/Building Quantum Computers One Block At A Time (VIDEO) | Asian Scientist Magazine (via Qpute.com)

Building Quantum Computers One Block At A Time (VIDEO) | Asian Scientist Magazine (via Qpute.com)


AsianScientist (Apr. 15, 2020) – As the proverbial saying goes, “When all you have is a hammer, everything looks like a nail.”

For those unfamiliar, the phrase was first uttered by noted American psychologist Abraham Maslow, describing the tendency of individuals to rely on familiar tools. But as scientists increasingly turn to computational devices to solve some of our most perplexing enigmas, classical computers may not be enough.

This is where quantum computers come into play. With the ability to run calculations exponentially faster than their classical counterparts, quantum computers can help researchers simulate intricate chemical interactions, forecast notoriously unpredictable weather conditions and decipher impossibly complex logistical optimization problems. Yvonne Gao, an assistant professor at the National University of Singapore, is actively researching new ways to realize the full potential of quantum computers.

Quantum computers are based on quantum bits, or qubits. Instead of being confined to binary values of ‘0’ and ‘1’ like in a classical computer, qubits can take on multiple states at the same time, said Gao. It’s a concept similar to Erwin Schrodinger’s classic thought experiment—the cat can be both dead and alive.

However, individual qubits are insufficient. They need to interact with each other for quantum computation. To allow such interactions between isolated particles, Gao ‘entangles’ them together.

“(It’s like having) two twin cats whose fates are intertwined with each other,” she explained. “They’re either both dead, or both alive.”

Following years of cumulative research by scientists worldwide, quantum computing has shown early signs of promise. According to a paper published in Nature last October 2019, Google’s quantum computer Sycamore finally claimed quantum supremacy, meaning that it can perform a computational task that classical computers find impossible to do. It did this by solving a task that would take approximately 10,000 years on state-of-the-art classical supercomputers in a mere 200 seconds.

Nevertheless, the task performed by Sycamore was mainly a laboratory test to demonstrate its potential; deploying it to solve practical, real world problems is still very much work in progress.

“Right now, (quantum computers only) have ten to 100 qubits and it’s working at a level that’s good enough to start showing the potential impacts. To get meaningful outcomes, we’ll need to both scale the number of qubits from hundreds to probably millions, and scale the performance of those qubits from an error rate of one in every thousand operations to one in a million operations,” explained Gao.

But achieving this isn’t as straight forward as cramming more and more qubits together; doing so causes unwanted interactions between them and increases the error rate in the process. Instead of piling everything together at once, Gao intends to build the individual components first, before piecing them together like Lego blocks.

“I’ll be starting a new group on building modular quantum hardware, small building blocks that can go into a quantum computer eventually,” Gao explained. “By doing so, we will get small isolated device (linked together by quantum communication channels) that can circumvent the problem of crosstalk, while still having the scale that we need.”

Another advantage of her modular approach is that faulty devices could be easily removed from the chain and fixed independently.

“If we have a local failure, we can turn off these connected links, replace that individual part and we’re back in business without having to replace a whole lot of components that are otherwise functioning fine,” she shared.

Although we’re still at the early stages of quantum computing, Gao is cautiously optimistic.

“(The initial steps from) zero to one qubit… and one to several tens of qubits are really hard. But once we know the kind of problems we need to think about and the kind of tricks that we can do, (moving) from hundred to a million (qubits) will be a slightly faster trajectory.”


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