Quantum Computing, who wins the race for Supremacy?

Posted by Peter Rudin on 28. September 2016 in Essay



As Moore’s law is coming to an end (See the Essay from 25.06.2016 under ARCHIVES) the race is on to build new computer hardware to meet the still exponentially growing demand for higher computer performance.

Quantum computing is the technology that many scientists, entrepreneurs and big businesses expect to provide a quantum leap into the future.

With normal computers, or classical computers as they are now called, there are only two options for processing information – on and off –. A computer “bit”, the smallest unit into which all information is broken down, is either a “1” or a “0”. The computational power of a normal computer is dependent on the number of binary transistors – tiny power switches – that are contained within its microprocessor.  Back in 1971 the first Intel processor was made up of 2,300 transistors. Intel now produces microprocessors with more than 5bn transistors. However, they’re still limited by their simple binary options.

Quantum computing chips are made up of devices called qubits that represent digital data using quantum effects. In the subatomic realm of quantum physics, particles can be particle or wave or particle and wave. This is what’s known in quantum mechanics as superposition. As a result of superposition a qubit can be a ‘0 or 1’ but also a ‘0 and 1’. That means it can perform two equations at the same time. Two qubits can perform four equations. And three qubits can perform eight, and so on in an exponential expansion. This leads to some inconceivably large numbers, not to mention some mind-boggling working concepts to solve complex problems.

Such problems exist for example in:

  • machine learning/deep learning
  • cognitive computing/artificial intelligence (AI)
  • pattern recognition and anomaly detection
  • financial analysis
  • software/hardware verification and validation
  • scheduling and logistics
  • precision medicine
  • bioinformatics

Experts generally agree that quantum computers could solve these problems quickly, often in mere seconds instead of days and weeks that the most powerful binary computers would require today.

D-Wave Systems a Canadian company which builds the first commercially available quantum computers has delivered systems to NASA, Google, Los Alamos National Laboratory, Lockheed Martin, and others. There is a debate in academic circles about whether the D-Wave system is a fully qualified quantum computer on the grounds that it does quantum annealing and hence is designed to tackle only a subset of all quantum computing problems. Some academic scientists agree that the D-Wave system is fully qualified, while others vehemently disagree.

In addition to venture capital-funded D-Wave Systems with investors like Jeff Bezos from Amazon, both IBM and Google are working on their own quantum computing development. IBM believes it can demonstrate an experimental chip that will prove the power of quantum computers in just a few years. The chips IBM announced in May 2016 have five and seven qubits. The best chip Google’s lead researchers had produced up to then had nine qubits.

Scott Aaronson, an associate professor at MIT, says a collection of just 50 qubits is likely to be the first computer to demonstrate “quantum supremacy”—the power to solve a computational problem immensely difficult and perhaps practically impossible for conventional machines.

In December 2015, Google and NASA announced that their shared D-Wave 2X quantum annealing computer solved a complex optimization problem up to 100 million times faster than a single-core classic computer did. Google said these results were “intriguing and very encouraging,” although there is “more work ahead to turn quantum enhanced optimization into a practical technology.”

To spread the know-how necessary to program its quantum chip, IBM provides a web service called Composer. Tutorials explain how to drag and drop different quantum logic gates to create an algorithm, which can then be run on the chip sitting in IBM’s lab. . “We want to help people think differently and learn how to program a quantum computer,” says Jerry Chow who manages IBM’s quantum computing group at the company’s Thomas J. Watson research center in Yorktown Heights, New York.

An article published in August 2016 by the New Scientist provides an insight into Google’s plan for quantum computer supremacy. The field of quantum computing is undergoing a rapid shake-up, and engineers at Google have quietly set out a plan to dominate it. Its engineers published a paper on August 3, 2016 detailing their plans (arxiv.org/abs/1608.00263). Their goal, audaciously named quantum supremacy, is to build the first quantum computer capable of performing a task no classical computer can. By combining analogue and digital concepts the Google research team has made great progress to handle the problem of error correction that has plagued quantum computers in the past.

The time-line to produce a commercially viable, general purpose quantum computer has been significantly shortened by the accomplishments of Google’s research team.  A breakthrough could already be achieved by year-end. Others are a bit more cautious. “I think this is achievable within two or three years,” says Matthias Troyer at the Swiss Federal Institute of Technology in Zurich. “They’ve shown concrete steps on how they will do it.”

Their expertise and knowledge in the artificial intelligence arena of deep learning combined with their knowledge in quantum computing will give Google a unique advantage to become the leader in personal assistant software and related business-to-consumer applications.  Competitors like Microsoft, Face-Book or Apple should not be discounted as they are engaged in Quantum Computing and/or Artificial Intelligence research as well. However they all lack the ‘de-facto’ world standard of information search and retrieval which represents Google’s core business.

In the business-to-business segment IBM and its Watson Cloud-Platform have been engaged in cognitive computer applications for several years. Working with partners they have applied artificial intelligence algorithms and systems to industry segments such as medical, logistics, financial, tourism and others. IBM has made major investments into their Watson Group and it is generally believed that the success of Watson is tightly linked to the future of IBM. Today Watson runs on standard binary transistors platforms. The exploitation of their research efforts in quantum computing might be another building block towards the future of IBM.

Besides their engagement in quantum computing, IBM research is working on other processor concepts.  Their ‘True North’ chip is an example of neuromorphic computing, which is designed to mimic the human brain. Each chip is powerful, with 1 million neurons and 256 million synapses, and they are assembled on boards with 16 chips, creating systems with 16 million neurons and 4 billion synapses. In comparison a human brain has approx. 100 billion neurons. Since the chip processes information differently, by using the neuron model of the brain, in which each neuron fires only when needed, the chip is not working constantly.  IBM and others claim that this makes the chip much more energy efficient compared to silicon-based transistors.

Taking a top-down view, it is staggering to see at what speed information technology is advancing. That a computer would beat the world’s best Go-Player as  Google’s Deep Mind system did in March 2016 was anticipated. Most experts however had forecasted that this landmark event would happen in 5 to 10 years from now. The same holds true for the unpredicted advancements in quantum computing.

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