‘We Need A Lot More Machines’

In November, IBM introduced its 127-qubit quantum processor Eagle, which showed that the dream of achieving true quantum computing power appears to be on the right track — although work must continue before real applications of the technology can be realized.

The demand for the development of quantum computers, which apply quantum physics to computations and data storage, stems from the belief that they will solve problems more accurately, faster, and at a lower cost than current computing machines. Many players, from AT&T and Amazon to Zapata Computing and Xanadu, have their hands on some aspects of quantum computing development.

Breaking the 100-qubit threshold for quantum processors is the next step in achieving the so-called ‘quantum advantage’. This is when quantum computers should demonstrate their ability to vastly outpace classical computers. IBM says the Eagle is their proof that the quantum advantage will be achievable by 2023.

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There could be frothy chatter with vague numbers and promises being made about them that could boost quantum computing sales. “Some of the noise out there, some of the qubits you hear about don’t actually work,” says Robert Sottor, chief quantum advocate at IBM. He explains that it is not enough to produce individual qubits; They should bond and work together to count. “If they can’t, we can’t implement a quantum computing model to do the kinds of computations we want.”

Sotor says the 100-kilobit threshold has been a major hurdle in efforts to achieve a quantum advantage. With a processor containing several hundred qubits, he says, they may be needed to work together to demonstrate the huge improvement that quantum computers must offer over classical computers.

In addition to the strides being made in hardware, quantum computing is finding its place in the cloud. “Both Microsoft and Amazon came up with this idea of ​​having third-party hardware access their environments,” says Konstantinos Karagiannis, co-director of quantum computing services with business consultancy Protiviti. He also expects Google to do something similar soon. “They’re already working on their own devices.”

Other activities in this space include the launch in October of the AWS Center for Quantum Computing in partnership with the California Institute of Technology, a joint effort at a facility in Pasadena to build quantum computers. The investments are being made in use cases for the financial world, says Karagiannis, at least to get proof of concept in the works. “This is going to be a tough thing to catch up with,” he says. “We’ve seen this in machine learning.”

If you are not awake to seize the opportunity, you will lose

Companies that waited on machine learning may have found themselves falling behind while peers sought such resources, says Karagiannis. “Trying to make a big splash in machine learning is now very difficult,” he says. “All good things have already been created.” Something similar might happen with quantum computing.

Hiring employees who can support innovation in quantum computing can be challenging because it can require more than a quick update of traditional development skills to work in the field, Karagiannis says. “You have to have some understanding of linear algebra, some basic understanding of the physics behind it,” he says. “Machine learning background is also helpful. Finding this talent synergy is a bit challenging.” Karagiannis predicts that there will be a 30%-40% increase annually in the need for such talent.

At the moment, it seems that the more technology developers contribute to the development of quantum computing, the happier they are. “We need more machines and we want them to be a lot better,” Karagiannis says. As more companies discuss ways to create quantum processors, he says they can offer new ways to discover best practices in production. “We need to continually encourage these materials, science, research, and methods.”

Not every business or sector necessarily sees an immediate need for quantum computers, says Sutter. He says financial services, chemistry and logistics may benefit from this upcoming development of computers.

Sotor says that the pace of progress in quantum computers is largely determined by the scale of interconnected qubits. Another factor, he says, is the quality of the qubits, including keeping them cool and in the dark, away from interference. This is to reduce background “noise” that might interfere with processing capabilities.

With their ever-increasing power, quantum computers should make tasks that were once huge much easier to complete. For example, Sutter says that a chemical calculation performed two years ago that took 4.5 billion quantum calculations required about 290 days to complete with a classical computer. “We can do it in seven hours now,” he says. “We have changed the way classical and quantum computers work together. We have improved the algorithms. We have improved the quantum computers themselves.”

Sutor says the next step in 2022 for IBM will be to produce a 433-kilobit processor.

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