars Technica's John Timmer talked with company CEO Alan Baratz to understand all the announcements. An anonymous reader shares an excerpt from the report: The simplest part of the announcement to understand is what's happening with D-Wave's quantum-annealing processor. The current processor, called Advantage, has 5,000 qubits and 40,000 connections among them. These connections play a major role in the chip's performance as, if a direct connection between two qubits can't be established, others have to be used to act as a bridge, resulting in a lower effective qubit count. Starting this week, users of D-Wave's cloud service will have access to an updated version of Advantage. The qubit and connection stats will remain the same, but the device will be less influenced by noise in the system (in technical terms, its qubits will maintain their coherence longer). [...] Further out in the future is the follow-on system, Advantage 2, which is expected late next year or the year after. This will see another boost to the qubit count, going up to somewhere above 7,000. But the connectivity would go up considerably as well, with D-Wave targeting 20 connections per qubit.

D-Wave provides a set of developer tools it calls Ocean. In previous iterations, Ocean has allowed people to step back from directly controlling the hardware; instead, if a problem could be expressed as a quadratic unconstrained binary optimization (QUBO), Ocean could produce the commands needed to handle all the hardware configuration and run the problem on the optimizer. D-Wave referred to this as a hybrid problem solver, since Ocean would use classical computing to optimize the QUBO prior to execution. The only problem is that not everyone who might be interested in trying D-Wave hardware knows how to express their problem as a QUBO. So, the new version of Ocean will allow an additional layer of abstraction by allowing problems to be sent to the system in the format typically used by people who tend to solve these sorts of problems. "You will now be able to specify problems in the language that data scientists and data analysts understand," Baratz promised.

The biggest part of today's announcement, however, may be that D-Wave intends to also build gate-based hardware. Baratz explained that he thinks that optimization is likely to remain a valid approach, pointing to a draft publication that shows that structuring some optimization problems for gate-based hardware may be so computationally expensive that it would offset any gains the quantum hardware could provide. But it's also clear that gate-based hardware can solve an array of problems that a quantum annealer can't. He also argued that D-Wave has solved a number of problems that are currently limiting advances in gate-based hardware that uses electronic qubits called transmons. These include the amount and size of the hardware that's needed to send control signals to the qubits and the ability to pack qubits in densely enough so that they're easy to connect but not close enough that they start to interfere with each other. One of the problems D-Wave faces, however, is that the qubits it uses for its annealer aren't useful for gate-based systems. While they're based on the same bit of hardware (the Josephson junction), the annealer's qubits can only be set as up or down. A gate-based qubit needs to allow manipulations in three dimensions. So, the company is going to try building flux qubits, which also rely on Josephson junctions but use them in a different way. So, at least some of the company's engineering expertise should still apply.

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D-Wave Announces New Hardware, Compiler, and Plans For Quantum Computing

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  • "So, the company is going to try building flux qubits, which also rely on Josephson junctions but use them in a different way."

    Question 1: Am I the only one that went back over it trying to see if I was being punked?

    Question2: Can it outperform my circa-1995 solar calculator?

    I really do get lost in the jargon here.

    • Give us a break already.

      Slashdotters who reason from conclusion have been telling us that D-Wave is a scam since they first came on the scene. Because they read something in Popular Science in 1984.

      Meanwhile some of the biggest tech and aerospace companies in the world are buying their machines at each iteration for millions of dollars.

      The hubris to think that they're all being scammed because they know less than you is astonishing.

      • I have no opinion on how wise an investment the chips are, and I know next to nothing about quantum computing. I couldn't infer any sense of actual computational capacity delivered from the text. In 1984 I was reading Compute! and Compute's Gazette... not Popular Science.

        You, however, were... triggered.

      • by vbdasc ( 146051 )

        Meanwhile some of the biggest tech and aerospace companies in the world are buying their machines at each iteration for millions of dollars.

        I wonder what exactly problems do the aerospace companies intend to solve with these machines.

      • by gweihir ( 88907 )

        Meanwhile some of the biggest tech and aerospace companies in the world are buying their machines at each iteration for millions of dollars.

        That means absolutely nothing. Now, if small companies were "millions" are not pocket change would be buying these things. But they are not and for good reasons.

    • All I know is that you can briefly store the state of a flux qubit in a flux capacitor.

    • by gweihir ( 88907 )

      Question2: Can it outperform my circa-1995 solar calculator?

      Sure. There must be some specific meaningless benchmark were it can.

  • by Viol8 ( 599362 ) on Wednesday October 06, 2021 @09:00AM (#61866203) Homepage

    ... I seem to understand what quantum computer designers are talking about and yet not understand at the same time.

    • I am somewhat confident that is the point.

      If they could actually explain what this stuff is supposed to do on a basic level using simple language, the people currently funding this most likely would not be funding this.

      Another good example of this it the recent articles on DeFi or whatever it is called, most of the terms there are made up such that an outsider just glazes over trying to put the randomly named pieces together.
    • Funny, but, sadly, no mod points.
    • Mods: +1 Funny, schroedinger's cat reference
  • Being that most programmers, program their code with a very linear top-down approach where most of the programs out there rarely ever take advantage of the Multi-CPU core, or use the GPU for additional processing. Means that a lot of money is going to be spent for quantum computing with a lot of sub optimal code out there to really take advantage of it.

    Parallel processing is still an elective course in some colleges Computer Science Departments. I got my CS Degree 20 years ago, and Parallel processing was

    • and yes the code is wrong because I stupidly didn't make my > and < in Html friendly format.

    • "most of the programs out there rarely ever take advantage of the Multi-CPU core"

      Really? What do you think multi threaded and multi process programs do then? Its not 1985 any more.

    • >Being that most programmers, program their code with a very linear top-down approach where most of the programs out there rarely ever take advantage of the Multi-CPU core, or use the GPU for additional processing

      Maybe 20 years ago. Not now.

      I work in this field, so either continue with your outdated knowledge or move on.

  • What insoluble, computationally-intensive or just-plain-hard problems has quantum computing solved?
    • What insoluble, computationally-intensive or just-plain-hard problems has quantum computing solved?

      This question might be better asked to Lockheed Martin, USC, QuAIL (Google/NASA), Los Alomos National Laboratory, Oak Ridge National Laboratory, Temporal Defense Systems, or the Jülich Supercomputing Centre.

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