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Think quantum computing sounds nerdy? It could help save the planet or boost your retirement fund

Google recently made a big announcement. It wasn’t a new phone, a virtual assistant or an upgrade to its cloud services. What Google announced was an early milestone in the development of quantum computing that points to the technology’s promise.

Google CEO Sundar Pichai with its quantum computer machine, which the company says only needs a few minutes to perform a task that would take a supercomputer at least 10,000 years.

Google CEO Sundar Pichai with its quantum computer machine, which the company says only needs a few minutes to perform a task that would take a supercomputer at least 10,000 years.

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Google recently made a big announcement. It wasn’t a new phone, a virtual assistant or an upgrade to its cloud services. What Google announced was an early milestone in the development of quantum computing that points to the technology’s promise.

In a paper published in the top scientific journal Nature on Oct 23, Google reported that its  quantum chip could outperform the world’s fastest supercomputer in solving a particular mathematical problem. This lays a claim for what is known in the field as “quantum supremacy”. 

Specifically, the Google team ran a computation on 53 quantum bits (qubits, the basic unit of quantum computing) made of superconducting circuits on a chip measuring a few centimetres across. It took 200 seconds.

By contrast, it estimates that it would take 10,000 years to run the same calculation on the world’s biggest and fastest supercomputer, called Summit, which has 250 petabytes of memory filling the size of two basketball courts. 

We know that big quantum computers, when we can build them, will be able to do some impressive things.

Consider this seemingly simple problem. A delivery driver has parcels to drop at a few different locations around Singapore. What’s the optimal route for them to take? With five addresses, there are already 120 different possible permutations for the stops.

With 10 addresses, there are almost 3.5 million routes and with 15 delivery points, there are more than a trillion options. Finding the shortest routes is a problem that can tax even today’s supercomputers. 

Quantum computers could help to solve problems like this more easily. For example, specially designed quantum algorithms might be able to process all possible routes by exploiting the laws of quantum physics.

The same approach we know can be very helpful in other optimisation problems, known as facility location-allocation problems. Quantum solutions here are expected to allow us to efficiently plan shipping routes, build financial portfolios and manage energy use and production. 

Computer scientists have also described programs for quantum computers that can perform specific tasks, including breaking some cryptosystems and searching data. These programs are known as Shor’s and Grover’s algorithms respectively.

Quantum computers get their power from storing information in systems small enough to follow the rules of quantum physics, our most accurate understanding of how particles behave. Instead of a bit of information being either 0 or 1, a quantum bit can exist as a superposition of both 0 and 1. That makes possible new ways of processing data.

Unfortunately, the Google demonstration has no real useful application. It performs what is known as a sampling problem. Roughly put, it generates certain sequences of numbers from a large unknown probability distribution which is difficult to do using today’s classical computing.

So, is it simply an interesting but “useless” and overhyped scientific result? Or does it signify the dawn of a new era? 

There has been intense discussion of the result since the news leaked out in September, following the accidental release of an internal report ahead of the Nature paper. 

IBM, which built the Summit supercomputer and has its own programme to build quantum computers, pointed out that another approach to simulating the sampling problem that would make it possible to reproduce Google’s work on Summit in just 2.5 days, not 10,000 years. 

That’s interesting, but it doesn’t diminish Google’s scientific achievement. The quantum computer is still faster – and its power will grow exponentially with the number of qubits. Add just a few more qubits and you would need several Summits to match the computation.

To compete with 60 qubits, you’d need 50 or so Summits. For 70 qubits, you’d need enough Summits to fill a good chunk of Singapore. 

So how do we make quantum computing machines useful for humankind?

There are still hard challenges ahead. Most of the impressive quantum algorithms, including Grover’s and Shor’s, will require thousands or millions of qubits to do useful work.

Remember that the state-of-the-art Google chip has just 53 qubits. It is a difficult problem, needing more work by scientists and engineers, to build bigger devices that still have good control of the qubits.

Other industry and academic efforts to build quantum computers, whether for superconducting systems or competing technologies such as trapped ions, also number a few tens of qubits.

We don’t know how long it will take us to get to million-qubit machines, so what we’re focused on now is turning the power of the soon-to-be-reached few hundred qubits devices into something useful.

Recently, we have figured out ways to get value from just a few hundred qubits by using hybrid quantum classical algorithms and possibly solve important problems in chemistry and optimisation. This is a major development in quantum algorithm design. My group in the Centre for Quantum Technologies at the National University of Singapore, along with researchers worldwide, is working in this field. 

I collaborated with Google’s quantum team in 2017 to run experiments on a precursor of their current chip, using just nine-quantum bits to simulate the inner workings of exotic materials. Exotic materials, like superconducting wires that work at room temperature for example, could be used for transporting electricity with zero losses.

We managed to shed light on these problems by simulating how electrons interact in the presence of strong magnetic fields using this prototype nine-qubit quantum processor. 

There’s promise for even small quantum computers to help us design better materials, simulate the structure of molecules for drug discovery, or find more efficient ways to make chemicals with less of an impact on the environment.

As the machines scale up, we could also see the uses mentioned earlier, in optimising logistics or financial portfolios and for machine learning and artificial intelligence tasks. 

This may not sound as exciting to the average reader as a glossy new consumer product, but quantum computers crunching problems behind the scenes might, through these applications, contribute to your future healthcare, to saving energy to protect the planet or to growing your retirement fund. 

Here in Singapore, we are not only waiting to see how this future unfolds, we’re also working to make it happen.

There are over 40 research groups with quantum expertise nationwide. As well as quantum computing, local teams are working on technologies for communication and sensing that get benefits from the same effects that power quantum computers. 

With a long-term vision and sustained support to educate and attract quantum specialists at all levels, I think Singapore is well equipped to play a global role in the emerging quantum era. We’re ready on the runway. 



Dimitris Angelakis is a Principal Investigator and Research Associate Professor at the Centre for Quantum Technologies, National University of Singapore.

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