D-Wave deployed what was considered the first commercial quantum computer in 2011. A handful of D-Wave’s quantum computers are now being used by Google, NASA and Lockheed Martin for artificial intelligence, image recognition and machine learning.
D-Wave now has a pipeline of government, commercial and intelligence customers waiting for the company’s faster quantum computers, which will start rolling out later this year, said CEO Vern Brownell.
The company will release faster processors over the next two years that will be central to the new quantum computers, Brownell said. The company currently offers the D-Wave Two, which financial analyst firm Sterne Agee in March estimated had a list price “north of $10 million.”
D-Wave last week received US$28 million in funding from new and existing investors, including Goldman Sachs and BDC Capital. The investment will be used to boost internal software development efforts, but there is room for more funding, Brownell said. The goal is to take the company public in a few years, Brownell said.
D-Wave has 1,152-qubit chips in its lab right now, and hopes to double that to a 2,000-qubit processor next year.
Researchers at Microsoft and universities have said D-Wave’s computer exhibits the behavior of a quantum computer, though IBM and others have argued otherwise.
IBM last week said it is investing $3 billion over the next five years to build new types of systems, including quantum and cognitive computers, and Microsoft is researching quantum computing based on a new particle.
IEEE explains other technological challenges and improvements made with each chip iteration of a couple of months
D-Wave initially thought it would rely on analog control lines that could apply a magnetic field to the superconducting qubits and control their quantum states in that manner. However, the company realized early on in development that it would need at least six or seven control lines per qubit, for a programmable computer. The dream of eventually building more powerful machines with thousands of qubits would become an “impossible engineering challenge” with such design requirements, Hilton says.
The solution came in the form of digital-to-analog flux converters (DAC)—each about the size of a human red blood cell at 10 micrometers in width— that act as control devices and sit directly on the quantum computer chip. Such devices can replace control lines by acting as a form of programmable magnetic memory that produces a static magnetic field to affect nearby qubits. D-Wave can reprogram the DACs digitally to change the “bias” of their magnetic fields, which in turn affects the quantum computing operations.
Both the D-Wave One (128 qubits) and D-Wave Two (512 qubits) processors have DACs. But the circuitry setup of D-Wave One created some problems between the programming DAC phase and the quantum annealing operations phase. Specifically, the D-Wave One programming phase temporarily raised the temperature to as much as 500 millikelvin, which only dropped back down to the 20 millikelvin temperature necessary for quantum annealing after one second. That’s a significant delay for a machine that can perform quantum annealing in just 20 microseconds (20 millionths of a second).
By simplifying the hardware architecture and adding some more control lines, D-Wave managed to largely eliminate the temperature rise. That in turn reduced the post-programming delay to about 10 milliseconds (10 thousandths of a second)— a “factor of 100 improvement achieved within one processor generation,” Hilton says. D-Wave also managed to reduce the physical size of the DAC “footprint” by about 50 percent in D-Wave Two.
Traditional experiments in quantum computing have qubits in almost perfect isolation. But if you want quantum computing to be scalable, it will have to be immersed in a sea of computing complexity.”
Still, D-Wave’s current hardware architecture, code-named “Chimera,” should be capable of building quantum computing machines of up to 8000 qubits, Hilton says. The company is also working on building a larger processor architecture beyond 10000 qubits.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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