AsianScientist (Oct. 16, 2018) – What would car manufacturers do with a quantum computer?
Plenty, it turns out. For one, automakers are interested in quantum computing for security reasons—when these new, qubit-crunching machines come online at some point in the next few decades, they are expected to be able to break classical encryption protocols with their exponentially superior processing power.
This means that security protocols currently installed in vehicles—now chockful of software and electronics—will be at risk, said Professor Gu Mile, an assistant professor and quantum technology researcher at Nanyang Technological University in Singapore.
“[Automakers] have to take that into account now when designing cars that are meant to last for the next 10 to 15 years,” Gu told me, recounting a conversation he had with industry representatives.
The auto industry isn’t the only one preparing for what has been termed the Second Quantum Revolution, said Gu, who specializes in developing software for quantum computers.
“In many industries, it’s already becoming relevant to understand the capabilities of quantum computers… if someone wants to invest heavily in blockchain technology”—widely hailed as a tamper-resistant method of recording transactions—“they should be made aware that its security does not account for quantum computers,” said Gu.
No errors allowed
If blockchain and AI are today’s technology superstars, quantum technology is shaping up to be the poster child of the decades to come. National initiatives in several countries are already pouring money into the field: the US Congress recently passed the National Quantum Initiative to the tune of US$1.3 billion; China is reportedly building a US$10 billion National Laboratory for Quantum Information Sciences; and Singapore’s National Research Foundation has just announced that it will be investing US$18.2 million in quantum engineering.
That said, important technical hurdles still need to be overcome before quantum computers can be used at scale in the real world, said Gu. In classical computers, a piece of information is encoded in a series of redundant bits, such that errors—the accidental ‘flipping’ of a bit between a 1 and a 0, for example—can be detected and corrected. Current implementations of quantum computers, however, can’t carry out error correction, because encoding such redundancies is as yet too challenging.
“[In quantum computers], error catches up to computations rather quickly; after a few steps, they are dominated by errors, so we can’t get any useful results,” explained Gu. “Before full quantum software can be applied to real-life systems, we need actual error-correcting quantum computers. The timeline for that is probably about five to ten years away.”
While this isn’t a long time where technological advances are concerned, investors seeking a quick return on investment shouldn’t hold their breaths, he added.
These challenges haven’t stopped industry players from setting their sights on quantum technology.
“Big tech companies in China and US are now actively hiring people specifically in quantum software, so that today they know what are the capabilities of tomorrow, and so they are not left behind trying to play catch-up once the technology actually hits,” said Gu, adding that academia is fast losing top talent to lucrative industry offers.
A glimpse of the future
One of Gu’s research interests involves developing quantum algorithms that can forecast the behavior of complex systems (such as social networks or the human brain) using minimal data.
“Nowadays we collect a lot of big data—we’re very good at this, maybe too good… but in a lot of cases we don’t know which pieces [of data] are relevant for future prediction,” he said.
Quantum computing allows researchers to isolate causes and make predictions much more precisely than classical methods, reflecting a better understanding of the systems in question, Gu explained.
While acknowledging the importance of developing quantum hardware, Gu thinks the potential and possibilities of quantum computing will be dictated by what the field can do with that hardware—which is in turn determined by the software these machines run.
“When we design software, we’re essentially also predicting the future—we’re telling people in industry what quantum computers can do, and what one has to watch out for,” Gu added.
Today, quantum computing is still in its infancy, and what we know about quantum computers—their ability to crack classical encryption protocols and to solve exponentially complicated equations in polynomial time, for instance—is merely the tip of the iceberg, said Gu.
The situation is not unlike when classical computers first came on the scene, he continued—people thought the machines would only be good for performing simulations that were too tedious for humans; yet today they are integral to countless applications beyond simulations.
“We keep finding new applications for classical information processing, and it’s going to be the same with quantum computing,” said Gu.
This article is from a monthly column called The Bug Report. Click here to see the other articles in this series.
Copyright: Asian Scientist Magazine; Photo: Shutterstock.
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